fix(infra): ml-serving LITELLM_URL default → host.docker.internal:4000

Inside the container, llm.alogins.net times out (public-DNS route, not the
loopback path Caddy listens on). host.docker.internal:4000 reaches the Agap
LiteLLM directly and is equivalent for dev. Prod deploys override via env.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

.env.example

@@ -0,0 +1,39 @@
+# Copy to .env.local and fill in values — never commit .env.local
+
+# API
+SESSION_SECRET=change-me-to-a-random-32-char-string
+PORT=3078
+NODE_ENV=development
+DATABASE_PATH=./data/oo.db
+# API_BASE_URL = public origin only, no path suffix (used to build OAuth redirect URIs)
+API_BASE_URL=http://localhost:3078
+WEB_BASE_URL=http://localhost:3000
+ML_SERVING_URL=http://localhost:8000
+
+# AI stack — shared Agap services (ollama + litellm + langfuse). Not run from oO.
+# Prod: https://llm.alogins.net  |  Dev: http://host.docker.internal:4000 from containers,
+# http://localhost:4000 from host. Ollama: http://host.docker.internal:11434 / :11434.
+LITELLM_URL=https://llm.alogins.net
+LITELLM_MASTER_KEY=sk-oo-dev
+OLLAMA_URL=http://host.docker.internal:11434
+
+# Google OAuth — https://console.cloud.google.com/
+GOOGLE_CLIENT_ID=
+GOOGLE_CLIENT_SECRET=
+
+# VAPID (Web Push) — generate: node -e "const wp=require('web-push');console.log(JSON.stringify(wp.generateVAPIDKeys()))"
+VAPID_PUBLIC_KEY=
+VAPID_PRIVATE_KEY=
+VAPID_SUBJECT=mailto:you@example.com
+
+# Todoist OAuth — https://developer.todoist.com/appconsole.html
+TODOIST_CLIENT_ID=
+TODOIST_CLIENT_SECRET=
+
+# Event bus — leave NATS_URL empty for in-process bus only (no JetStream bridge).
+# Set to nats://nats:4222 (compose service name) or nats://localhost:4222 (host)
+# to mirror every publish to durable JetStream streams (signals.>, feedback.>).
+# Start the broker with: docker compose --profile events up nats
+NATS_URL=
+# How often the background scheduler refreshes Todoist tasks per active user (ms).
+TODOIST_SYNC_INTERVAL_MS=900000

.gitignore

@@ -11,6 +11,7 @@ build/
 __pycache__/
 *.pyc
 .venv/
+__pycache__/
 .mypy_cache/
 .pytest_cache/
 .ruff_cache/
@@ -19,3 +20,4 @@ coverage/
 *.sqlite
 .idea/
 .vscode/
+.playwright-mcp/

.playwright-mcp/page-2026-04-14T14-06-03-068Z.yml

@@ -0,0 +1,2 @@
+- main [ref=e2] [cursor=pointer]:
+  - generic [ref=e3]: ···

.playwright-mcp/page-2026-04-14T14-06-35-398Z.yml

@@ -0,0 +1,119 @@
+- generic [ref=e3]:
+  - generic [ref=e5]:
+    - generic [ref=e8]:
+      - img "Google" [ref=e10]
+      - generic [ref=e11]: Sign in with Google
+    - generic [ref=e12]:
+      - generic [ref=e14]:
+        - heading "Sign in" [level=1] [ref=e15]
+        - paragraph [ref=e16]:
+          - text: to continue to
+          - button "alogins.net" [ref=e17] [cursor=pointer]
+      - generic [ref=e18]:
+        - generic [ref=e21]:
+          - generic [ref=e26]:
+            - textbox "Email or phone" [active] [ref=e27]
+            - generic:
+              - generic: Email or phone
+          - paragraph [ref=e28]:
+            - link "Forgot email?" [ref=e29] [cursor=pointer]:
+              - /url: /signin/v2/usernamerecovery?app_domain=https://o.alogins.net&client_id=225787180325-cesuikl95j1qg3aijh4j10n8n7usf65p.apps.googleusercontent.com&code_challenge=oJlG0iJD7GEnZ_p0tMbi56r9QGirq6lY0KHNKh-A7sI&code_challenge_method=S256&continue=https://accounts.google.com/signin/oauth/legacy/consent?authuser%3Dunknown%26part%3DAJi8hAP_s0wcqLhX3B4DTcLADDDkyjYYD_dTsSJST_xu2o-PkobLfbuk1XhXVndyBN6gkOnR0zh89fZIeMovlOB4w8i9PC5L8hRlhSDi_OSh3ki0cAZ8RRH7CMPl0NmSZbAb7253b7Sq7Uj7dN8TmsRtXQbgjYmbhyQtpViFok9UeZM7XROiV83I_xwzDvOMQD1WQkkCPL_ZjRyGIpPgmLbBXxUWwGnWs7x0CLlb2wOYMM4diy8wjIIVzACtLq0g_hnnf0y_mxrQYevSjMx1y6vLEeMZrKz4zXxSwX11OP6adWx8v9lVviJvM53GJLq4oV46GDTGcxuXLkt9W6FBgRJqMoh1oulT8tHVf1O4VG6FuQkvXnppbkH8b9OMEnqTaVlL1DVwPrvaEytsqZ79DQ74hKi9NiK3RE9wkvTaSElEARWCxILbbRjXR-GKwwybfKjQwGUZ9t2sYcJdZK3ygn8vZIYDrPIKQM8g27tJTfNj5yjjYJZsv-EMRSSvheUtOMdNBzy7fqqBKvxGQEO3iDfgy88NdOrw1AktvipSuf5E5uVlJ5KPLTq5J8TuKHO9TQcmBu9Fn1U1_NwlvMkvWbPJ2zbkshNe2q200XCnKF6Wz1bLG7sukKzEoyJkmc3x7poz1z9JQ4f7%26flowName%3DGeneralOAuthFlow%26as%3DS356240196%253A1776175595013373%26client_id%3D225787180325-cesuikl95j1qg3aijh4j10n8n7usf65p.apps.googleusercontent.com%23&dsh=S356240196:1776175595013373&flowName=GeneralOAuthLite&o2v=2&opparams=%253F&rart=ANgoxceHU_HzI34dur-e3VKjuSW_62nNyS0F-NAT8vowVRgzLCH8LgeU-dR_jmgEfEI3TjNPYuzeB6EBCMum_GguMnKcbkqUwFjfpff8YscBkT3joDYra5Q&redirect_uri=https://o.alogins.net/api/auth/callback&response_type=code&scope=openid+email+profile&service=lso&state=dfjtgpxO8h1eS83EqakZj
+        - generic [ref=e31]:
+          - button "Next" [ref=e33]
+          - link "Create account" [ref=e35] [cursor=pointer]:
+            - /url: /lifecycle/flows/signup?app_domain=https://o.alogins.net&client_id=225787180325-cesuikl95j1qg3aijh4j10n8n7usf65p.apps.googleusercontent.com&code_challenge=oJlG0iJD7GEnZ_p0tMbi56r9QGirq6lY0KHNKh-A7sI&code_challenge_method=S256&continue=https://accounts.google.com/signin/oauth/legacy/consent?authuser%3Dunknown%26part%3DAJi8hAP_s0wcqLhX3B4DTcLADDDkyjYYD_dTsSJST_xu2o-PkobLfbuk1XhXVndyBN6gkOnR0zh89fZIeMovlOB4w8i9PC5L8hRlhSDi_OSh3ki0cAZ8RRH7CMPl0NmSZbAb7253b7Sq7Uj7dN8TmsRtXQbgjYmbhyQtpViFok9UeZM7XROiV83I_xwzDvOMQD1WQkkCPL_ZjRyGIpPgmLbBXxUWwGnWs7x0CLlb2wOYMM4diy8wjIIVzACtLq0g_hnnf0y_mxrQYevSjMx1y6vLEeMZrKz4zXxSwX11OP6adWx8v9lVviJvM53GJLq4oV46GDTGcxuXLkt9W6FBgRJqMoh1oulT8tHVf1O4VG6FuQkvXnppbkH8b9OMEnqTaVlL1DVwPrvaEytsqZ79DQ74hKi9NiK3RE9wkvTaSElEARWCxILbbRjXR-GKwwybfKjQwGUZ9t2sYcJdZK3ygn8vZIYDrPIKQM8g27tJTfNj5yjjYJZsv-EMRSSvheUtOMdNBzy7fqqBKvxGQEO3iDfgy88NdOrw1AktvipSuf5E5uVlJ5KPLTq5J8TuKHO9TQcmBu9Fn1U1_NwlvMkvWbPJ2zbkshNe2q200XCnKF6Wz1bLG7sukKzEoyJkmc3x7poz1z9JQ4f7%26flowName%3DGeneralOAuthFlow%26as%3DS356240196%253A1776175595013373%26client_id%3D225787180325-cesuikl95j1qg3aijh4j10n8n7usf65p.apps.googleusercontent.com%23&dsh=S356240196:1776175595013373&flowEntry=SignUp&flowName=GlifWebSignIn&o2v=2&opparams=%253F&rart=ANgoxceHU_HzI34dur-e3VKjuSW_62nNyS0F-NAT8vowVRgzLCH8LgeU-dR_jmgEfEI3TjNPYuzeB6EBCMum_GguMnKcbkqUwFjfpff8YscBkT3joDYra5Q&redirect_uri=https://o.alogins.net/api/auth/callback&response_type=code&scope=openid+email+profile&service=lso&signInUrl=https://accounts.google.com/signin/oauth?app_domain%3Dhttps://o.alogins.net%26client_id%3D225787180325-cesuikl95j1qg3aijh4j10n8n7usf65p.apps.googleusercontent.com%26code_challenge%3DoJlG0iJD7GEnZ_p0tMbi56r9QGirq6lY0KHNKh-A7sI%26code_challenge_method%3DS256%26continue%3Dhttps://accounts.google.com/signin/oauth/legacy/consent?authuser%253Dunknown%2526part%253DAJi8hAP_s0wcqLhX3B4DTcLADDDkyjYYD_dTsSJST_xu2o-PkobLfbuk1XhXVndyBN6gkOnR0zh89fZIeMovlOB4w8i9PC5L8hRlhSDi_OSh3ki0cAZ8RRH7CMPl0NmSZbAb7253b7Sq7Uj7dN8TmsRtXQbgjYmbhyQtpViFok9UeZM7XROiV83I_xwzDvOMQD1WQkkCPL_ZjRyGIpPgmLbBXxUWwGnWs7x0CLlb2wOYMM4diy8wjIIVzACtLq0g_hnnf0y_mxrQYevSjMx1y6vLEeMZrKz4zXxSwX11OP6adWx8v9lVviJvM53GJLq4oV46GDTGcxuXLkt9W6FBgRJqMoh1oulT8tHVf1O4VG6FuQkvXnppbkH8b9OMEnqTaVlL1DVwPrvaEytsqZ79DQ74hKi9NiK3RE9wkvTaSElEARWCxILbbRjXR-GKwwybfKjQwGUZ9t2sYcJdZK3ygn8vZIYDrPIKQM8g27tJTfNj5yjjYJZsv-EMRSSvheUtOMdNBzy7fqqBKvxGQEO3iDfgy88NdOrw1AktvipSuf5E5uVlJ5KPLTq5J8TuKHO9TQcmBu9Fn1U1_NwlvMkvWbPJ2zbkshNe2q200XCnKF6Wz1bLG7sukKzEoyJkmc3x7poz1z9JQ4f7%2526flowName%253DGeneralOAuthFlow%2526as%253DS356240196%25253A1776175595013373%2526client_id%253D225787180325-cesuikl95j1qg3aijh4j10n8n7usf65p.apps.googleusercontent.com%2523%26dsh%3DS356240196:1776175595013373%26flowName%3DGeneralOAuthLite%26o2v%3D2%26opparams%3D%25253F%26rart%3DANgoxceHU_HzI34dur-e3VKjuSW_62nNyS0F-NAT8vowVRgzLCH8LgeU-dR_jmgEfEI3TjNPYuzeB6EBCMum_GguMnKcbkqUwFjfpff8YscBkT3joDYra5Q%26redirect_uri%3Dhttps://o.alogins.net/api/auth/callback%26response_type%3Dcode%26scope%3Dopenid%2Bemail%2Bprofile%26service%3Dlso%26state%3DdfjtgpxO8h1eS83EqakZj&state=dfjtgpxO8h1eS83EqakZj
+  - contentinfo [ref=e36]:
+    - combobox [ref=e39] [cursor=pointer]:
+      - option "Afrikaans"
+      - option "azərbaycan"
+      - option "bosanski"
+      - option "català"
+      - option "Čeština"
+      - option "Cymraeg"
+      - option "Dansk"
+      - option "Deutsch"
+      - option "eesti"
+      - option "English (United Kingdom)"
+      - option "English (United States)" [selected]
+      - option "Español (España)"
+      - option "Español (Latinoamérica)"
+      - option "euskara"
+      - option "Filipino"
+      - option "Français (Canada)"
+      - option "Français (France)"
+      - option "Gaeilge"
+      - option "galego"
+      - option "Hrvatski"
+      - option "Indonesia"
+      - option "isiZulu"
+      - option "íslenska"
+      - option "Italiano"
+      - option "Kiswahili"
+      - option "latviešu"
+      - option "lietuvių"
+      - option "magyar"
+      - option "Melayu"
+      - option "Nederlands"
+      - option "norsk"
+      - option "o‘zbek"
+      - option "polski"
+      - option "Português (Brasil)"
+      - option "Português (Portugal)"
+      - option "română"
+      - option "shqip"
+      - option "Slovenčina"
+      - option "slovenščina"
+      - option "srpski (latinica)"
+      - option "Suomi"
+      - option "Svenska"
+      - option "Tiếng Việt"
+      - option "Türkçe"
+      - option "Ελληνικά"
+      - option "беларуская"
+      - option "български"
+      - option "кыргызча"
+      - option "қазақ тілі"
+      - option "македонски"
+      - option "монгол"
+      - option "Русский"
+      - option "српски (ћирилица)"
+      - option "Українська"
+      - option "ქართული"
+      - option "հայերեն"
+      - option "‫עברית‬‎"
+      - option "‫اردو‬‎"
+      - option "‫العربية‬‎"
+      - option "‫فارسی‬‎"
+      - option "አማርኛ"
+      - option "नेपाली"
+      - option "मराठी"
+      - option "हिन्दी"
+      - option "অসমীয়া"
+      - option "বাংলা"
+      - option "ਪੰਜਾਬੀ"
+      - option "ગુજરાતી"
+      - option "ଓଡ଼ିଆ"
+      - option "தமிழ்"
+      - option "తెలుగు"
+      - option "ಕನ್ನಡ"
+      - option "മലയാളം"
+      - option "සිංහල"
+      - option "ไทย"
+      - option "ລາວ"
+      - option "မြန်မာ"
+      - option "ខ្មែរ"
+      - option "한국어"
+      - option "中文（香港）"
+      - option "日本語"
+      - option "简体中文"
+      - option "繁體中文"
+    - list [ref=e40]:
+      - listitem [ref=e41]:
+        - link "Help" [ref=e42] [cursor=pointer]:
+          - /url: https://support.google.com/accounts?hl=en-US&p=account_iph
+      - listitem [ref=e43]:
+        - link "Privacy" [ref=e44] [cursor=pointer]:
+          - /url: https://accounts.google.com/TOS?loc=LV&hl=en-US&privacy=true
+      - listitem [ref=e45]:
+        - link "Terms" [ref=e46] [cursor=pointer]:
+          - /url: https://accounts.google.com/TOS?loc=LV&hl=en-US

.playwright-mcp/page-2026-04-14T14-12-07-158Z.yml

@@ -0,0 +1,16 @@
+- main [ref=e2]:
+  - generic [ref=e3]:
+    - heading "oO" [level=1] [ref=e4]
+    - paragraph [ref=e5]: one tip. right now.
+  - link "Continue with Google" [ref=e7] [cursor=pointer]:
+    - /url: /api/auth/login?redirectTo=/connect
+    - img [ref=e8]
+    - text: Continue with Google
+  - paragraph [ref=e13]:
+    - text: By continuing you agree to our
+    - link "Terms" [ref=e14] [cursor=pointer]:
+      - /url: /legal/terms
+    - text: and
+    - link "Privacy Policy" [ref=e15] [cursor=pointer]:
+      - /url: /legal/privacy
+    - text: .

.playwright-mcp/page-2026-04-14T14-12-17-872Z.yml

@@ -0,0 +1,2 @@
+- main [ref=e2] [cursor=pointer]:
+  - generic [ref=e3]: ···

.playwright-mcp/page-2026-04-14T14-14-53-788Z.yml

@@ -0,0 +1,16 @@
+- main [ref=e2]:
+  - generic [ref=e3]:
+    - heading "oO" [level=1] [ref=e4]
+    - paragraph [ref=e5]: one tip. right now.
+  - link "Continue with Google" [ref=e7] [cursor=pointer]:
+    - /url: /api/auth/login?redirectTo=/connect
+    - img [ref=e8]
+    - text: Continue with Google
+  - paragraph [ref=e13]:
+    - text: By continuing you agree to our
+    - link "Terms" [ref=e14] [cursor=pointer]:
+      - /url: /legal/terms
+    - text: and
+    - link "Privacy Policy" [ref=e15] [cursor=pointer]:
+      - /url: /legal/privacy
+    - text: .

.playwright-mcp/page-2026-04-14T14-26-57-754Z.yml

@@ -0,0 +1,119 @@
+- generic [ref=e3]:
+  - generic [ref=e5]:
+    - generic [ref=e8]:
+      - img "Google" [ref=e10]
+      - generic [ref=e11]: Sign in with Google
+    - generic [ref=e12]:
+      - generic [ref=e14]:
+        - heading "Sign in" [level=1] [ref=e15]
+        - paragraph [ref=e16]:
+          - text: to continue to
+          - button "alogins.net" [ref=e17] [cursor=pointer]
+      - generic [ref=e18]:
+        - generic [ref=e21]:
+          - generic [ref=e26]:
+            - textbox "Email or phone" [active] [ref=e27]
+            - generic:
+              - generic: Email or phone
+          - paragraph [ref=e28]:
+            - link "Forgot email?" [ref=e29] [cursor=pointer]:
+              - /url: /signin/v2/usernamerecovery?app_domain=https://o.alogins.net&client_id=225787180325-cesuikl95j1qg3aijh4j10n8n7usf65p.apps.googleusercontent.com&code_challenge=-BqTqiuiRm7bqR18AN6dGJza3m1LQ-rUHm5iCKVp4L0&code_challenge_method=S256&continue=https://accounts.google.com/signin/oauth/legacy/consent?authuser%3Dunknown%26part%3DAJi8hAMZa_8Uw5oeDBf5xu6LwYAzWw0IfUPVe1s-RdkhKrryVpbj5DP1e4mWD5shlmUM9MHWJjmo0221X4Itv9m_QVhq6U9AE3ixMmFjYikcxLUbYpSC0ZK2Gpk6iXyS0bmfDCxbgrB-XxcJUfHUxxHIFAIPwGNH1HXRh9xm5nfY7qXSpWvjqH2SjPsvABBxBfb4_gYQVYDpFH6xY9tvo9ivQm607DUHzOGvM91l2PAzDK2xfzP1ly9SqBaA342VjnFJmEA5mKtYKfGXiThy7J62jQMM-NK8pjUTysf6PXNOLLyUCtl7VjQPs23EBAwe_22hjTKkVo9DRb9dlv8VNmIdVK-BVUoalJmfsRs3BVet5yibkeKV20QKQlCDgtPLCorYZyu3gnFh5taleK1WBbKLyRtscF3rVnhCkIp4Y4y3m8nHtTr_lKRi0jyIfZA9CJwxJnFJa50DFwjmiOYWosdQsuu6HCZ5CfNfCorlKIYB3zjmMRcFHdwYxPvydfXXR6OPui9JQfcE4KEjnE4sDQbB6B70TD9R-o7lqt5V9Qh0cOWwKpO0-m167gCqNjS67_qgdM4UK0vGResYyPoAGae9OtyQmCAj_dcU-62wi6Keit4fc9kh4tW_Sg3z-_uWIv3YDam93LJE%26flowName%3DGeneralOAuthFlow%26as%3DS-1308179881%253A1776176817375272%26client_id%3D225787180325-cesuikl95j1qg3aijh4j10n8n7usf65p.apps.googleusercontent.com%23&dsh=S-1308179881:1776176817375272&flowName=GeneralOAuthLite&o2v=2&opparams=%253F&rart=ANgoxceTKJUOKU3v1dqvsh5ic8iCtLsW59TMJ-d2ocODSbnDkgr7QsEsYbgBLhyzyxlCKvCeKxeWXE4oh50Ic8Zii472KjuAo007j0Fg5aey109I_iJ5RME&redirect_uri=https://o.alogins.net/api/auth/callback&response_type=code&scope=openid+email+profile&service=lso&state=8jVx7mQ1bRb8HljdpHf35
+        - generic [ref=e31]:
+          - button "Next" [ref=e33]
+          - link "Create account" [ref=e35] [cursor=pointer]:
+            - /url: /lifecycle/flows/signup?app_domain=https://o.alogins.net&client_id=225787180325-cesuikl95j1qg3aijh4j10n8n7usf65p.apps.googleusercontent.com&code_challenge=-BqTqiuiRm7bqR18AN6dGJza3m1LQ-rUHm5iCKVp4L0&code_challenge_method=S256&continue=https://accounts.google.com/signin/oauth/legacy/consent?authuser%3Dunknown%26part%3DAJi8hAMZa_8Uw5oeDBf5xu6LwYAzWw0IfUPVe1s-RdkhKrryVpbj5DP1e4mWD5shlmUM9MHWJjmo0221X4Itv9m_QVhq6U9AE3ixMmFjYikcxLUbYpSC0ZK2Gpk6iXyS0bmfDCxbgrB-XxcJUfHUxxHIFAIPwGNH1HXRh9xm5nfY7qXSpWvjqH2SjPsvABBxBfb4_gYQVYDpFH6xY9tvo9ivQm607DUHzOGvM91l2PAzDK2xfzP1ly9SqBaA342VjnFJmEA5mKtYKfGXiThy7J62jQMM-NK8pjUTysf6PXNOLLyUCtl7VjQPs23EBAwe_22hjTKkVo9DRb9dlv8VNmIdVK-BVUoalJmfsRs3BVet5yibkeKV20QKQlCDgtPLCorYZyu3gnFh5taleK1WBbKLyRtscF3rVnhCkIp4Y4y3m8nHtTr_lKRi0jyIfZA9CJwxJnFJa50DFwjmiOYWosdQsuu6HCZ5CfNfCorlKIYB3zjmMRcFHdwYxPvydfXXR6OPui9JQfcE4KEjnE4sDQbB6B70TD9R-o7lqt5V9Qh0cOWwKpO0-m167gCqNjS67_qgdM4UK0vGResYyPoAGae9OtyQmCAj_dcU-62wi6Keit4fc9kh4tW_Sg3z-_uWIv3YDam93LJE%26flowName%3DGeneralOAuthFlow%26as%3DS-1308179881%253A1776176817375272%26client_id%3D225787180325-cesuikl95j1qg3aijh4j10n8n7usf65p.apps.googleusercontent.com%23&dsh=S-1308179881:1776176817375272&flowEntry=SignUp&flowName=GlifWebSignIn&o2v=2&opparams=%253F&rart=ANgoxceTKJUOKU3v1dqvsh5ic8iCtLsW59TMJ-d2ocODSbnDkgr7QsEsYbgBLhyzyxlCKvCeKxeWXE4oh50Ic8Zii472KjuAo007j0Fg5aey109I_iJ5RME&redirect_uri=https://o.alogins.net/api/auth/callback&response_type=code&scope=openid+email+profile&service=lso&signInUrl=https://accounts.google.com/signin/oauth?app_domain%3Dhttps://o.alogins.net%26client_id%3D225787180325-cesuikl95j1qg3aijh4j10n8n7usf65p.apps.googleusercontent.com%26code_challenge%3D-BqTqiuiRm7bqR18AN6dGJza3m1LQ-rUHm5iCKVp4L0%26code_challenge_method%3DS256%26continue%3Dhttps://accounts.google.com/signin/oauth/legacy/consent?authuser%253Dunknown%2526part%253DAJi8hAMZa_8Uw5oeDBf5xu6LwYAzWw0IfUPVe1s-RdkhKrryVpbj5DP1e4mWD5shlmUM9MHWJjmo0221X4Itv9m_QVhq6U9AE3ixMmFjYikcxLUbYpSC0ZK2Gpk6iXyS0bmfDCxbgrB-XxcJUfHUxxHIFAIPwGNH1HXRh9xm5nfY7qXSpWvjqH2SjPsvABBxBfb4_gYQVYDpFH6xY9tvo9ivQm607DUHzOGvM91l2PAzDK2xfzP1ly9SqBaA342VjnFJmEA5mKtYKfGXiThy7J62jQMM-NK8pjUTysf6PXNOLLyUCtl7VjQPs23EBAwe_22hjTKkVo9DRb9dlv8VNmIdVK-BVUoalJmfsRs3BVet5yibkeKV20QKQlCDgtPLCorYZyu3gnFh5taleK1WBbKLyRtscF3rVnhCkIp4Y4y3m8nHtTr_lKRi0jyIfZA9CJwxJnFJa50DFwjmiOYWosdQsuu6HCZ5CfNfCorlKIYB3zjmMRcFHdwYxPvydfXXR6OPui9JQfcE4KEjnE4sDQbB6B70TD9R-o7lqt5V9Qh0cOWwKpO0-m167gCqNjS67_qgdM4UK0vGResYyPoAGae9OtyQmCAj_dcU-62wi6Keit4fc9kh4tW_Sg3z-_uWIv3YDam93LJE%2526flowName%253DGeneralOAuthFlow%2526as%253DS-1308179881%25253A1776176817375272%2526client_id%253D225787180325-cesuikl95j1qg3aijh4j10n8n7usf65p.apps.googleusercontent.com%2523%26dsh%3DS-1308179881:1776176817375272%26flowName%3DGeneralOAuthLite%26o2v%3D2%26opparams%3D%25253F%26rart%3DANgoxceTKJUOKU3v1dqvsh5ic8iCtLsW59TMJ-d2ocODSbnDkgr7QsEsYbgBLhyzyxlCKvCeKxeWXE4oh50Ic8Zii472KjuAo007j0Fg5aey109I_iJ5RME%26redirect_uri%3Dhttps://o.alogins.net/api/auth/callback%26response_type%3Dcode%26scope%3Dopenid%2Bemail%2Bprofile%26service%3Dlso%26state%3D8jVx7mQ1bRb8HljdpHf35&state=8jVx7mQ1bRb8HljdpHf35
+  - contentinfo [ref=e36]:
+    - combobox [ref=e39] [cursor=pointer]:
+      - option "Afrikaans"
+      - option "azərbaycan"
+      - option "bosanski"
+      - option "català"
+      - option "Čeština"
+      - option "Cymraeg"
+      - option "Dansk"
+      - option "Deutsch"
+      - option "eesti"
+      - option "English (United Kingdom)"
+      - option "English (United States)" [selected]
+      - option "Español (España)"
+      - option "Español (Latinoamérica)"
+      - option "euskara"
+      - option "Filipino"
+      - option "Français (Canada)"
+      - option "Français (France)"
+      - option "Gaeilge"
+      - option "galego"
+      - option "Hrvatski"
+      - option "Indonesia"
+      - option "isiZulu"
+      - option "íslenska"
+      - option "Italiano"
+      - option "Kiswahili"
+      - option "latviešu"
+      - option "lietuvių"
+      - option "magyar"
+      - option "Melayu"
+      - option "Nederlands"
+      - option "norsk"
+      - option "o‘zbek"
+      - option "polski"
+      - option "Português (Brasil)"
+      - option "Português (Portugal)"
+      - option "română"
+      - option "shqip"
+      - option "Slovenčina"
+      - option "slovenščina"
+      - option "srpski (latinica)"
+      - option "Suomi"
+      - option "Svenska"
+      - option "Tiếng Việt"
+      - option "Türkçe"
+      - option "Ελληνικά"
+      - option "беларуская"
+      - option "български"
+      - option "кыргызча"
+      - option "қазақ тілі"
+      - option "македонски"
+      - option "монгол"
+      - option "Русский"
+      - option "српски (ћирилица)"
+      - option "Українська"
+      - option "ქართული"
+      - option "հայերեն"
+      - option "‫עברית‬‎"
+      - option "‫اردو‬‎"
+      - option "‫العربية‬‎"
+      - option "‫فارسی‬‎"
+      - option "አማርኛ"
+      - option "नेपाली"
+      - option "मराठी"
+      - option "हिन्दी"
+      - option "অসমীয়া"
+      - option "বাংলা"
+      - option "ਪੰਜਾਬੀ"
+      - option "ગુજરાતી"
+      - option "ଓଡ଼ିଆ"
+      - option "தமிழ்"
+      - option "తెలుగు"
+      - option "ಕನ್ನಡ"
+      - option "മലയാളം"
+      - option "සිංහල"
+      - option "ไทย"
+      - option "ລາວ"
+      - option "မြန်မာ"
+      - option "ខ្មែរ"
+      - option "한국어"
+      - option "中文（香港）"
+      - option "日本語"
+      - option "简体中文"
+      - option "繁體中文"
+    - list [ref=e40]:
+      - listitem [ref=e41]:
+        - link "Help" [ref=e42] [cursor=pointer]:
+          - /url: https://support.google.com/accounts?hl=en-US&p=account_iph
+      - listitem [ref=e43]:
+        - link "Privacy" [ref=e44] [cursor=pointer]:
+          - /url: https://accounts.google.com/TOS?loc=LV&hl=en-US&privacy=true
+      - listitem [ref=e45]:
+        - link "Terms" [ref=e46] [cursor=pointer]:
+          - /url: https://accounts.google.com/TOS?loc=LV&hl=en-US

.playwright-mcp/page-2026-04-15T07-41-23-867Z.yml

@@ -0,0 +1,16 @@
+- main [ref=e2]:
+  - generic [ref=e3]:
+    - heading "oO" [level=1] [ref=e4]
+    - paragraph [ref=e5]: one tip. right now.
+  - link "Continue with Google" [ref=e7] [cursor=pointer]:
+    - /url: /api/auth/login?redirectTo=/connect
+    - img [ref=e8]
+    - text: Continue with Google
+  - paragraph [ref=e13]:
+    - text: By continuing you agree to our
+    - link "Terms" [ref=e14] [cursor=pointer]:
+      - /url: /legal/terms
+    - text: and
+    - link "Privacy Policy" [ref=e15] [cursor=pointer]:
+      - /url: /legal/privacy
+    - text: .

.playwright-mcp/page-2026-04-15T08-09-40-643Z.yml

@@ -0,0 +1,16 @@
+- main [ref=e2]:
+  - generic [ref=e3]:
+    - heading "oO" [level=1] [ref=e4]
+    - paragraph [ref=e5]: one tip. right now.
+  - link "Continue with Google" [ref=e7] [cursor=pointer]:
+    - /url: /api/auth/login?redirectTo=/connect
+    - img [ref=e8]
+    - text: Continue with Google
+  - paragraph [ref=e13]:
+    - text: By continuing you agree to our
+    - link "Terms" [ref=e14] [cursor=pointer]:
+      - /url: /legal/terms
+    - text: and
+    - link "Privacy Policy" [ref=e15] [cursor=pointer]:
+      - /url: /legal/privacy
+    - text: .

CLAUDE.md

@@ -56,7 +56,7 @@ docs/              architecture notes, ADRs, API specs
 ## Contracts between modules
 
 - **HTTP** (OpenAPI, in `packages/shared-types/http/`) — synchronous request/response. In-process today; over the network once extracted. Signatures are identical.
-- **Events** (Protocol Buffers, in `packages/shared-types/events/`) — durable signals + feedback. Today: in-process event emitter. Tomorrow: NATS JetStream. Schema registry enforced in CI (ADR-0005).
+- **Events** (Protocol Buffers, in `packages/shared-types/events/`) — durable signals + feedback. Today: in-process `Bus` with a `onPublish` bridge to NATS JetStream when `NATS_URL` is set (ADR-0010). The in-proc bus stays the source of truth — JetStream is the durable mirror that cross-process consumers (`ml/serving`, future feature pipelines) tail. Schema registry enforced in CI when #54 lands; until then payloads are JSON envelopes (ADR-0005).
 - Do not redefine types per module. Regenerate from `shared-types`.
 
 ## Conventions
@@ -65,7 +65,7 @@ docs/              architecture notes, ADRs, API specs
 - One PR = one concern. Conventional-commit prefixes (`feat:`, `fix:`, `chore:`, `docs:`, `refactor:`).
 - ADRs go in `docs/adr/NNNN-title.md` for any decision that constrains future work.
 - No secrets in repo. Local dev via `.env.local` (gitignored), prod via the server's secret store (Vaultwarden now; k8s secrets later).
-- Compose profiles (`core`, `full`) so devs can run a subset without 16 GB of RAM.
+- Compose profiles: `core` (api + web + admin), `full` (adds ml-serving), `mlops` (adds MLflow + Airflow), `ai` (adds Ollama + LiteLLM). Mix as needed.
 
 ## Definition of done (per feature)
 
@@ -76,15 +76,39 @@ docs/              architecture notes, ADRs, API specs
 5. Deployable via `docker compose up` locally.
 6. If it touches user data → a deletion path exists and is tested.
 
+## AI stack
+
+oO generates tips with an LLM and ranks them with a bandit. All LLM calls route through **LiteLLM** at `llm.alogins.net` using model aliases — swapping models is a config change, not a code change.
+
+| Alias | Model | Used by |
+|-------|-------|---------|
+| `tip-generator` | qwen2.5:1.5b (default) | `ml/serving` tip generation |
+| `embedder` | nomic-embed-text | task clustering, dedup |
+| `judge` | claude-haiku-4-5 (cloud, eval only) | offline sim |
+
+Env vars: `LITELLM_URL` (prod `https://llm.alogins.net`), `OLLAMA_URL` (Agap host, `http://host.docker.internal:11434` from containers).
+
+Ollama and LiteLLM are **shared Agap services**, not oO services — they live in `agap_git/openai/docker-compose.yml` along with langfuse (observability). oO never starts them; ml-serving just calls the alias.
+
+**LLM tip generation pipeline:**
+1. `ml/features/context.py` assembles user signals → structured prompt context
+2. `POST /generate` in `ml/serving` calls LiteLLM → returns `TipCandidate[]`
+3. Bandit policy in `ml/serving` scores + ranks candidates
+4. Best candidate returned as tip; reaction closes the online reward loop
+
 ## Current phase
 
-**Phase 0 — Prototype.** See `README.md` for the phase roadmap and `docs/architecture/` for diagrams. Work is tracked as Gitea milestones + issues on `alvis/oO`.
+**M1 shipped. M2 (AI tips) in progress.** See `README.md` for the phase roadmap and `docs/architecture/` for diagrams. Work is tracked as Gitea milestones + issues on `alvis/oO`.
+
+Active work: AI tip generation pipeline — issues #86–#93 in M2 milestone.
 
 ## What NOT to do
 
 - Don't copy Todoist's data into our DB. Store the OAuth token + computed features/derivatives we need, fetch raw on demand.
-- Don't implement auth by hand. Phase 0 uses **Auth.js** behind an OIDC-shaped boundary (ADR-0004); swap to a dedicated OIDC provider only when mobile ships.
-- Don't hardwire a recommender. The "random todo" v0 must live behind the same interface the real ML model will implement (`POST /recommend` → `{tip}`). Swap internals, keep contract.
+- Don't implement auth by hand. Auth.js behind an OIDC-shaped boundary (ADR-0004); swap to a dedicated OIDC provider only when mobile ships.
+- Don't hardwire a recommender. The contract is `POST /recommend → {tip}`. Swap internals (bandit, LLM, hybrid), keep contract.
 - Don't replace a policy in one step. New policies deploy shadow-first; promoted only after offline + online agreement with the incumbent (ADR-0002).
-- Don't build an admin UI before the user-facing black page is polished.
 - Don't over-split processes. Extract a service when pressure demands it, not in anticipation (ADR-0003).
+- Don't call LLMs directly from application code. All LLM calls go through `ml/serving` (Python) via `LITELLM_URL`. The TS recommender never holds a model name.
+- Don't embed MLflow/Airflow/OpenWebUI in the admin panel. They are external services; link out to them. The admin shell links to `o.alogins.net/mlflow`, `/airflow`, `ai.alogins.net`.
+- Don't `nats.publish()` directly from feature code. All publishes go through the in-process `Bus` (`services/api/src/events/bus.ts`); the NATS adapter (`events/nats.ts`) bridges every publish to JetStream when `NATS_URL` is set. This keeps subscribers, the ring-buffer tail used by the admin event viewer, and JetStream all in lockstep.

README.md

@@ -67,55 +67,192 @@ docs/        architecture, adr, api
 
 ---
 
+## AI stack
+
+oO is AI-native: the recommender's job is to **rank**, not to write. An LLM generates candidate tips from the user's context; the bandit picks the best one.
+
+### Three-tier layout
+
+| Tier | Service | Purpose | Where |
+|------|---------|---------|-------|
+| Inference | **Ollama** | Local LLM + embedding; no data leaves the host | `localhost:11434` |
+| Routing | **LiteLLM** | Unified OpenAI-compatible API; model aliases; cloud fallback | `llm.alogins.net` (Agap shared) |
+| Testing | **OpenWebUI** | Prompt iteration, model comparison, manual evals | `ai.alogins.net` (Agap shared) |
+
+### Tip generation pipeline (Phase 2 target)
+
+```
+User signals  ──▶  Context assembler  ──▶  LiteLLM  ──▶  Ollama (local)
+(tasks, calendar,    (ml/features/)         (routing)     or cloud fallback
+ patterns, time)
+                                                ▼
+                                     N typed TipCandidates
+                                     {content, kind, model,
+                                      prompt_version, confidence}
+                                                ▼
+                                    Bandit policy (ml/serving)
+                                    scores + ranks candidates
+                                                ▼
+                                         Best tip shown
+                                                ▼
+                              User reaction (done / snooze / dismiss + dwell)
+                                                ▼
+                              Online bandit update + prompt_version tracking
+```
+
+**Why LiteLLM as gateway:**  All LLM calls use a single `LITELLM_URL` env var. Swapping from qwen2.5 to llama3.2, or routing a fraction to Claude for A/B, is a config change in LiteLLM — zero code change in oO. The model name in `tip_scores` tells you exactly which model produced each tip.
+
+**Why Ollama first:**  Tips contain personal context. Local inference means no user data leaves the host for the inference path. Cloud models (Anthropic, OpenAI) are opt-in fallbacks for evaluation and simulation only, gated behind `ANTHROPIC_API_KEY`.
+
+### Models (planned)
+
+| Alias | Model | Task |
+|-------|-------|------|
+| `tip-generator` | qwen2.5:7b (default) | Generate typed tip candidates from user context |
+| `embedder` | nomic-embed-text | Task clustering, semantic similarity for dedup |
+| `judge` | claude-haiku-4-5 (cloud, eval-only) | Offline sim judge; rates tip quality for A/B |
+
+---
+
 ## Roadmap
 
-### Phase 0 — Walking skeleton  *(M0)*
+### Phase 0 — Walking skeleton  *(M0)* ✓ shipped
 Goal: a single user signs in with Google, connects Todoist, and sees one random Todoist task on a black page. Deletion works.
-- [ ] Monorepo scaffold, CI skeleton, docker-compose dev env with `core`/`full` profiles
-- [ ] `auth` on Auth.js with Google provider; OIDC-shaped boundary (ADR-0004)
-- [ ] `integrations/todoist` OAuth2 flow + encrypted token vault + provider-side revocation
-- [ ] `recommender` with `RandomPolicy`; stable `POST /recommend` contract
-- [ ] `apps/web` — three pages (sign-in, connect, tip); PWA manifest; offline reaction queue
-- [ ] ToS + Privacy Policy + consent capture on first sign-in
-- [ ] Account-deletion endpoint: revokes providers, purges credentials, soft-deletes profile
-- [ ] Metrics baseline: activation, first-tip reaction rate, dwell, retention (see `docs/architecture/metrics.md`)
-- [ ] Deploy modular monolith + `ml/serving` stub to a single VM via docker-compose + Caddy
+- [x] Monorepo scaffold, docker-compose dev env
+- [x] `auth` — Google OAuth2/PKCE via openid-client v6; session cookie; Next.js middleware guard
+- [x] `integrations/todoist` — OAuth2 flow, token stored in DB, disconnect supported
+- [x] `recommender` with `RandomPolicy`; stable `POST /recommend` contract; 30s task cache
+- [x] `apps/web` — sign-in, connect, tip pages; PWA manifest + icons
+- [x] Feedback: `done / snooze / dismiss`; reward inferred from dwell-time (`inferReward`); marks task complete in Todoist
+- [x] Deploy modular monolith to Agap VM via Caddy at `o.alogins.net`
+- [x] ToS + Privacy Policy pages (`/legal/terms`, `/legal/privacy`); implicit consent on sign-in
+- [x] Account deletion: revokes tokens, purges data, soft-deletes profile; button on /connect
+- [x] Metrics baseline: `tip_views` table (tip served) + `tip_feedback` (reactions) — activation + reaction rate queryable
 
-### Phase 1 — Real signal + in-the-moment delivery  *(M1)*
+### Phase 1 — Real signal + in-the-moment delivery  *(M1)* ✓ shipped
 Goal: tips are picked, not drawn from a hat — and they arrive at the right moment on the web.
-- [ ] Event bus (NATS JetStream) with protobuf schemas (ADR-0005) + schema-registry CI gate
-- [ ] Todoist event-driven sync (emit `signals.task.*`)
-- [ ] Feature store skeleton + first five features (hour-of-day, overdue count, task age, priority, project)
-- [ ] `ml/serving` FastAPI scorer; `RemotePolicy` wrapper in recommender
-- [ ] **Global-then-personalize bandit**: pooled LinUCB over shared features, per-user residual when data allows
-- [ ] Shadow-deploy infra: every new policy logs what it *would* have picked; promotion requires reward-parity
-- [ ] Feedback loop: reactions → rewards; delayed rewards for tasks completed in Todoist directly
-- [ ] **Web Push notifications** (VAPID) so the "magic" shows up without opening the app
-- [ ] `notifier` (lite): web-push delivery, quiet-hours honoured, dedupe
-- [ ] Apple OAuth added (deferred from M0)
+- [x] Event bus scaffold: typed in-process EventEmitter with 500-event ring buffer; subjects match future NATS JetStream — swap is mechanical
+- [x] Todoist sync emits `signals.task.synced`; tip served/feedback emit `signals.tip.*`
+- [x] Features extracted per task: `is_overdue`, `task_age_days`, `priority`; context: `hour_of_day`, `day_of_week`
+- [x] `ml/serving` LinUCB (d=5) + **ε-greedy v1** (d=7, ε=0.10, day-of-week sin/cos features); per-user state persisted to disk
+- [x] `RemotePolicy` in recommender: calls ml/serving, falls back to RandomPolicy on timeout/error; logs explainability to `tip_scores`
+- [x] Feedback loop: dwell-time inferred reward (`inferReward`) → online model update; `done` in 15 s–2 min = +1.0 (magic zone)
+- [x] Offline simulation framework (`ml/experiments/sim`): rule/LLM/claude-code judges, two-policy comparison, results persisted to `sim_runs` + `sim_events`
+- [x] **ε-greedy v1 promoted to active policy** (ADR-0007) — +10.7% mean reward vs LinUCB in offline sim
+- [x] **Web Push** (VAPID): SW, subscribe/unsubscribe API, "notify me" button on tip page
+- [x] Shadow-policy registry: run N shadow policies per request, log picks without serving them (#56)
+- [ ] Quiet-hours + dedupe for push delivery
+- [ ] Delayed rewards: tasks completed directly in Todoist (requires webhook from Todoist)
+- [x] NATS JetStream bridge — durable `signals.>` and `feedback.>` streams; in-process bus stays the source of truth, every publish bridges out (#21, shipped)
 
-### Phase 2 — Multi-source profile & trust  *(M2)*
-Goal: oO knows more than tasks, and users can see/control what we know.
-- [ ] Integrations: Google Calendar, Apple Health (web import), generic webhook ingress
-- [ ] Unified `Profile` model (identity, preferences, contexts, consents)
-- [ ] Timing signals (Page Visibility, Idle Detection, coarse location) — opt-in, transparent
-- [ ] Advice library + mixing policy (todo vs advice vs ambient)
-- [ ] User-facing data dashboard: what's stored, what's computed, export, delete-by-category
-- [ ] Cost/usage observability
+#### M1 add-on — Admin & ML Ops Console  *(fully shipped)*
+
+oO is ML-heavy. Without a cockpit, every model change ships blind. This console is the team's single pane for users, signals, features, models, experiments, and tip outcomes — with the ability to *act* on them (revoke a token, replay an event, promote a model, reset a bandit).
+
+**Framework pick — `apps/admin` on Next.js 15 + Tremor + shadcn/ui.**  Analytics-first UI for an analytics-first product, stays on our existing TS/React/Tailwind stack, reuses `packages/shared-types`, `sdk-js`, and the Auth.js session. Specialized ML tooling (MLflow, Airflow) runs as **separate external services** linked from the admin shell; Grafana panels are embedded.
+
+| Layer | Tool | Why |
+|-------|------|-----|
+| App shell | **Next.js 15** (new `apps/admin`) | Same stack as `apps/web`; reuses auth, types, SDK |
+| Dashboards / charts | **[Tremor](https://tremor.so)** | Analytics-first React + Tailwind — KPI cards, time-series, categorical, heatmaps |
+| CRUD primitives | **[shadcn/ui](https://ui.shadcn.com)** | Copy-paste Radix components; forms, dialogs, command palette |
+| Heavy grids | **[TanStack Table v8](https://tanstack.com/table)** | Sortable / paginated / virtualized tables (events, users, tips) |
+| Extra charts | **[Recharts](https://recharts.org)** / **[visx](https://airbnb.io/visx)** | Fallbacks where Tremor falls short (e.g. force graphs, Sankey) |
+| Model registry / experiments | **[MLflow](https://mlflow.org)** *(external — `o.alogins.net/mlflow`)* | Experiment tracking, artifact browser, model registry; own basic-auth |
+| Pipeline orchestration | **[Airflow](https://airflow.apache.org)** *(external — `o.alogins.net/airflow`)* | Batch feature + retraining DAGs; own web-auth |
+| Infra metrics | **[Grafana](https://grafana.com)** *(embedded panels)* | One ops source of truth |
+| Ad-hoc analysis | **[Marimo](https://marimo.io)** reactive notebooks | Python-native for the ML side; launch-out link |
+| AuthZ | `profile.role='admin'` + Next.js middleware | Reuses existing session; no new auth surface |
+
+**Rejected alternatives (so we don't re-litigate):**
+- *Retool / AppSmith* — low-code speed, but admin logic leaves our repo; weak analytics affordances for an analytics product
+- *Streamlit / Gradio / Dash* — Python-first; thin RBAC and routing; splits our frontend stack in two
+- *React-admin / Refine.dev* — strong CRUD scaffolding, but analytics/ML views feel bolted on; we'd rebuild Tremor-style dashboards ourselves
+- *Superset / Metabase as the admin surface* — excellent for BI, poor for operational **writes** (revoke, replay, promote). Plan: **adopt Superset in M4** for BI alongside batch pipelines; ship a read-only SQL widget inside admin for now
+
+**Build sequence (plan, not code):**
+1. [x] **ADR-0006** — record the framework choice + "embed, don't rebuild" rule for MLflow/Grafana
+2. [x] **Scaffold** — `apps/admin` with Next.js 15, Tailwind, Tremor; deploy behind Caddy at `admin.o.alogins.net`
+3. [x] **RBAC** — `role` column on `users`; admin-only Next.js middleware; seed first admin via `ADMIN_SEED_EMAIL` env; `admin_actions` audit-log table
+4. [x] **Overview dashboard** — DAU/WAU KPI cards, tips served, reaction breakdown, activation funnel
+5. [x] **User explorer** — list + detail page: identity, consents, integrations, last tip, reward history; revoke-integration + reset-bandit actions
+6. [x] **Event stream viewer** — live tail of `signals.*` with filters by subject/user/time; same UI when the bus swaps to NATS
+7. [x] **Feature store browser** — features sent to `ml/serving` per scoring call; diff across time for a user
+8. [x] **Model registry panel** — `/admin/models` links out to MLflow (`mlflow.o.alogins.net`); experiment tracking and dataset management in MLflow + Airflow
+9. [x] **MLOps hub** — `/admin/experiments` links to MLflow experiments/models and Airflow DAGs/datasets; bandit reset on Users page
+10. [x] **Recommendation log (explainability)** — per served tip: `(user, features, policy, score, feedback, latency)`; `tip_scores` table, 30-day retention
+11. [x] **Reward analytics** — reaction distribution over time; per-policy compare; slice by `hour_of_day`, `priority`, cohort
+12. [x] **Data quality widget** — missing-feature rate, stale-token rate, daily completeness heatmap
+13. [x] **Ops actions** — revoke token (Users page), replay signal, disable/promote shadow policy; every action audit-logged
+14. [x] **Read-only SQL runner** — SELECT-only runner against SQLite + saved queries (sunsets to Superset in M4)
+15. [x] **Health rollup** — `/admin/health` surfaces api, ml/serving, SQLite, event-bus; auto-refreshes every 15s
+16. [ ] **Docs** — `apps/admin/README.md`, runbook for common ops actions, ADR-0006 merged
+
+- [ ] Apple OAuth (deferred to M2)
+
+### Phase 2 — AI tips + multi-source signals  *(M2)*
+Goal: tips are AI-generated from user context, not just raw Todoist tasks. Multiple signal sources feed a generalized pipeline. Research-intensive milestone.
+
+**AI infrastructure (unblock everything else):**
+- [ ] `ai` compose profile — Ollama + LiteLLM for local dev; env vars `OLLAMA_URL` / `LITELLM_URL` (#86)
+- [ ] AI gateway — wire `ml/serving` to LiteLLM; model aliases `tip-generator` + `embedder` (#87)
+
+**AI tip generation pipeline:**
+- [ ] Context assembler — user signals + feature store → structured prompt context (`ml/features/context.py`) (#88)
+- [ ] Tip generator endpoint — `POST /generate` in `ml/serving`; LLM → N typed `TipCandidate` objects (#79)
+- [ ] `TipCandidate` shared schema — `{content, kind, source, model, prompt_version, confidence}`; update recommender pipeline (#89)
+- [ ] LLM output validation + retry — JSON schema gate, clarification retry (2×), fallback to task-based (#90)
+- [ ] Prompt versioning — `prompt_version` + `model` columns in `tip_scores`; content-hash invalidation (#91)
+- [ ] LLM tip quality dashboard — reaction breakdown by model / prompt_version in `/admin/reward-analytics` (#92)
+
+**Evaluation & model selection:**
+- [ ] Model benchmark — compare qwen2.5:7b / llama3.2:3b / gemma3:4b via offline sim + LLM judge (#93)
+- [ ] LLM prompt research — persona design, context injection strategies, few-shot examples (#84)
+
+**Pipeline architecture:**
+- [ ] Signal source abstraction — `SignalSource` interface generalizing beyond Todoist (#78)
+- [ ] Generalized recommendation pipeline — candidate → rank → render stages (#80)
+- [ ] Feature registry + user profile builder — centralized features, persistent profiles (#81)
+- [ ] Tip kind system — task, advice, insight, reminder with kind-aware UI + rewards (#82)
+
+**Policy research:**
+- [ ] Next-gen policies — Thompson sampling, neural bandits, hybrid transfer learning (#83)
+
+**Integrations & infra (carried from M1):**
+- [ ] Apple OAuth (#7)
+- [x] NATS JetStream replacing in-process bus (#21) — adapter ships in `services/api/src/events/nats.ts`; in-proc bus is the producer, JetStream is the durable mirror
+- [x] Todoist sync via events (#22) — background scheduler in `services/api/src/signals/scheduler.ts` emits `signals.task.synced` every `TODOIST_SYNC_INTERVAL_MS`; on-demand fetch remains as freshness fallback
+- [ ] Event schema registry + protobuf CI gate (#54)
+- [ ] Per-user freshness SLAs for features (#61)
+- [ ] CI skeleton (#3), observability (#18), E2E tests (#20)
+
+**Bugs (fix before new features):**
+- [ ] TipFeedback type mismatch (#73)
+- [ ] Todoist token refresh (#74)
+- [ ] Reward fire-and-forget (#75)
+- [ ] Data retention purge (#76)
+- [ ] Port mismatch (#77)
 
 ### Phase 3 — Native mobile  *(M3)*
 - [ ] iOS app (SwiftUI) with APNs push
 - [ ] Android app (Compose) with FCM push
 - [ ] `notifier` gains APNs + FCM channels, per-device rate limits
 - [ ] Migrate auth from Auth.js to dedicated OIDC provider (trigger from ADR-0004)
+- [ ] Consolidate MLflow + Airflow behind shared OIDC (SSO for all internal services)
 - [ ] Decide-and-deliver scheduler: per-user "is this tip worth interrupting now?" threshold
 
 ### Phase 4 — MLOps at scale  *(M4)*
-- [ ] Prefect/Airflow for batch feature materialization + retraining
-- [ ] MLflow registry; shadow → A/B → launch pipeline as first-class
+- [x] Airflow + MLflow deployed as external services (`mlops` compose profile); each with own auth
+- [ ] Write first retraining DAG (Airflow) + first MLflow experiment logging from `ml/serving`
+- [ ] Feature-to-prompt pipeline — nightly Airflow DAG materializes context for LLM; cuts inline latency (#94)
+- [ ] Prompt optimization loop — sim A/B → MLflow experiment → human-approved promotion (#95)
+- [ ] LLM fine-tuning — tip reactions as training signal; LoRA on base model; MLflow tracks runs (#96)
+- [ ] Embedding-based task clustering — `nomic-embed-text` for dedup + user pattern features (#97)
+- [ ] Consolidate MLflow + Airflow auth into shared OIDC provider (tracked as M3 issue #85)
+- [ ] Shadow → A/B → launch pipeline as first-class in MLflow
 - [ ] Online experiments framework: deterministic assignment + bandit policies alongside fixed-split A/B
 - [ ] Cross-user collaborative features (opt-in only); cohort slicing; fairness checks
-- [ ] Drift monitoring (feature drift, prediction drift, reward drift); model cards per version
+- [ ] Drift monitoring (feature + prediction + reward drift); model cards per LLM version
 
 ### Phase 5 — Production hardening  *(M5)*
 - [ ] Audit logging, rotation of provider tokens + internal signing keys

apps/admin/README.md

@@ -0,0 +1,37 @@
+# apps/admin — oO Admin Console
+
+Next.js 15 app. Deployed at `admin.o.alogins.net` (dev: `http://localhost:3080`).
+
+## Contract
+
+- All routes are admin-only. The Next.js middleware calls `GET /api/user/me` on every request
+  and checks `role === 'admin'`. First admin is seeded via `ADMIN_SEED_EMAIL` env var at API startup.
+- Admin write actions are appended to the `admin_actions` audit log in the DB.
+
+## Pages
+
+| Route | Description |
+|-------|-------------|
+| `/` | Overview: DAU/WAU KPI cards, tips served, reaction breakdown, activation funnel |
+| `/users` | User list (paginated) |
+| `/users/:id` | User detail: identity, consents, integrations, tip stats, reward history; revoke-integration + reset-bandit actions |
+| `/audit` | Admin action audit log |
+| `/events` | Event stream viewer (stub — pending API history endpoint) |
+
+## Dev
+
+```bash
+pnpm --filter @oo/admin dev   # starts on :3080
+# also run the API: pnpm --filter @oo/api dev  (port 3078)
+```
+
+## Extraction criteria
+
+Stays as a Next.js app in the monorepo permanently — it's not a candidate for extraction.
+It gets richer (more pages, embedded MLflow/Grafana) but not split.
+
+## Known issues
+
+- `@tremor/react 3.x` declares a peer dep on React 18; the workspace uses React 19.
+  Works in practice. Will resolve naturally when Tremor ships React 19 support or when
+  we switch to Tremor v4 (which targets React 18+).

apps/admin/next.config.ts

@@ -0,0 +1,18 @@
+import type { NextConfig } from 'next';
+import path from 'node:path';
+
+const nextConfig: NextConfig = {
+  output: 'standalone',
+  outputFileTracingRoot: path.join(__dirname, '../../'),
+  basePath: '/admin',
+  async rewrites() {
+    return [
+      {
+        source: '/api/:path*',
+        destination: `${process.env.NEXT_PUBLIC_API_URL ?? 'http://localhost:3078'}/api/:path*`,
+      },
+    ];
+  },
+};
+
+export default nextConfig;

apps/admin/package.json

@@ -0,0 +1,32 @@
+{
+  "name": "@oo/admin",
+  "version": "0.0.0",
+  "private": true,
+  "scripts": {
+    "dev": "next dev -p 3080",
+    "build": "next build",
+    "start": "next start -p 3080",
+    "lint": "next lint",
+    "type-check": "tsc --noEmit",
+    "clean": "rm -rf .next"
+  },
+  "dependencies": {
+    "@oo/shared-types": "workspace:*",
+    "@tremor/react": "^3.18.3",
+    "@tanstack/react-table": "^8.20.5",
+    "next": "^15.1.6",
+    "react": "^19.0.0",
+    "react-dom": "^19.0.0",
+    "recharts": "^2.15.3",
+    "marked": "^14.1.4"
+  },
+  "devDependencies": {
+    "@types/node": "^22.10.5",
+    "@types/react": "^19.0.0",
+    "@types/react-dom": "^19.0.0",
+    "tailwindcss": "^3.4.17",
+    "autoprefixer": "^10.4.20",
+    "postcss": "^8.5.1",
+    "typescript": "^5.7.3"
+  }
+}

apps/admin/postcss.config.js

@@ -0,0 +1,6 @@
+module.exports = {
+  plugins: {
+    tailwindcss: {},
+    autoprefixer: {},
+  },
+};

apps/admin/src/app/audit/page.tsx

@@ -0,0 +1,12 @@
+import { AdminShell } from '@/components/AdminShell';
+import { AuditLog } from '@/components/AuditLog';
+
+export const dynamic = 'force-dynamic';
+
+export default function AuditPage() {
+  return (
+    <AdminShell>
+      <AuditLog />
+    </AdminShell>
+  );
+}

apps/admin/src/app/data-quality/page.tsx

@@ -0,0 +1,89 @@
+'use client';
+
+import { useEffect, useState } from 'react';
+import { AdminShell } from '@/components/AdminShell';
+import { getDataQuality } from '@/lib/api';
+
+function Pct({ value }: { value: number }) {
+  const pct = (value * 100).toFixed(1);
+  const color = value < 0.05 ? 'text-green-400' : value < 0.2 ? 'text-yellow-400' : 'text-red-400';
+  return <span className={color}>{pct}%</span>;
+}
+
+export default function DataQualityPage() {
+  const [data, setData] = useState<Awaited<ReturnType<typeof getDataQuality>> | null>(null);
+  const [loading, setLoading] = useState(true);
+  const [error, setError] = useState('');
+
+  useEffect(() => {
+    getDataQuality()
+      .then(setData)
+      .catch((e) => setError(e.message))
+      .finally(() => setLoading(false));
+  }, []);
+
+  return (
+    <AdminShell>
+      <div className="space-y-6">
+        <h1 className="text-xl font-semibold">Data quality</h1>
+        {error && <p className="text-red-400 text-sm">{error}</p>}
+        {loading && <p className="text-gray-500 text-sm">Loading…</p>}
+
+        {data && (
+          <>
+            <div className="grid grid-cols-2 gap-4 md:grid-cols-4">
+              <div className="bg-gray-900 border border-gray-800 rounded p-4">
+                <div className="text-xs text-gray-500 mb-1">Scoring calls (30d)</div>
+                <div className="text-2xl font-semibold">{data.scoringCallsLast30d}</div>
+              </div>
+              <div className="bg-gray-900 border border-gray-800 rounded p-4">
+                <div className="text-xs text-gray-500 mb-1">Missing feature rate</div>
+                <div className="text-2xl font-semibold"><Pct value={data.missingFeatureRate} /></div>
+              </div>
+              <div className="bg-gray-900 border border-gray-800 rounded p-4">
+                <div className="text-xs text-gray-500 mb-1">Integration tokens</div>
+                <div className="text-2xl font-semibold">{data.totalTokens}</div>
+              </div>
+              <div className="bg-gray-900 border border-gray-800 rounded p-4">
+                <div className="text-xs text-gray-500 mb-1">Stale token rate (&gt;7d)</div>
+                <div className="text-2xl font-semibold"><Pct value={data.staleTokenRate} /></div>
+              </div>
+            </div>
+
+            <div className="space-y-2">
+              <h2 className="text-sm font-medium text-gray-400">Daily feature completeness (14d)</h2>
+              <table className="w-full text-xs">
+                <thead>
+                  <tr className="border-b border-gray-800 text-gray-500 text-left">
+                    <th className="py-2 pr-4">Date</th>
+                    <th className="py-2 pr-4">Scoring calls</th>
+                    <th className="py-2 pr-4">With features</th>
+                    <th className="py-2 pr-4">Coverage</th>
+                    <th className="py-2">Avg candidates</th>
+                  </tr>
+                </thead>
+                <tbody>
+                  {data.dailyQuality.map((row) => {
+                    const coverage = row.total > 0 ? row.withFeatures / row.total : 0;
+                    return (
+                      <tr key={row.date} className="border-b border-gray-800/50">
+                        <td className="py-1.5 pr-4 font-mono text-gray-500">{row.date}</td>
+                        <td className="py-1.5 pr-4 text-gray-300">{row.total}</td>
+                        <td className="py-1.5 pr-4 text-gray-300">{row.withFeatures}</td>
+                        <td className="py-1.5 pr-4"><Pct value={coverage} /></td>
+                        <td className="py-1.5 text-gray-300">{row.avgCandidates?.toFixed(1) ?? '—'}</td>
+                      </tr>
+                    );
+                  })}
+                  {data.dailyQuality.length === 0 && (
+                    <tr><td colSpan={5} className="py-4 text-center text-gray-600">No data yet</td></tr>
+                  )}
+                </tbody>
+              </table>
+            </div>
+          </>
+        )}
+      </div>
+    </AdminShell>
+  );
+}

apps/admin/src/app/docs/[category]/[slug]/page.tsx

@@ -0,0 +1,74 @@
+import { notFound } from 'next/navigation';
+import Link from 'next/link';
+import { AdminShell } from '@/components/AdminShell';
+import { getDoc, type DocCategory } from '@/lib/docs';
+
+export const dynamic = 'force-dynamic';
+
+const CATEGORY_LABELS: Record<DocCategory, string> = {
+  adr: 'ADR',
+  architecture: 'Architecture',
+};
+
+function isDocCategory(value: string): value is DocCategory {
+  return value === 'adr' || value === 'architecture';
+}
+
+export default async function DocDetailPage({
+  params,
+}: {
+  params: Promise<{ category: string; slug: string }>;
+}) {
+  const { category, slug } = await params;
+  if (!isDocCategory(category)) notFound();
+
+  const doc = await getDoc(category, slug);
+  if (!doc) notFound();
+
+  const categoryLabel = CATEGORY_LABELS[category];
+
+  return (
+    <AdminShell>
+      <div className="max-w-3xl space-y-6">
+        {/* Breadcrumb */}
+        <nav className="flex items-center gap-2 text-xs text-gray-500">
+          <Link href="/docs" className="hover:text-gray-300 transition-colors">
+            Docs
+          </Link>
+          <span>/</span>
+          <span className="text-gray-400">{categoryLabel}</span>
+          <span>/</span>
+          <span className="text-gray-300 truncate">{doc.slug}</span>
+        </nav>
+
+        {/* Meta bar */}
+        {(doc.status || doc.date) && (
+          <div className="flex items-center gap-3 text-xs text-gray-500">
+            {doc.status && (
+              <span
+                className={`px-1.5 py-0.5 rounded font-medium ${
+                  doc.status === 'Accepted'
+                    ? 'bg-emerald-900 text-emerald-300'
+                    : doc.status === 'Proposed'
+                      ? 'bg-yellow-900 text-yellow-300'
+                      : doc.status === 'Deprecated'
+                        ? 'bg-red-900 text-red-400'
+                        : 'bg-gray-800 text-gray-400'
+                }`}
+              >
+                {doc.status}
+              </span>
+            )}
+            {doc.date && <span>{doc.date}</span>}
+          </div>
+        )}
+
+        {/* Markdown body */}
+        <article
+          className="prose-doc"
+          dangerouslySetInnerHTML={{ __html: doc.html }}
+        />
+      </div>
+    </AdminShell>
+  );
+}

apps/admin/src/app/docs/page.tsx

@@ -0,0 +1,82 @@
+import Link from 'next/link';
+import { AdminShell } from '@/components/AdminShell';
+import { listAllDocs, type DocMeta } from '@/lib/docs';
+
+export const dynamic = 'force-dynamic';
+
+function StatusBadge({ status }: { status?: string }) {
+  if (!status) return null;
+  const color =
+    status === 'Accepted'
+      ? 'bg-emerald-900 text-emerald-300'
+      : status === 'Proposed'
+        ? 'bg-yellow-900 text-yellow-300'
+        : status === 'Deprecated'
+          ? 'bg-red-900 text-red-400'
+          : 'bg-gray-800 text-gray-400';
+  return (
+    <span className={`px-1.5 py-0.5 rounded text-xs font-medium ${color}`}>{status}</span>
+  );
+}
+
+function DocList({ docs, emptyText }: { docs: DocMeta[]; emptyText: string }) {
+  if (docs.length === 0) {
+    return <p className="text-sm text-gray-500">{emptyText}</p>;
+  }
+  return (
+    <ul className="divide-y divide-gray-800">
+      {docs.map((doc) => (
+        <li key={doc.href}>
+          <Link
+            href={doc.href}
+            className="flex items-center gap-4 px-4 py-3 hover:bg-gray-800 transition-colors rounded"
+          >
+            <span className="flex-1 text-sm text-gray-200 leading-snug">{doc.title}</span>
+            <StatusBadge status={doc.status} />
+            {doc.date && (
+              <span className="text-xs text-gray-600 tabular-nums w-24 text-right">
+                {doc.date}
+              </span>
+            )}
+          </Link>
+        </li>
+      ))}
+    </ul>
+  );
+}
+
+export default async function DocsPage() {
+  const { adr, architecture } = await listAllDocs();
+
+  return (
+    <AdminShell>
+      <div className="space-y-8 max-w-3xl">
+        <div>
+          <h1 className="text-xl font-semibold">Docs</h1>
+          <p className="text-sm text-gray-500 mt-0.5">
+            Architecture Decision Records and design notes from{' '}
+            <code className="text-xs bg-gray-800 px-1 py-0.5 rounded">docs/</code>
+          </p>
+        </div>
+
+        <section className="space-y-2">
+          <h2 className="text-xs text-gray-500 uppercase tracking-widest font-medium px-1">
+            Architecture Decision Records
+          </h2>
+          <div className="rounded-lg border border-gray-800 bg-gray-900 overflow-hidden">
+            <DocList docs={adr} emptyText="No ADRs found." />
+          </div>
+        </section>
+
+        <section className="space-y-2">
+          <h2 className="text-xs text-gray-500 uppercase tracking-widest font-medium px-1">
+            Architecture notes
+          </h2>
+          <div className="rounded-lg border border-gray-800 bg-gray-900 overflow-hidden">
+            <DocList docs={architecture} emptyText="No architecture docs found." />
+          </div>
+        </section>
+      </div>
+    </AdminShell>
+  );
+}

apps/admin/src/app/events/page.tsx

@@ -0,0 +1,93 @@
+'use client';
+
+import { useEffect, useRef, useState } from 'react';
+import { AdminShell } from '@/components/AdminShell';
+import { getEvents, StoredEvent } from '@/lib/api';
+
+const SUBJECTS = ['', 'signals.tip', 'signals.task', 'signals.tip.served', 'signals.tip.feedback', 'signals.task.synced'];
+
+export default function EventsPage() {
+  const [events, setEvents] = useState<StoredEvent[]>([]);
+  const [subject, setSubject] = useState('');
+  const [userId, setUserId] = useState('');
+  const [live, setLive] = useState(true);
+  const [error, setError] = useState('');
+  const sinceRef = useRef(0);
+  const timerRef = useRef<ReturnType<typeof setInterval> | null>(null);
+
+  const fetchEvents = async (reset = false) => {
+    try {
+      const since = reset ? 0 : sinceRef.current;
+      const res = await getEvents({ subject: subject || undefined, userId: userId || undefined, limit: 100, since });
+      sinceRef.current = res.nextSince;
+      setEvents((prev) => {
+        const next = reset ? res.events : [...prev, ...res.events];
+        return next.slice(-500); // keep last 500
+      });
+      setError('');
+    } catch (e: any) {
+      setError(e.message);
+    }
+  };
+
+  useEffect(() => {
+    sinceRef.current = 0;
+    fetchEvents(true);
+  }, [subject, userId]);
+
+  useEffect(() => {
+    if (live) {
+      timerRef.current = setInterval(() => fetchEvents(false), 2000);
+    } else if (timerRef.current) {
+      clearInterval(timerRef.current);
+    }
+    return () => { if (timerRef.current) clearInterval(timerRef.current); };
+  }, [live, subject, userId]);
+
+  return (
+    <AdminShell>
+      <div className="space-y-4">
+        <div className="flex items-center justify-between">
+          <h1 className="text-xl font-semibold">Event stream</h1>
+          <div className="flex items-center gap-2">
+            <label className="flex items-center gap-1.5 text-sm text-gray-400 cursor-pointer">
+              <input type="checkbox" checked={live} onChange={(e) => setLive(e.target.checked)} className="accent-indigo-500" />
+              Live
+            </label>
+            <button onClick={() => { sinceRef.current = 0; fetchEvents(true); }} className="text-xs text-gray-400 hover:text-white border border-gray-700 rounded px-2 py-1">
+              Refresh
+            </button>
+          </div>
+        </div>
+
+        <div className="flex gap-3">
+          <select value={subject} onChange={(e) => setSubject(e.target.value)} className="bg-gray-900 border border-gray-700 rounded px-2 py-1 text-sm text-gray-300">
+            {SUBJECTS.map((s) => <option key={s} value={s}>{s || 'All subjects'}</option>)}
+          </select>
+          <input
+            value={userId}
+            onChange={(e) => setUserId(e.target.value)}
+            placeholder="Filter by user ID"
+            className="bg-gray-900 border border-gray-700 rounded px-2 py-1 text-sm text-gray-300 w-64"
+          />
+        </div>
+
+        {error && <p className="text-red-400 text-sm">{error}</p>}
+
+        <div className="font-mono text-xs space-y-1 max-h-[70vh] overflow-y-auto">
+          {events.length === 0 && (
+            <p className="text-gray-500 text-sm">No events yet. Waiting…</p>
+          )}
+          {[...events].reverse().map((e) => (
+            <div key={e.id} className="flex gap-3 border-b border-gray-800 pb-1">
+              <span className="text-gray-600 w-12 flex-shrink-0">{e.id}</span>
+              <span className="text-gray-500 w-24 flex-shrink-0">{e.ts.slice(11, 19)}</span>
+              <span className="text-indigo-400 w-40 flex-shrink-0">{e.subject}</span>
+              <span className="text-gray-300 break-all">{JSON.stringify(e.payload)}</span>
+            </div>
+          ))}
+        </div>
+      </div>
+    </AdminShell>
+  );
+}

apps/admin/src/app/features/page.tsx

@@ -0,0 +1,98 @@
+'use client';
+
+import { useEffect, useState } from 'react';
+import { AdminShell } from '@/components/AdminShell';
+
+interface FeatureEntry {
+  ts: string;
+  features: Record<string, unknown>;
+  score: number;
+  tip_id: string;
+}
+
+const FEATURE_NAMES = ['hour_of_day', 'is_overdue', 'task_age_days', 'priority'];
+
+export default function FeaturesPage() {
+  const [userId, setUserId] = useState('');
+  const [history, setHistory] = useState<FeatureEntry[]>([]);
+  const [loading, setLoading] = useState(false);
+  const [error, setError] = useState('');
+
+  const fetch_ = async () => {
+    if (!userId.trim()) return;
+    setLoading(true);
+    setError('');
+    try {
+      const res = await fetch(`/api/ml/features/${encodeURIComponent(userId.trim())}`, { credentials: 'include' });
+      if (!res.ok) throw new Error(res.statusText);
+      const data = await res.json();
+      setHistory(data.history ?? []);
+    } catch (e: any) {
+      setError(e.message);
+    } finally {
+      setLoading(false);
+    }
+  };
+
+  return (
+    <AdminShell>
+      <div className="space-y-4">
+        <h1 className="text-xl font-semibold">Feature store browser</h1>
+        <p className="text-sm text-gray-500">
+          Features sent to ml/serving per scoring call for a user. Shows last 100 entries.
+        </p>
+
+        <div className="flex gap-2">
+          <input
+            value={userId}
+            onChange={(e) => setUserId(e.target.value)}
+            onKeyDown={(e) => e.key === 'Enter' && fetch_()}
+            placeholder="User ID"
+            className="bg-gray-900 border border-gray-700 rounded px-3 py-1.5 text-sm text-gray-300 w-80"
+          />
+          <button onClick={fetch_} className="bg-indigo-600 hover:bg-indigo-500 text-white rounded px-4 py-1.5 text-sm">
+            Load
+          </button>
+        </div>
+
+        {error && <p className="text-red-400 text-sm">{error}</p>}
+        {loading && <p className="text-gray-500 text-sm">Loading…</p>}
+
+        {history.length > 0 && (
+          <div className="overflow-x-auto">
+            <table className="w-full text-xs font-mono">
+              <thead>
+                <tr className="border-b border-gray-800 text-gray-500">
+                  <th className="text-left py-2 pr-4">Time</th>
+                  <th className="text-left py-2 pr-4">Score</th>
+                  {FEATURE_NAMES.map((f) => (
+                    <th key={f} className="text-left py-2 pr-4">{f}</th>
+                  ))}
+                  <th className="text-left py-2">Tip ID</th>
+                </tr>
+              </thead>
+              <tbody>
+                {[...history].reverse().map((entry, i) => (
+                  <tr key={i} className="border-b border-gray-800/50">
+                    <td className="py-1.5 pr-4 text-gray-500">{entry.ts.slice(11, 19)}</td>
+                    <td className="py-1.5 pr-4 text-indigo-300">{entry.score.toFixed(4)}</td>
+                    {FEATURE_NAMES.map((f) => (
+                      <td key={f} className="py-1.5 pr-4 text-gray-300">
+                        {String(entry.features[f] ?? '—')}
+                      </td>
+                    ))}
+                    <td className="py-1.5 text-gray-500 truncate max-w-xs">{entry.tip_id}</td>
+                  </tr>
+                ))}
+              </tbody>
+            </table>
+          </div>
+        )}
+
+        {history.length === 0 && !loading && userId && (
+          <p className="text-gray-500 text-sm">No scoring history for this user yet.</p>
+        )}
+      </div>
+    </AdminShell>
+  );
+}

apps/admin/src/app/forbidden/page.tsx

@@ -0,0 +1,10 @@
+export default function ForbiddenPage() {
+  return (
+    <div className="flex min-h-screen items-center justify-center">
+      <div className="text-center space-y-2">
+        <h1 className="text-2xl font-semibold">403 — Forbidden</h1>
+        <p className="text-gray-400 text-sm">Your account does not have admin access.</p>
+      </div>
+    </div>
+  );
+}

apps/admin/src/app/globals.css

@@ -0,0 +1,123 @@
+@tailwind base;
+@tailwind components;
+@tailwind utilities;
+
+:root {
+  --background: #0a0a0a;
+  --foreground: #ededed;
+}
+
+body {
+  background: var(--background);
+  color: var(--foreground);
+  font-family: system-ui, -apple-system, sans-serif;
+}
+
+/* -------------------------------------------------------------------------
+   Markdown prose — used on /docs pages via the .prose-doc class.
+   Purposely minimal: dark theme, respects the existing gray palette.
+   ------------------------------------------------------------------------- */
+.prose-doc {
+  color: #d1d5db;        /* gray-300 */
+  line-height: 1.7;
+  font-size: 0.9375rem;
+}
+
+.prose-doc h1,
+.prose-doc h2,
+.prose-doc h3,
+.prose-doc h4 {
+  color: #f3f4f6;        /* gray-100 */
+  font-weight: 600;
+  margin-top: 1.75em;
+  margin-bottom: 0.5em;
+  line-height: 1.3;
+}
+.prose-doc h1 { font-size: 1.5rem; margin-top: 0; border-bottom: 1px solid #374151; padding-bottom: 0.4em; }
+.prose-doc h2 { font-size: 1.2rem; }
+.prose-doc h3 { font-size: 1.05rem; }
+.prose-doc h4 { font-size: 0.95rem; }
+
+.prose-doc p { margin-top: 0.75em; margin-bottom: 0.75em; }
+.prose-doc p:first-child { margin-top: 0; }
+
+.prose-doc a {
+  color: #818cf8;        /* indigo-400 */
+  text-decoration: underline;
+  text-underline-offset: 2px;
+}
+.prose-doc a:hover { color: #a5b4fc; }
+
+.prose-doc code {
+  background: #1f2937;   /* gray-800 */
+  border-radius: 3px;
+  padding: 0.15em 0.4em;
+  font-size: 0.85em;
+  color: #e5e7eb;
+  font-family: ui-monospace, 'Cascadia Code', 'Fira Mono', monospace;
+}
+
+.prose-doc pre {
+  background: #111827;   /* gray-900 */
+  border: 1px solid #374151;
+  border-radius: 6px;
+  padding: 1em 1.25em;
+  overflow-x: auto;
+  margin: 1.25em 0;
+}
+.prose-doc pre code {
+  background: none;
+  padding: 0;
+  font-size: 0.85em;
+  color: #d1d5db;
+}
+
+.prose-doc ul,
+.prose-doc ol {
+  padding-left: 1.5em;
+  margin: 0.75em 0;
+}
+.prose-doc li { margin: 0.25em 0; }
+.prose-doc ul { list-style-type: disc; }
+.prose-doc ol { list-style-type: decimal; }
+
+.prose-doc blockquote {
+  border-left: 3px solid #4b5563;
+  margin: 1em 0;
+  padding: 0.25em 1em;
+  color: #9ca3af;
+  font-style: italic;
+}
+
+.prose-doc table {
+  width: 100%;
+  border-collapse: collapse;
+  margin: 1.25em 0;
+  font-size: 0.875rem;
+}
+.prose-doc th {
+  text-align: left;
+  padding: 0.5em 0.75em;
+  background: #1f2937;
+  color: #9ca3af;
+  font-weight: 500;
+  font-size: 0.75rem;
+  text-transform: uppercase;
+  letter-spacing: 0.05em;
+  border-bottom: 1px solid #374151;
+}
+.prose-doc td {
+  padding: 0.5em 0.75em;
+  border-bottom: 1px solid #1f2937;
+  vertical-align: top;
+}
+.prose-doc tr:last-child td { border-bottom: none; }
+
+.prose-doc hr {
+  border: none;
+  border-top: 1px solid #374151;
+  margin: 2em 0;
+}
+
+.prose-doc strong { color: #f3f4f6; font-weight: 600; }
+.prose-doc em { color: #d1d5db; }

apps/admin/src/app/health/page.tsx

@@ -0,0 +1,71 @@
+'use client';
+
+import { useEffect, useState } from 'react';
+import { AdminShell } from '@/components/AdminShell';
+import { getHealth, HealthStatus } from '@/lib/api';
+
+const STATUS_STYLES: Record<string, string> = {
+  ok: 'bg-green-900 text-green-300 border-green-800',
+  degraded: 'bg-yellow-900 text-yellow-300 border-yellow-800',
+  down: 'bg-red-900 text-red-300 border-red-800',
+};
+
+export default function HealthPage() {
+  const [health, setHealth] = useState<HealthStatus | null>(null);
+  const [loading, setLoading] = useState(true);
+  const [error, setError] = useState('');
+
+  const refresh = () => {
+    setLoading(true);
+    getHealth()
+      .then(setHealth)
+      .catch((e) => setError(e.message))
+      .finally(() => setLoading(false));
+  };
+
+  useEffect(() => {
+    refresh();
+    const t = setInterval(refresh, 15_000);
+    return () => clearInterval(t);
+  }, []);
+
+  return (
+    <AdminShell>
+      <div className="space-y-6">
+        <div className="flex items-center justify-between">
+          <h1 className="text-xl font-semibold">Health</h1>
+          <div className="flex items-center gap-3">
+            {health && (
+              <span className={`text-xs px-2 py-1 rounded border ${health.ok ? 'bg-green-900 text-green-300 border-green-800' : 'bg-red-900 text-red-300 border-red-800'}`}>
+                {health.ok ? 'All systems operational' : 'Degraded'}
+              </span>
+            )}
+            <button onClick={refresh} className="text-xs text-gray-400 hover:text-white border border-gray-700 rounded px-2 py-1">
+              Refresh
+            </button>
+          </div>
+        </div>
+
+        {error && <p className="text-red-400 text-sm">{error}</p>}
+        {loading && !health && <p className="text-gray-500 text-sm">Checking…</p>}
+
+        {health && (
+          <>
+            <div className="grid grid-cols-2 gap-3 md:grid-cols-3 lg:grid-cols-4">
+              {health.services.map((svc) => (
+                <div key={svc.name} className={`rounded border p-4 ${STATUS_STYLES[svc.status] ?? STATUS_STYLES.down}`}>
+                  <div className="text-xs font-medium uppercase tracking-wide mb-1">{svc.name}</div>
+                  <div className="text-lg font-semibold capitalize">{svc.status}</div>
+                  {svc.latencyMs > 0 && (
+                    <div className="text-xs opacity-70 mt-1">{svc.latencyMs}ms</div>
+                  )}
+                </div>
+              ))}
+            </div>
+            <p className="text-xs text-gray-600">Last checked: {health.checkedAt} · auto-refreshes every 15s</p>
+          </>
+        )}
+      </div>
+    </AdminShell>
+  );
+}

apps/admin/src/app/layout.tsx

@@ -0,0 +1,15 @@
+import type { Metadata } from 'next';
+import './globals.css';
+
+export const metadata: Metadata = {
+  title: 'oO Admin',
+  description: 'oO admin console',
+};
+
+export default function RootLayout({ children }: { children: React.ReactNode }) {
+  return (
+    <html lang="en" className="dark">
+      <body className="min-h-screen bg-gray-950 text-gray-100">{children}</body>
+    </html>
+  );
+}

apps/admin/src/app/login/page.tsx

@@ -0,0 +1,16 @@
+export default function LoginPage() {
+  return (
+    <div className="flex min-h-screen items-center justify-center">
+      <div className="text-center space-y-4">
+        <h1 className="text-2xl font-semibold">oO Admin</h1>
+        <p className="text-gray-400 text-sm">Sign in via the main app first, then return here.</p>
+        <a
+          href="/sign-in"
+          className="inline-block px-4 py-2 bg-white text-black rounded text-sm font-medium hover:bg-gray-200 transition-colors"
+        >
+          Sign in with Google
+        </a>
+      </div>
+    </div>
+  );
+}

apps/admin/src/app/ops/page.tsx

@@ -0,0 +1,114 @@
+'use client';
+
+import { useEffect, useState } from 'react';
+import { AdminShell } from '@/components/AdminShell';
+import { getPolicies, togglePolicy, replaySignal, PolicyInfo } from '@/lib/api';
+
+const VALID_SUBJECTS = ['signals.tip.served', 'signals.tip.feedback', 'signals.task.synced'];
+
+export default function OpsPage() {
+  const [policies, setPolicies] = useState<PolicyInfo[]>([]);
+  const [replaySubject, setReplaySubject] = useState(VALID_SUBJECTS[0]);
+  const [replayPayload, setReplayPayload] = useState('{\n  "userId": "",\n  "tipId": ""\n}');
+  const [msg, setMsg] = useState('');
+  const [error, setError] = useState('');
+
+  useEffect(() => {
+    getPolicies().then((r) => setPolicies(r.policies)).catch(() => {});
+  }, []);
+
+  const handleToggle = async (name: string, active: boolean) => {
+    try {
+      await togglePolicy(name, active);
+      setPolicies((prev) => prev.map((p) => p.name === name ? { ...p, active } : p));
+      setMsg(`Policy "${name}" ${active ? 'enabled' : 'disabled'}.`);
+    } catch (e: any) {
+      setError(e.message);
+    }
+  };
+
+  const handleReplay = async () => {
+    let payload: Record<string, unknown>;
+    try {
+      payload = JSON.parse(replayPayload);
+    } catch {
+      setError('Invalid JSON payload');
+      return;
+    }
+    try {
+      await replaySignal(replaySubject, payload);
+      setMsg(`Signal replayed: ${replaySubject}`);
+      setError('');
+    } catch (e: any) {
+      setError(e.message);
+    }
+  };
+
+  return (
+    <AdminShell>
+      <div className="space-y-8">
+        <h1 className="text-xl font-semibold">Ops actions</h1>
+        {msg && <p className="text-green-400 text-sm">{msg}</p>}
+        {error && <p className="text-red-400 text-sm">{error}</p>}
+
+        {/* Policy toggles */}
+        <section className="space-y-3">
+          <h2 className="text-base font-medium text-gray-300">Policies</h2>
+          {policies.length === 0 ? (
+            <p className="text-gray-500 text-sm">No shadow policies registered. Shadow policies can be added to the recommender source.</p>
+          ) : (
+            <div className="space-y-2">
+              {policies.map((p) => (
+                <div key={p.name} className="flex items-center justify-between bg-gray-900 border border-gray-800 rounded p-3">
+                  <span className="text-sm text-gray-300 font-mono">{p.name}</span>
+                  <button
+                    onClick={() => handleToggle(p.name, !p.active)}
+                    className={`px-3 py-1 rounded text-xs ${p.active ? 'bg-green-800 text-green-200' : 'bg-gray-800 text-gray-400'}`}
+                  >
+                    {p.active ? 'Active' : 'Disabled'}
+                  </button>
+                </div>
+              ))}
+            </div>
+          )}
+        </section>
+
+        {/* Replay signal */}
+        <section className="space-y-3">
+          <h2 className="text-base font-medium text-gray-300">Replay signal</h2>
+          <p className="text-sm text-gray-500">Re-emit a past event on the in-process bus. Useful for backfill and testing.</p>
+          <div className="space-y-2">
+            <select
+              value={replaySubject}
+              onChange={(e) => setReplaySubject(e.target.value)}
+              className="bg-gray-900 border border-gray-700 rounded px-3 py-1.5 text-sm text-gray-300 w-full max-w-sm"
+            >
+              {VALID_SUBJECTS.map((s) => <option key={s} value={s}>{s}</option>)}
+            </select>
+            <textarea
+              value={replayPayload}
+              onChange={(e) => setReplayPayload(e.target.value)}
+              rows={6}
+              className="w-full max-w-xl bg-gray-900 border border-gray-700 rounded px-3 py-2 text-sm font-mono text-gray-300"
+            />
+            <button
+              onClick={handleReplay}
+              className="bg-indigo-600 hover:bg-indigo-500 text-white rounded px-4 py-1.5 text-sm"
+            >
+              Replay
+            </button>
+          </div>
+        </section>
+
+        {/* User-level ops */}
+        <section className="space-y-3">
+          <h2 className="text-base font-medium text-gray-300">User-level actions</h2>
+          <p className="text-sm text-gray-500">
+            Revoke integration tokens and reset bandit state are available on the{' '}
+            <a href="/users" className="text-indigo-400 hover:underline">Users page</a> — navigate to a user detail view.
+          </p>
+        </section>
+      </div>
+    </AdminShell>
+  );
+}

apps/admin/src/app/page.tsx

@@ -0,0 +1,12 @@
+import { AdminShell } from '@/components/AdminShell';
+import { OverviewDashboard } from '@/components/OverviewDashboard';
+
+export const dynamic = 'force-dynamic';
+
+export default function OverviewPage() {
+  return (
+    <AdminShell>
+      <OverviewDashboard />
+    </AdminShell>
+  );
+}

apps/admin/src/app/reward-analytics/page.tsx

@@ -0,0 +1,144 @@
+'use client';
+
+import { useEffect, useState } from 'react';
+import { AdminShell } from '@/components/AdminShell';
+import { getRewardAnalytics } from '@/lib/api';
+
+const ACTION_COLORS: Record<string, string> = {
+  done: 'bg-green-500',
+  helpful: 'bg-teal-500',
+  snooze: 'bg-yellow-500',
+  not_helpful: 'bg-orange-500',
+  dismiss: 'bg-red-500',
+};
+
+export default function RewardAnalyticsPage() {
+  const [days, setDays] = useState(30);
+  const [data, setData] = useState<Awaited<ReturnType<typeof getRewardAnalytics>> | null>(null);
+  const [loading, setLoading] = useState(false);
+  const [error, setError] = useState('');
+
+  useEffect(() => {
+    setLoading(true);
+    getRewardAnalytics(days)
+      .then(setData)
+      .catch((e) => setError(e.message))
+      .finally(() => setLoading(false));
+  }, [days]);
+
+  // Aggregate totals per action across all days
+  const totals: Record<string, number> = {};
+  for (const row of data?.daily ?? []) {
+    totals[row.action] = (totals[row.action] ?? 0) + Number(row.count);
+  }
+  const grandTotal = Object.values(totals).reduce((a, b) => a + b, 0);
+
+  // Aggregate per policy
+  const policyMap: Record<string, Record<string, number>> = {};
+  for (const row of data?.byPolicy ?? []) {
+    if (!row.policy) continue;
+    policyMap[row.policy] ??= {};
+    if (row.action) policyMap[row.policy][row.action] = (policyMap[row.policy][row.action] ?? 0) + Number(row.count);
+  }
+
+  return (
+    <AdminShell>
+      <div className="space-y-6">
+        <div className="flex items-center gap-4">
+          <h1 className="text-xl font-semibold">Reward analytics</h1>
+          <select value={days} onChange={(e) => setDays(Number(e.target.value))} className="bg-gray-900 border border-gray-700 rounded px-2 py-1 text-sm text-gray-300">
+            <option value={7}>Last 7 days</option>
+            <option value={30}>Last 30 days</option>
+            <option value={90}>Last 90 days</option>
+          </select>
+        </div>
+
+        {error && <p className="text-red-400 text-sm">{error}</p>}
+        {loading && <p className="text-gray-500 text-sm">Loading…</p>}
+
+        {/* Reaction breakdown bar */}
+        {grandTotal > 0 && (
+          <div className="space-y-2">
+            <h2 className="text-sm font-medium text-gray-400">Reaction distribution ({grandTotal} total)</h2>
+            <div className="flex rounded overflow-hidden h-6">
+              {Object.entries(totals).map(([action, count]) => (
+                <div
+                  key={action}
+                  title={`${action}: ${count} (${((count / grandTotal) * 100).toFixed(1)}%)`}
+                  className={`${ACTION_COLORS[action] ?? 'bg-gray-500'} transition-all`}
+                  style={{ width: `${(count / grandTotal) * 100}%` }}
+                />
+              ))}
+            </div>
+            <div className="flex flex-wrap gap-3 text-xs text-gray-400">
+              {Object.entries(totals).map(([action, count]) => (
+                <span key={action} className="flex items-center gap-1">
+                  <span className={`inline-block w-2 h-2 rounded-full ${ACTION_COLORS[action] ?? 'bg-gray-500'}`} />
+                  {action}: {count} ({((count / grandTotal) * 100).toFixed(1)}%)
+                </span>
+              ))}
+            </div>
+          </div>
+        )}
+
+        {/* Per-policy table */}
+        {Object.keys(policyMap).length > 0 && (
+          <div className="space-y-2">
+            <h2 className="text-sm font-medium text-gray-400">Per-policy reactions</h2>
+            <table className="w-full text-xs">
+              <thead>
+                <tr className="border-b border-gray-800 text-gray-500 text-left">
+                  <th className="py-2 pr-4">Policy</th>
+                  {['done', 'helpful', 'snooze', 'not_helpful', 'dismiss'].map((a) => (
+                    <th key={a} className="py-2 pr-4">{a}</th>
+                  ))}
+                </tr>
+              </thead>
+              <tbody>
+                {Object.entries(policyMap).map(([policy, actions]) => (
+                  <tr key={policy} className="border-b border-gray-800/50">
+                    <td className="py-2 pr-4 font-medium text-indigo-300">{policy}</td>
+                    {['done', 'helpful', 'snooze', 'not_helpful', 'dismiss'].map((a) => (
+                      <td key={a} className="py-2 pr-4 text-gray-300">{actions[a] ?? 0}</td>
+                    ))}
+                  </tr>
+                ))}
+              </tbody>
+            </table>
+          </div>
+        )}
+
+        {/* Daily table */}
+        {(data?.daily?.length ?? 0) > 0 && (
+          <div className="space-y-2">
+            <h2 className="text-sm font-medium text-gray-400">Daily breakdown</h2>
+            <div className="overflow-x-auto max-h-80">
+              <table className="w-full text-xs font-mono">
+                <thead>
+                  <tr className="border-b border-gray-800 text-gray-500 text-left">
+                    <th className="py-1.5 pr-4">Date</th>
+                    <th className="py-1.5 pr-4">Action</th>
+                    <th className="py-1.5">Count</th>
+                  </tr>
+                </thead>
+                <tbody>
+                  {data!.daily.map((row, i) => (
+                    <tr key={i} className="border-b border-gray-800/40">
+                      <td className="py-1 pr-4 text-gray-500">{row.date}</td>
+                      <td className="py-1 pr-4 text-gray-300">{row.action}</td>
+                      <td className="py-1 text-gray-300">{row.count}</td>
+                    </tr>
+                  ))}
+                </tbody>
+              </table>
+            </div>
+          </div>
+        )}
+
+        {!loading && grandTotal === 0 && (
+          <p className="text-gray-500 text-sm">No reaction data in this period.</p>
+        )}
+      </div>
+    </AdminShell>
+  );
+}

apps/admin/src/app/sql/page.tsx

@@ -0,0 +1,152 @@
+'use client';
+
+import { useEffect, useState } from 'react';
+import { AdminShell } from '@/components/AdminShell';
+import { runSql, getSavedQueries, saveQuery, deleteSavedQuery, SavedQuery } from '@/lib/api';
+
+const EXAMPLE_QUERIES = [
+  'SELECT * FROM users ORDER BY created_at DESC LIMIT 20',
+  'SELECT action, count(*) as cnt FROM tip_feedback GROUP BY action',
+  'SELECT policy, count(*) as cnt FROM tip_scores GROUP BY policy',
+  'SELECT date(served_at) as day, count(*) as tips FROM tip_views GROUP BY day ORDER BY day DESC LIMIT 14',
+];
+
+export default function SqlPage() {
+  const [query, setQuery] = useState(EXAMPLE_QUERIES[0]);
+  const [rows, setRows] = useState<unknown[]>([]);
+  const [cols, setCols] = useState<string[]>([]);
+  const [rowCount, setRowCount] = useState<number | null>(null);
+  const [running, setRunning] = useState(false);
+  const [error, setError] = useState('');
+  const [savedQueries, setSavedQueries] = useState<SavedQuery[]>([]);
+  const [saveName, setSaveName] = useState('');
+
+  useEffect(() => {
+    getSavedQueries().then((r) => setSavedQueries(r.queries)).catch(() => {});
+  }, []);
+
+  const run = async () => {
+    if (!query.trim()) return;
+    setRunning(true);
+    setError('');
+    try {
+      const res = await runSql(query);
+      const r = res.rows as Record<string, unknown>[];
+      setRows(r);
+      setRowCount(res.rowCount);
+      setCols(r.length > 0 ? Object.keys(r[0] as object) : []);
+    } catch (e: any) {
+      setError(e.message);
+      setRows([]);
+      setRowCount(null);
+    } finally {
+      setRunning(false);
+    }
+  };
+
+  const handleSave = async () => {
+    if (!saveName.trim()) return;
+    await saveQuery(saveName, query);
+    const res = await getSavedQueries();
+    setSavedQueries(res.queries);
+    setSaveName('');
+  };
+
+  const handleDelete = async (id: string) => {
+    await deleteSavedQuery(id);
+    setSavedQueries((prev) => prev.filter((q) => q.id !== id));
+  };
+
+  return (
+    <AdminShell>
+      <div className="space-y-4">
+        <div className="flex items-center justify-between">
+          <h1 className="text-xl font-semibold">SQL runner</h1>
+          <span className="text-xs text-gray-500">Read-only · SELECT only · sunsets in M4</span>
+        </div>
+
+        <div className="flex gap-4">
+          {/* Editor */}
+          <div className="flex-1 space-y-2">
+            <textarea
+              value={query}
+              onChange={(e) => setQuery(e.target.value)}
+              onKeyDown={(e) => { if ((e.metaKey || e.ctrlKey) && e.key === 'Enter') run(); }}
+              rows={6}
+              spellCheck={false}
+              className="w-full bg-gray-900 border border-gray-700 rounded px-3 py-2 text-sm font-mono text-gray-200 focus:outline-none focus:border-indigo-500"
+              placeholder="SELECT ..."
+            />
+            <div className="flex items-center gap-2">
+              <button
+                onClick={run}
+                disabled={running}
+                className="bg-indigo-600 hover:bg-indigo-500 disabled:opacity-50 text-white rounded px-4 py-1.5 text-sm"
+              >
+                {running ? 'Running…' : 'Run (⌘↵)'}
+              </button>
+              <input
+                value={saveName}
+                onChange={(e) => setSaveName(e.target.value)}
+                placeholder="Save as…"
+                className="bg-gray-900 border border-gray-700 rounded px-3 py-1.5 text-sm text-gray-300 w-40"
+              />
+              <button onClick={handleSave} className="text-sm text-gray-400 hover:text-white border border-gray-700 rounded px-3 py-1.5">
+                Save
+              </button>
+            </div>
+          </div>
+
+          {/* Saved / examples */}
+          <div className="w-56 space-y-2 flex-shrink-0">
+            <p className="text-xs text-gray-500 font-medium uppercase tracking-wide">Saved queries</p>
+            {savedQueries.length === 0 && (
+              <p className="text-xs text-gray-600">None saved yet</p>
+            )}
+            {savedQueries.map((q) => (
+              <div key={q.id} className="flex items-start justify-between gap-1">
+                <button onClick={() => setQuery(q.sql)} className="text-xs text-indigo-400 hover:text-indigo-300 text-left">{q.name}</button>
+                <button onClick={() => handleDelete(q.id)} className="text-xs text-gray-600 hover:text-red-400">✕</button>
+              </div>
+            ))}
+            <p className="text-xs text-gray-500 font-medium uppercase tracking-wide pt-2">Examples</p>
+            {EXAMPLE_QUERIES.map((q, i) => (
+              <button key={i} onClick={() => setQuery(q)} className="block text-xs text-gray-500 hover:text-gray-300 text-left truncate w-full">
+                {q.slice(0, 40)}…
+              </button>
+            ))}
+          </div>
+        </div>
+
+        {error && <p className="text-red-400 text-sm">{error}</p>}
+
+        {rowCount !== null && (
+          <p className="text-xs text-gray-500">{rowCount} rows returned</p>
+        )}
+
+        {cols.length > 0 && (
+          <div className="overflow-auto max-h-[50vh] border border-gray-800 rounded">
+            <table className="w-full text-xs font-mono">
+              <thead className="sticky top-0 bg-gray-950">
+                <tr className="border-b border-gray-800">
+                  {cols.map((c) => (
+                    <th key={c} className="text-left py-2 px-3 text-gray-500 font-medium">{c}</th>
+                  ))}
+                </tr>
+              </thead>
+              <tbody>
+                {(rows as Record<string, unknown>[]).map((row, i) => (
+                  <tr key={i} className="border-b border-gray-800/40 hover:bg-gray-900/40">
+                    {cols.map((c) => (
+                      <td key={c} className="py-1.5 px-3 text-gray-300">{String(row[c] ?? '')}</td>
+                    ))}
+                  </tr>
+                ))}
+              </tbody>
+            </table>
+          </div>
+        )}
+      </div>
+    </AdminShell>
+  );
+}

apps/admin/src/app/tips/page.tsx

@@ -0,0 +1,97 @@
+'use client';
+
+import { useEffect, useState } from 'react';
+import { AdminShell } from '@/components/AdminShell';
+import { getTips, TipScore } from '@/lib/api';
+
+export default function TipsPage() {
+  const [tips, setTips] = useState<TipScore[]>([]);
+  const [total, setTotal] = useState(0);
+  const [offset, setOffset] = useState(0);
+  const [userId, setUserId] = useState('');
+  const [loading, setLoading] = useState(false);
+  const [error, setError] = useState('');
+  const LIMIT = 50;
+
+  const fetch_ = async (off = 0) => {
+    setLoading(true);
+    try {
+      const res = await getTips({ limit: LIMIT, offset: off, userId: userId || undefined });
+      setTips(res.tips);
+      setTotal(res.total);
+      setOffset(off);
+    } catch (e: any) {
+      setError(e.message);
+    } finally {
+      setLoading(false);
+    }
+  };
+
+  useEffect(() => { fetch_(0); }, [userId]);
+
+  return (
+    <AdminShell>
+      <div className="space-y-4">
+        <div className="flex items-center justify-between">
+          <h1 className="text-xl font-semibold">Recommendation log</h1>
+          <span className="text-sm text-gray-500">{total} total</span>
+        </div>
+
+        <div className="flex gap-2">
+          <input
+            value={userId}
+            onChange={(e) => setUserId(e.target.value)}
+            placeholder="Filter by user ID"
+            className="bg-gray-900 border border-gray-700 rounded px-3 py-1.5 text-sm text-gray-300 w-72"
+          />
+        </div>
+
+        {error && <p className="text-red-400 text-sm">{error}</p>}
+
+        <div className="overflow-x-auto">
+          <table className="w-full text-xs">
+            <thead>
+              <tr className="border-b border-gray-800 text-gray-500 text-left">
+                <th className="py-2 pr-3">Served at</th>
+                <th className="py-2 pr-3">User</th>
+                <th className="py-2 pr-3">Policy</th>
+                <th className="py-2 pr-3">Score</th>
+                <th className="py-2 pr-3">Candidates</th>
+                <th className="py-2 pr-3">Latency</th>
+                <th className="py-2">Features</th>
+              </tr>
+            </thead>
+            <tbody>
+              {tips.map((t) => {
+                const feats = t.featuresJson ? JSON.parse(t.featuresJson) : null;
+                return (
+                  <tr key={t.id} className="border-b border-gray-800/50 hover:bg-gray-900/50">
+                    <td className="py-1.5 pr-3 text-gray-500 font-mono">{t.servedAt.slice(0, 19)}</td>
+                    <td className="py-1.5 pr-3 text-gray-400 font-mono truncate max-w-[120px]">{t.userId.slice(0, 8)}…</td>
+                    <td className="py-1.5 pr-3">
+                      <span className={`px-1.5 py-0.5 rounded text-xs ${t.policy === 'random' ? 'bg-gray-800 text-gray-400' : 'bg-indigo-900 text-indigo-300'}`}>
+                        {t.policy}
+                      </span>
+                    </td>
+                    <td className="py-1.5 pr-3 font-mono text-gray-300">{t.mlScore != null ? (t.mlScore / 1000).toFixed(3) : '—'}</td>
+                    <td className="py-1.5 pr-3 text-gray-400">{t.candidateCount ?? '—'}</td>
+                    <td className="py-1.5 pr-3 text-gray-400">{t.latencyMs != null ? `${t.latencyMs}ms` : '—'}</td>
+                    <td className="py-1.5 text-gray-500 font-mono text-xs">
+                      {feats ? `p${feats.priority} ${feats.is_overdue ? '⚠' : ''}` : '—'}
+                    </td>
+                  </tr>
+                );
+              })}
+            </tbody>
+          </table>
+        </div>
+
+        <div className="flex gap-3 items-center text-sm">
+          <button onClick={() => fetch_(offset - LIMIT)} disabled={offset === 0 || loading} className="text-gray-400 hover:text-white disabled:opacity-30">← Prev</button>
+          <span className="text-gray-600">{offset + 1}–{Math.min(offset + LIMIT, total)} of {total}</span>
+          <button onClick={() => fetch_(offset + LIMIT)} disabled={offset + LIMIT >= total || loading} className="text-gray-400 hover:text-white disabled:opacity-30">Next →</button>
+        </div>
+      </div>
+    </AdminShell>
+  );
+}

apps/admin/src/app/users/[id]/page.tsx

@@ -0,0 +1,17 @@
+import { AdminShell } from '@/components/AdminShell';
+import { UserDetail } from '@/components/UserDetail';
+
+export const dynamic = 'force-dynamic';
+
+export default async function UserDetailPage({
+  params,
+}: {
+  params: Promise<{ id: string }>;
+}) {
+  const { id } = await params;
+  return (
+    <AdminShell>
+      <UserDetail userId={id} />
+    </AdminShell>
+  );
+}

apps/admin/src/app/users/page.tsx

@@ -0,0 +1,12 @@
+import { AdminShell } from '@/components/AdminShell';
+import { UsersTable } from '@/components/UsersTable';
+
+export const dynamic = 'force-dynamic';
+
+export default function UsersPage() {
+  return (
+    <AdminShell>
+      <UsersTable />
+    </AdminShell>
+  );
+}

apps/admin/src/components/AdminShell.tsx

@@ -0,0 +1,118 @@
+'use client';
+
+import Link from 'next/link';
+import { usePathname } from 'next/navigation';
+
+const mlflowUrl = process.env.NEXT_PUBLIC_MLFLOW_URL ?? '/mlflow';
+const airflowUrl = process.env.NEXT_PUBLIC_AIRFLOW_URL ?? '/airflow';
+
+type NavItem = {
+  href: string;
+  label: string;
+  external?: boolean;
+};
+
+type NavSection = {
+  label?: string;
+  items: NavItem[];
+};
+
+const NAV: NavSection[] = [
+  {
+    items: [{ href: '/', label: 'Overview' }],
+  },
+  {
+    label: 'Signals',
+    items: [
+      { href: '/users', label: 'Users' },
+      { href: '/events', label: 'Events' },
+      { href: '/features', label: 'Features' },
+      { href: '/data-quality', label: 'Data quality' },
+    ],
+  },
+  {
+    label: 'Recommender status',
+    items: [
+      { href: '/tips', label: 'Tips' },
+      { href: '/reward-analytics', label: 'Rewards' },
+    ],
+  },
+  {
+    label: 'Operations',
+    items: [
+      { href: '/health', label: 'Health' },
+      { href: '/ops', label: 'Ops' },
+      { href: '/sql', label: 'SQL runner' },
+      { href: '/audit', label: 'Audit log' },
+    ],
+  },
+  {
+    label: 'Resources',
+    items: [
+      { href: '/docs', label: 'Docs' },
+      { href: mlflowUrl, label: 'MLflow ↗', external: true },
+      { href: airflowUrl, label: 'Airflow ↗', external: true },
+    ],
+  },
+];
+
+export function AdminShell({ children }: { children: React.ReactNode }) {
+  const pathname = usePathname();
+  return (
+    <div className="flex min-h-screen">
+      {/* Sidebar */}
+      <aside className="w-52 flex-shrink-0 border-r border-gray-800 bg-gray-950 flex flex-col">
+        <div className="px-5 py-4 border-b border-gray-800">
+          <span className="text-lg font-bold tracking-tight">oO</span>
+          <span className="ml-2 text-xs text-gray-500 font-medium uppercase tracking-widest">
+            Admin
+          </span>
+        </div>
+        <nav className="flex-1 px-2 py-3 overflow-y-auto">
+          {NAV.map((section, sectionIdx) => (
+            <div key={section.label ?? `top-${sectionIdx}`} className={sectionIdx === 0 ? '' : 'pt-3'}>
+              {section.label && (
+                <div className="pb-1 px-3">
+                  <span className="text-xs text-gray-600 uppercase tracking-wider font-medium">
+                    {section.label}
+                  </span>
+                </div>
+              )}
+              <div className="space-y-0.5">
+                {section.items.map((item) => {
+                  const active =
+                    !item.external &&
+                    (item.href === '/' ? pathname === '/' : pathname.startsWith(item.href));
+                  const className = `flex items-center px-3 py-2 rounded text-sm transition-colors ${
+                    active
+                      ? 'bg-gray-800 text-white font-medium'
+                      : item.external
+                        ? 'text-gray-500 hover:text-white hover:bg-gray-900'
+                        : 'text-gray-400 hover:text-white hover:bg-gray-900'
+                  }`;
+                  return item.external ? (
+                    <a
+                      key={item.href}
+                      href={item.href}
+                      target="_blank"
+                      rel="noreferrer"
+                      className={className}
+                    >
+                      {item.label}
+                    </a>
+                  ) : (
+                    <Link key={item.href} href={item.href} className={className}>
+                      {item.label}
+                    </Link>
+                  );
+                })}
+              </div>
+            </div>
+          ))}
+        </nav>
+      </aside>
+      {/* Main content */}
+      <main className="flex-1 overflow-auto p-6">{children}</main>
+    </div>
+  );
+}

apps/admin/src/components/AuditLog.tsx

@@ -0,0 +1,112 @@
+'use client';
+
+import { useEffect, useState } from 'react';
+import { getAuditLog, type AuditAction } from '@/lib/api';
+
+const PAGE_SIZE = 50;
+
+export function AuditLog() {
+  const [rows, setRows] = useState<AuditAction[]>([]);
+  const [total, setTotal] = useState(0);
+  const [offset, setOffset] = useState(0);
+  const [error, setError] = useState<string | null>(null);
+  const [loading, setLoading] = useState(true);
+
+  useEffect(() => {
+    setLoading(true);
+    getAuditLog(PAGE_SIZE, offset)
+      .then(({ actions, total }) => {
+        setRows(actions);
+        setTotal(total);
+      })
+      .catch((e) => setError(String(e.message)))
+      .finally(() => setLoading(false));
+  }, [offset]);
+
+  if (error) return <p className="text-red-400 text-sm">Error: {error}</p>;
+
+  return (
+    <div className="space-y-4">
+      <div className="flex items-center justify-between">
+        <h1 className="text-xl font-semibold">Audit log</h1>
+        <span className="text-sm text-gray-500">{total} entries</span>
+      </div>
+
+      <div className="rounded-lg border border-gray-800 overflow-hidden">
+        <table className="w-full text-sm">
+          <thead className="bg-gray-900 border-b border-gray-800">
+            <tr>
+              {['Time', 'Admin', 'Action', 'Target'].map((h) => (
+                <th
+                  key={h}
+                  className="text-left px-4 py-2.5 text-xs text-gray-500 font-medium uppercase tracking-wide"
+                >
+                  {h}
+                </th>
+              ))}
+            </tr>
+          </thead>
+          <tbody className="divide-y divide-gray-800">
+            {loading ? (
+              <tr>
+                <td colSpan={4} className="px-4 py-6 text-center text-gray-500">
+                  Loading…
+                </td>
+              </tr>
+            ) : rows.length === 0 ? (
+              <tr>
+                <td colSpan={4} className="px-4 py-6 text-center text-gray-500">
+                  No actions logged yet.
+                </td>
+              </tr>
+            ) : (
+              rows.map((a) => (
+                <tr key={a.id} className="hover:bg-gray-900 transition-colors">
+                  <td className="px-4 py-2.5 text-xs tabular-nums text-gray-400">
+                    {a.createdAt.slice(0, 19).replace('T', ' ')}
+                  </td>
+                  <td className="px-4 py-2.5 font-mono text-xs text-gray-300 truncate max-w-[8rem]">
+                    {a.adminId.slice(0, 8)}…
+                  </td>
+                  <td className="px-4 py-2.5">
+                    <span className="px-1.5 py-0.5 rounded bg-gray-800 text-xs text-gray-200 font-mono">
+                      {a.action}
+                    </span>
+                  </td>
+                  <td className="px-4 py-2.5 text-xs text-gray-400">
+                    {a.targetType && (
+                      <span className="text-gray-500">{a.targetType}: </span>
+                    )}
+                    <span className="font-mono">{a.targetId?.slice(0, 12) ?? '—'}</span>
+                  </td>
+                </tr>
+              ))
+            )}
+          </tbody>
+        </table>
+      </div>
+
+      {total > PAGE_SIZE && (
+        <div className="flex items-center gap-3 text-sm">
+          <button
+            disabled={offset === 0}
+            onClick={() => setOffset(Math.max(0, offset - PAGE_SIZE))}
+            className="px-3 py-1.5 rounded border border-gray-700 disabled:opacity-30 hover:border-gray-500 transition-colors"
+          >
+            Previous
+          </button>
+          <span className="text-gray-500">
+            {offset + 1}–{Math.min(offset + PAGE_SIZE, total)} of {total}
+          </span>
+          <button
+            disabled={offset + PAGE_SIZE >= total}
+            onClick={() => setOffset(offset + PAGE_SIZE)}
+            className="px-3 py-1.5 rounded border border-gray-700 disabled:opacity-30 hover:border-gray-500 transition-colors"
+          >
+            Next
+          </button>
+        </div>
+      )}
+    </div>
+  );
+}

apps/admin/src/components/OverviewDashboard.tsx

@@ -0,0 +1,165 @@
+'use client';
+
+import { useEffect, useState } from 'react';
+import { getStats, type AdminStats } from '@/lib/api';
+
+function KpiCard({
+  title,
+  value,
+  sub,
+}: {
+  title: string;
+  value: string | number;
+  sub?: string;
+}) {
+  return (
+    <div className="rounded-lg border border-gray-800 bg-gray-900 px-5 py-4 space-y-1">
+      <p className="text-xs text-gray-500 uppercase tracking-widest font-medium">{title}</p>
+      <p className="text-3xl font-bold tabular-nums">{value}</p>
+      {sub && <p className="text-xs text-gray-500">{sub}</p>}
+    </div>
+  );
+}
+
+function ReactionBar({ reactions }: { reactions: Record<string, number> }) {
+  const total = Object.values(reactions).reduce((a, b) => a + b, 0);
+  if (total === 0) return <p className="text-sm text-gray-500">No reactions yet.</p>;
+
+  const COLORS: Record<string, string> = {
+    done: 'bg-emerald-500',
+    snooze: 'bg-yellow-400',
+    dismiss: 'bg-red-500',
+  };
+
+  return (
+    <div className="space-y-2">
+      {Object.entries(reactions).map(([action, count]) => (
+        <div key={action} className="flex items-center gap-3">
+          <span className="w-16 text-xs text-gray-400 capitalize">{action}</span>
+          <div className="flex-1 bg-gray-800 rounded-full h-2">
+            <div
+              className={`${COLORS[action] ?? 'bg-gray-500'} h-2 rounded-full transition-all`}
+              style={{ width: `${((count / total) * 100).toFixed(1)}%` }}
+            />
+          </div>
+          <span className="w-8 text-right text-xs tabular-nums text-gray-400">{count}</span>
+        </div>
+      ))}
+    </div>
+  );
+}
+
+export function OverviewDashboard() {
+  const [stats, setStats] = useState<AdminStats | null>(null);
+  const [error, setError] = useState<string | null>(null);
+
+  useEffect(() => {
+    getStats()
+      .then(setStats)
+      .catch((e) => setError(String(e.message)));
+  }, []);
+
+  if (error) {
+    return <p className="text-red-400 text-sm">Failed to load stats: {error}</p>;
+  }
+
+  const activationPct =
+    stats && stats.totalUsers > 0
+      ? ((stats.activatedUsers / stats.totalUsers) * 100).toFixed(1)
+      : null;
+
+  return (
+    <div className="space-y-8">
+      <div>
+        <h1 className="text-xl font-semibold">Overview</h1>
+        <p className="text-sm text-gray-500 mt-0.5">Last 7 days unless noted</p>
+      </div>
+
+      {/* KPI grid */}
+      <div className="grid grid-cols-2 lg:grid-cols-4 gap-4">
+        <KpiCard title="DAU" value={stats?.dau ?? '—'} sub="unique users today" />
+        <KpiCard title="WAU" value={stats?.wau ?? '—'} sub="unique users last 7 d" />
+        <KpiCard
+          title="Tips served"
+          value={stats?.tipsServedLast7d ?? '—'}
+          sub="last 7 days"
+        />
+        <KpiCard
+          title="Activation"
+          value={activationPct != null ? `${activationPct}%` : '—'}
+          sub={
+            stats
+              ? `${stats.activatedUsers} of ${stats.totalUsers} users`
+              : 'users who saw ≥1 tip'
+          }
+        />
+      </div>
+
+      {/* Reactions */}
+      <div className="rounded-lg border border-gray-800 bg-gray-900 px-5 py-4 max-w-sm">
+        <p className="text-xs text-gray-500 uppercase tracking-widest font-medium mb-3">
+          Reactions last 7 days
+        </p>
+        {stats ? (
+          <ReactionBar reactions={stats.reactionsLast7d} />
+        ) : (
+          <p className="text-sm text-gray-500">Loading…</p>
+        )}
+      </div>
+
+      {/* Activation funnel */}
+      <div className="rounded-lg border border-gray-800 bg-gray-900 px-5 py-4 max-w-sm">
+        <p className="text-xs text-gray-500 uppercase tracking-widest font-medium mb-3">
+          Activation funnel
+        </p>
+        {stats ? (
+          <div className="space-y-2 text-sm">
+            <FunnelRow label="Total users" value={stats.totalUsers} max={stats.totalUsers} />
+            <FunnelRow
+              label="Saw ≥1 tip"
+              value={stats.activatedUsers}
+              max={stats.totalUsers}
+            />
+            <FunnelRow
+              label="Reacted to tip"
+              value={Object.values(stats.reactionsLast7d).reduce((a, b) => a + b, 0)}
+              max={stats.tipsServedLast7d}
+              dimMax
+            />
+          </div>
+        ) : (
+          <p className="text-sm text-gray-500">Loading…</p>
+        )}
+      </div>
+    </div>
+  );
+}
+
+function FunnelRow({
+  label,
+  value,
+  max,
+  dimMax,
+}: {
+  label: string;
+  value: number;
+  max: number;
+  dimMax?: boolean;
+}) {
+  const pct = max > 0 ? (value / max) * 100 : 0;
+  return (
+    <div className="flex items-center gap-3">
+      <span className="w-32 text-gray-400 text-xs">{label}</span>
+      <div className="flex-1 bg-gray-800 rounded-full h-1.5">
+        <div
+          className="bg-indigo-500 h-1.5 rounded-full transition-all"
+          style={{ width: `${pct.toFixed(1)}%` }}
+        />
+      </div>
+      <span className="w-8 text-right text-xs tabular-nums text-gray-300">{value}</span>
+      {!dimMax && max > 0 && (
+        <span className="text-xs text-gray-600 tabular-nums">{pct.toFixed(0)}%</span>
+      )}
+    </div>
+  );
+}

apps/admin/src/components/UserDetail.tsx

@@ -0,0 +1,159 @@
+'use client';
+
+import { useEffect, useState } from 'react';
+import { getUserDetail, revokeIntegration, resetBandit, type AdminUserDetail } from '@/lib/api';
+
+export function UserDetail({ userId }: { userId: string }) {
+  const [data, setData] = useState<AdminUserDetail | null>(null);
+  const [error, setError] = useState<string | null>(null);
+  const [busy, setBusy] = useState<string | null>(null); // which action is running
+
+  useEffect(() => {
+    getUserDetail(userId)
+      .then(setData)
+      .catch((e) => setError(String(e.message)));
+  }, [userId]);
+
+  async function handleRevoke(provider: string) {
+    if (!confirm(`Revoke ${provider} for this user?`)) return;
+    setBusy(`revoke:${provider}`);
+    try {
+      await revokeIntegration(userId, provider);
+      setData((d) =>
+        d
+          ? { ...d, integrations: d.integrations.filter((i) => i.provider !== provider) }
+          : d,
+      );
+    } catch (e: unknown) {
+      alert(`Failed: ${(e as Error).message}`);
+    } finally {
+      setBusy(null);
+    }
+  }
+
+  async function handleResetBandit() {
+    if (!confirm("Reset this user's LinUCB model? Their personalization will start over.")) return;
+    setBusy('bandit');
+    try {
+      await resetBandit(userId);
+      alert('Bandit reset.');
+    } catch (e: unknown) {
+      alert(`Failed: ${(e as Error).message}`);
+    } finally {
+      setBusy(null);
+    }
+  }
+
+  if (error) return <p className="text-red-400 text-sm">Error: {error}</p>;
+  if (!data) return <p className="text-gray-500 text-sm">Loading…</p>;
+
+  const { user, integrations, tipsServed, lastTipAt, recentFeedback } = data;
+
+  return (
+    <div className="space-y-6 max-w-2xl">
+      {/* Header */}
+      <div className="flex items-start justify-between">
+        <div>
+          <h1 className="text-xl font-semibold">{user.name ?? user.email}</h1>
+          <p className="text-sm text-gray-400 mt-0.5">{user.email}</p>
+        </div>
+        <div className="flex gap-2">
+          <button
+            onClick={handleResetBandit}
+            disabled={busy === 'bandit'}
+            className="px-3 py-1.5 text-xs rounded border border-gray-700 hover:border-red-600 hover:text-red-400 transition-colors disabled:opacity-40"
+          >
+            {busy === 'bandit' ? 'Resetting…' : 'Reset bandit'}
+          </button>
+        </div>
+      </div>
+
+      {/* Identity */}
+      <Section title="Identity">
+        <Row label="ID" value={user.id} mono />
+        <Row label="Role" value={user.role} />
+        <Row label="Consent" value={user.consentGiven ? `yes (${user.consentAt?.slice(0, 10)})` : 'no'} />
+        <Row label="Joined" value={user.createdAt.slice(0, 10)} />
+        {user.deletedAt && <Row label="Deleted" value={user.deletedAt.slice(0, 10)} />}
+      </Section>
+
+      {/* Integrations */}
+      <Section title="Integrations">
+        {integrations.length === 0 ? (
+          <p className="text-sm text-gray-500">No integrations connected.</p>
+        ) : (
+          integrations.map((i) => (
+            <div key={i.provider} className="flex items-center justify-between py-1">
+              <div>
+                <span className="text-sm capitalize">{i.provider}</span>
+                <span className="ml-2 text-xs text-gray-500">
+                  connected {i.connectedAt.slice(0, 10)}
+                </span>
+              </div>
+              <button
+                onClick={() => handleRevoke(i.provider)}
+                disabled={busy === `revoke:${i.provider}`}
+                className="text-xs text-red-500 hover:text-red-400 transition-colors disabled:opacity-40"
+              >
+                {busy === `revoke:${i.provider}` ? 'Revoking…' : 'Revoke'}
+              </button>
+            </div>
+          ))
+        )}
+      </Section>
+
+      {/* Tip stats */}
+      <Section title="Tip activity">
+        <Row label="Tips served (all time)" value={String(tipsServed)} />
+        <Row label="Last tip" value={lastTipAt?.slice(0, 19).replace('T', ' ') ?? '—'} />
+      </Section>
+
+      {/* Feedback history */}
+      <Section title="Recent feedback">
+        {recentFeedback.length === 0 ? (
+          <p className="text-sm text-gray-500">No feedback recorded.</p>
+        ) : (
+          <div className="space-y-1">
+            {recentFeedback.map((f) => (
+              <div key={f.id} className="flex items-center gap-4 text-sm">
+                <span
+                  className={`w-16 text-xs font-medium ${
+                    f.action === 'done'
+                      ? 'text-emerald-400'
+                      : f.action === 'snooze'
+                        ? 'text-yellow-400'
+                        : 'text-red-400'
+                  }`}
+                >
+                  {f.action}
+                </span>
+                <span className="text-gray-500 text-xs tabular-nums">
+                  {f.createdAt.slice(0, 19).replace('T', ' ')}
+                </span>
+                <span className="text-gray-600 text-xs font-mono truncate">{f.tipId}</span>
+              </div>
+            ))}
+          </div>
+        )}
+      </Section>
+    </div>
+  );
+}
+
+function Section({ title, children }: { title: string; children: React.ReactNode }) {
+  return (
+    <div className="rounded-lg border border-gray-800 bg-gray-900 px-5 py-4 space-y-2">
+      <p className="text-xs text-gray-500 uppercase tracking-widest font-medium mb-3">{title}</p>
+      {children}
+    </div>
+  );
+}
+
+function Row({ label, value, mono }: { label: string; value: string; mono?: boolean }) {
+  return (
+    <div className="flex items-baseline gap-3 text-sm">
+      <span className="w-36 flex-shrink-0 text-gray-500">{label}</span>
+      <span className={mono ? 'font-mono text-xs text-gray-300' : 'text-gray-200'}>{value}</span>
+    </div>
+  );
+}

apps/admin/src/components/UsersTable.tsx

@@ -0,0 +1,134 @@
+'use client';
+
+import { useEffect, useState } from 'react';
+import Link from 'next/link';
+import { getUsers, type AdminUser } from '@/lib/api';
+
+const PAGE_SIZE = 50;
+
+export function UsersTable() {
+  const [users, setUsers] = useState<AdminUser[]>([]);
+  const [total, setTotal] = useState(0);
+  const [offset, setOffset] = useState(0);
+  const [error, setError] = useState<string | null>(null);
+  const [loading, setLoading] = useState(true);
+
+  useEffect(() => {
+    setLoading(true);
+    getUsers(PAGE_SIZE, offset)
+      .then(({ users, total }) => {
+        setUsers(users);
+        setTotal(total);
+      })
+      .catch((e) => setError(String(e.message)))
+      .finally(() => setLoading(false));
+  }, [offset]);
+
+  if (error) return <p className="text-red-400 text-sm">Error: {error}</p>;
+
+  return (
+    <div className="space-y-4">
+      <div className="flex items-center justify-between">
+        <h1 className="text-xl font-semibold">Users</h1>
+        <span className="text-sm text-gray-500">{total} total</span>
+      </div>
+
+      <div className="rounded-lg border border-gray-800 overflow-hidden">
+        <table className="w-full text-sm">
+          <thead className="bg-gray-900 border-b border-gray-800">
+            <tr>
+              {['Email', 'Name', 'Role', 'Consent', 'Joined', 'Status'].map((h) => (
+                <th
+                  key={h}
+                  className="text-left px-4 py-2.5 text-xs text-gray-500 font-medium uppercase tracking-wide"
+                >
+                  {h}
+                </th>
+              ))}
+            </tr>
+          </thead>
+          <tbody className="divide-y divide-gray-800">
+            {loading ? (
+              <tr>
+                <td colSpan={6} className="px-4 py-6 text-center text-gray-500">
+                  Loading…
+                </td>
+              </tr>
+            ) : users.length === 0 ? (
+              <tr>
+                <td colSpan={6} className="px-4 py-6 text-center text-gray-500">
+                  No users yet.
+                </td>
+              </tr>
+            ) : (
+              users.map((u) => (
+                <tr
+                  key={u.id}
+                  className="hover:bg-gray-900 transition-colors cursor-pointer"
+                >
+                  <td className="px-4 py-2.5">
+                    <Link href={`/users/${u.id}`} className="hover:underline text-indigo-400">
+                      {u.email}
+                    </Link>
+                  </td>
+                  <td className="px-4 py-2.5 text-gray-300">{u.name ?? '—'}</td>
+                  <td className="px-4 py-2.5">
+                    <span
+                      className={`px-1.5 py-0.5 rounded text-xs font-medium ${
+                        u.role === 'admin'
+                          ? 'bg-indigo-900 text-indigo-300'
+                          : 'bg-gray-800 text-gray-400'
+                      }`}
+                    >
+                      {u.role}
+                    </span>
+                  </td>
+                  <td className="px-4 py-2.5">
+                    {u.consentGiven ? (
+                      <span className="text-emerald-400 text-xs">yes</span>
+                    ) : (
+                      <span className="text-gray-600 text-xs">no</span>
+                    )}
+                  </td>
+                  <td className="px-4 py-2.5 text-gray-400 text-xs tabular-nums">
+                    {u.createdAt.slice(0, 10)}
+                  </td>
+                  <td className="px-4 py-2.5">
+                    {u.deletedAt ? (
+                      <span className="text-red-500 text-xs">deleted</span>
+                    ) : (
+                      <span className="text-emerald-500 text-xs">active</span>
+                    )}
+                  </td>
+                </tr>
+              ))
+            )}
+          </tbody>
+        </table>
+      </div>
+
+      {/* Pagination */}
+      {total > PAGE_SIZE && (
+        <div className="flex items-center gap-3 text-sm">
+          <button
+            disabled={offset === 0}
+            onClick={() => setOffset(Math.max(0, offset - PAGE_SIZE))}
+            className="px-3 py-1.5 rounded border border-gray-700 disabled:opacity-30 hover:border-gray-500 transition-colors"
+          >
+            Previous
+          </button>
+          <span className="text-gray-500">
+            {offset + 1}–{Math.min(offset + PAGE_SIZE, total)} of {total}
+          </span>
+          <button
+            disabled={offset + PAGE_SIZE >= total}
+            onClick={() => setOffset(offset + PAGE_SIZE)}
+            className="px-3 py-1.5 rounded border border-gray-700 disabled:opacity-30 hover:border-gray-500 transition-colors"
+          >
+            Next
+          </button>
+        </div>
+      )}
+    </div>
+  );
+}

apps/admin/src/lib/api.ts

@@ -0,0 +1,222 @@
+const API = '/api';
+
+async function apiFetch<T>(path: string, init?: RequestInit): Promise<T> {
+  const res = await fetch(`${API}${path}`, {
+    credentials: 'include',
+    ...init,
+    headers: { 'Content-Type': 'application/json', ...init?.headers },
+  });
+  if (!res.ok) {
+    const err = await res.json().catch(() => ({ error: res.statusText }));
+    throw Object.assign(new Error(err.error ?? 'API error'), { status: res.status });
+  }
+  return res.json() as T;
+}
+
+// ── Types ──────────────────────────────────────────────────────────────────
+
+export interface AdminStats {
+  dau: number;
+  wau: number;
+  tipsServedLast7d: number;
+  reactionsLast7d: Record<string, number>;
+  totalUsers: number;
+  activatedUsers: number;
+}
+
+export interface AdminUser {
+  id: string;
+  email: string;
+  name: string | null;
+  image: string | null;
+  role: string;
+  consentGiven: boolean;
+  consentAt: string | null;
+  createdAt: string;
+  deletedAt: string | null;
+}
+
+export interface AdminUserDetail {
+  user: AdminUser;
+  integrations: { provider: string; connectedAt: string }[];
+  tipsServed: number;
+  lastTipAt: string | null;
+  recentFeedback: { id: string; action: string; createdAt: string; tipId: string }[];
+}
+
+export interface AuditAction {
+  id: string;
+  adminId: string;
+  action: string;
+  targetType: string | null;
+  targetId: string | null;
+  detail: string | null;
+  createdAt: string;
+}
+
+export interface StoredEvent {
+  id: number;
+  subject: string;
+  payload: unknown;
+  ts: string;
+}
+
+export interface TipScore {
+  id: string;
+  userId: string;
+  tipId: string;
+  policy: string;
+  mlScore: number | null;
+  featuresJson: string | null;
+  candidateCount: number | null;
+  latencyMs: number | null;
+  servedAt: string;
+}
+
+export interface HealthStatus {
+  ok: boolean;
+  checkedAt: string;
+  services: { name: string; status: string; latencyMs: number }[];
+}
+
+export interface PolicyInfo {
+  name: string;
+  active: boolean;
+}
+
+export interface SavedQuery {
+  id: string;
+  name: string;
+  sql: string;
+  createdAt: string;
+}
+
+export interface BanditStats {
+  user_id: string;
+  pulls: number;
+  reward_count: number;
+  cumulative_reward: number;
+  estimated_mean_reward: number;
+  theta: number[];
+  last_updated: string | null;
+}
+
+export interface FeatureHistory {
+  user_id: string;
+  history: { ts: string; features: Record<string, unknown>; score: number; tip_id: string }[];
+}
+
+// ── Fetchers ───────────────────────────────────────────────────────────────
+
+export function getStats() {
+  return apiFetch<AdminStats>('/admin/stats');
+}
+
+export function getUsers(limit = 50, offset = 0) {
+  return apiFetch<{ users: AdminUser[]; total: number }>(
+    `/admin/users?limit=${limit}&offset=${offset}`,
+  );
+}
+
+export function getUserDetail(id: string) {
+  return apiFetch<AdminUserDetail>(`/admin/users/${id}`);
+}
+
+export function revokeIntegration(userId: string, provider: string) {
+  return apiFetch<{ ok: boolean }>(`/admin/users/${userId}/revoke-integration`, {
+    method: 'POST',
+    body: JSON.stringify({ provider }),
+  });
+}
+
+export function resetBandit(userId: string) {
+  return apiFetch<{ ok: boolean }>(`/admin/users/${userId}/reset-bandit`, {
+    method: 'POST',
+  });
+}
+
+export function getAuditLog(limit = 50, offset = 0) {
+  return apiFetch<{ actions: AuditAction[]; total: number }>(
+    `/admin/audit?limit=${limit}&offset=${offset}`,
+  );
+}
+
+export function getEvents(params: { subject?: string; userId?: string; limit?: number; since?: number } = {}) {
+  const q = new URLSearchParams();
+  if (params.subject) q.set('subject', params.subject);
+  if (params.userId) q.set('userId', params.userId);
+  if (params.limit) q.set('limit', String(params.limit));
+  if (params.since) q.set('since', String(params.since));
+  return apiFetch<{ events: StoredEvent[]; nextSince: number }>(`/admin/events?${q}`);
+}
+
+export function getTips(params: { limit?: number; offset?: number; userId?: string } = {}) {
+  const q = new URLSearchParams();
+  if (params.limit) q.set('limit', String(params.limit));
+  if (params.offset) q.set('offset', String(params.offset));
+  if (params.userId) q.set('userId', params.userId);
+  return apiFetch<{ tips: TipScore[]; total: number }>(`/admin/tips?${q}`);
+}
+
+export function getRewardAnalytics(days = 30) {
+  return apiFetch<{
+    daily: { date: string; action: string; count: number }[];
+    byPolicy: { policy: string; action: string; count: number }[];
+    byHour: { action: string; count: number; avgHour: number }[];
+  }>(`/admin/reward-analytics?days=${days}`);
+}
+
+export function getDataQuality() {
+  return apiFetch<{
+    scoringCallsLast30d: number;
+    missingFeatureRate: number;
+    staleTokenRate: number;
+    totalTokens: number;
+    staleTokens: number;
+    dailyQuality: { date: string; total: number; withFeatures: number; avgCandidates: number }[];
+  }>('/admin/data-quality');
+}
+
+export function getHealth() {
+  return apiFetch<HealthStatus>('/admin/health');
+}
+
+export function getPolicies() {
+  return apiFetch<{ policies: PolicyInfo[] }>('/admin/policies');
+}
+
+export function togglePolicy(name: string, active: boolean) {
+  return apiFetch<{ ok: boolean }>(`/admin/policies/${name}/toggle`, {
+    method: 'POST',
+    body: JSON.stringify({ active }),
+  });
+}
+
+export function replaySignal(subject: string, payload: Record<string, unknown>) {
+  return apiFetch<{ ok: boolean }>('/admin/replay-signal', {
+    method: 'POST',
+    body: JSON.stringify({ subject, payload }),
+  });
+}
+
+export function runSql(query: string) {
+  return apiFetch<{ rows: unknown[]; rowCount: number }>('/admin/sql', {
+    method: 'POST',
+    body: JSON.stringify({ query }),
+  });
+}
+
+export function getSavedQueries() {
+  return apiFetch<{ queries: SavedQuery[] }>('/admin/saved-queries');
+}
+
+export function saveQuery(name: string, querySql: string) {
+  return apiFetch<{ id: string }>('/admin/saved-queries', {
+    method: 'POST',
+    body: JSON.stringify({ name, querySql }),
+  });
+}
+
+export function deleteSavedQuery(id: string) {
+  return apiFetch<{ ok: boolean }>(`/admin/saved-queries/${id}`, { method: 'DELETE' });
+}

apps/admin/src/lib/docs.ts

@@ -0,0 +1,119 @@
+/**
+ * Server-side utilities for reading project documentation from the monorepo
+ * `docs/` directory and rendering it as HTML.
+ *
+ * All functions are async and must only be called from server components or
+ * server actions (no 'use client' imports of this module).
+ *
+ * Directory layout relative to monorepo root:
+ *   docs/adr/         — Architecture Decision Records (NNN-title.md)
+ *   docs/architecture/ — longer architecture notes (topic.md)
+ */
+import { readdir, readFile } from 'fs/promises';
+import path from 'path';
+import { marked } from 'marked';
+
+// apps/admin sits two levels below the monorepo root.
+const DOCS_ROOT = path.resolve(process.cwd(), '../../docs');
+
+export type DocCategory = 'adr' | 'architecture';
+
+export interface DocMeta {
+  category: DocCategory;
+  slug: string;         // filename without .md
+  title: string;        // first H1 from the file, fallback = slug
+  href: string;         // /docs/adr/0001-monorepo-polyglot
+  status?: string;      // for ADRs: "Accepted", "Proposed", …
+  date?: string;        // for ADRs: date after em-dash on Status line
+}
+
+export interface DocPage extends DocMeta {
+  html: string;
+}
+
+// ---------------------------------------------------------------------------
+// internal helpers
+// ---------------------------------------------------------------------------
+
+/** Extract the first # heading from markdown. */
+function extractTitle(md: string): string {
+  const m = md.match(/^#\s+(.+)$/m);
+  return m ? m[1].trim() : '';
+}
+
+/** Extract status + date from "## Status\nAccepted — 2026-04-13" pattern. */
+function extractStatus(md: string): { status?: string; date?: string } {
+  const block = md.match(/##\s+Status\s*\n+([^\n#]+)/);
+  if (!block) return {};
+  const line = block[1].trim();
+  // "Accepted — 2026-04-13" or "Proposed"
+  const parts = line.split(/\s*[–—]\s*/);
+  return { status: parts[0]?.trim(), date: parts[1]?.trim() };
+}
+
+function slugFromFile(filename: string): string {
+  return filename.replace(/\.md$/, '');
+}
+
+// ---------------------------------------------------------------------------
+// public API
+// ---------------------------------------------------------------------------
+
+/** List all docs in a category, sorted by filename. */
+export async function listDocs(category: DocCategory): Promise<DocMeta[]> {
+  const dir = path.join(DOCS_ROOT, category);
+  let files: string[];
+  try {
+    files = (await readdir(dir)).filter((f) => f.endsWith('.md')).sort();
+  } catch {
+    return [];
+  }
+
+  return Promise.all(
+    files.map(async (file) => {
+      const slug = slugFromFile(file);
+      const md = await readFile(path.join(dir, file), 'utf8');
+      const title = extractTitle(md) || slug;
+      const { status, date } = extractStatus(md);
+      return {
+        category,
+        slug,
+        title,
+        href: `/docs/${category}/${slug}`,
+        status,
+        date,
+      };
+    }),
+  );
+}
+
+/** List all docs across all categories. */
+export async function listAllDocs(): Promise<Record<DocCategory, DocMeta[]>> {
+  const [adr, architecture] = await Promise.all([listDocs('adr'), listDocs('architecture')]);
+  return { adr, architecture };
+}
+
+/** Read and render a single doc to HTML. */
+export async function getDoc(category: DocCategory, slug: string): Promise<DocPage | null> {
+  const file = path.join(DOCS_ROOT, category, `${slug}.md`);
+  let md: string;
+  try {
+    md = await readFile(file, 'utf8');
+  } catch {
+    return null;
+  }
+
+  const title = extractTitle(md) || slug;
+  const { status, date } = extractStatus(md);
+  const html = await marked(md, { gfm: true });
+
+  return {
+    category,
+    slug,
+    title,
+    href: `/docs/${category}/${slug}`,
+    status,
+    date,
+    html,
+  };
+}

apps/admin/src/middleware.ts

@@ -0,0 +1,49 @@
+import { NextResponse } from 'next/server';
+import type { NextRequest } from 'next/server';
+
+export async function middleware(req: NextRequest) {
+  const { pathname } = req.nextUrl;
+
+  // Pass through the login page and API calls
+  if (pathname.startsWith('/login') || pathname.startsWith('/api/')) {
+    return NextResponse.next();
+  }
+
+  const sid = req.cookies.get('sid')?.value;
+  if (!sid) {
+    const url = req.nextUrl.clone();
+    url.pathname = '/login';
+    return NextResponse.redirect(url);
+  }
+
+  // Verify admin role via API. INTERNAL_API_URL (e.g. http://api:3078) is preferred
+  // when set — it points to the API service on the internal Docker network, avoiding
+  // a Caddy round-trip. Falls back to NEXT_PUBLIC_API_URL for dev, or localhost.
+  const apiBase =
+    process.env.INTERNAL_API_URL ||
+    process.env.NEXT_PUBLIC_API_URL ||
+    'http://localhost:3078';
+  try {
+    const profile = await fetch(`${apiBase}/api/user/me`, {
+      headers: { cookie: `sid=${sid}` },
+      next: { revalidate: 0 },
+    });
+    if (!profile.ok) throw new Error('not ok');
+    const data = (await profile.json()) as { role?: string };
+    if (data.role !== 'admin') {
+      const url = req.nextUrl.clone();
+      url.pathname = '/forbidden';
+      return NextResponse.redirect(url);
+    }
+  } catch {
+    const url = req.nextUrl.clone();
+    url.pathname = '/login';
+    return NextResponse.redirect(url);
+  }
+
+  return NextResponse.next();
+}
+
+export const config = {
+  matcher: ['/', '/((?!_next/static|_next/image|favicon.ico).*)'],
+};

apps/admin/tailwind.config.ts

@@ -0,0 +1,12 @@
+import type { Config } from 'tailwindcss';
+
+const config: Config = {
+  content: [
+    './src/**/*.{ts,tsx}',
+    './node_modules/@tremor/**/*.{js,jsx,ts,tsx}',
+  ],
+  theme: { extend: {} },
+  plugins: [],
+};
+
+export default config;

apps/admin/tsconfig.json

@@ -0,0 +1,23 @@
+{
+  "compilerOptions": {
+    "target": "ES2017",
+    "lib": ["dom", "dom.iterable", "esnext"],
+    "allowJs": true,
+    "skipLibCheck": true,
+    "strict": true,
+    "noEmit": true,
+    "esModuleInterop": true,
+    "module": "esnext",
+    "moduleResolution": "bundler",
+    "resolveJsonModule": true,
+    "isolatedModules": true,
+    "jsx": "preserve",
+    "incremental": true,
+    "plugins": [{ "name": "next" }],
+    "paths": {
+      "@/*": ["./src/*"]
+    }
+  },
+  "include": ["next-env.d.ts", "**/*.ts", "**/*.tsx", ".next/types/**/*.ts"],
+  "exclude": ["node_modules"]
+}

apps/web/e2e/sign-in.spec.ts

@@ -0,0 +1,11 @@
+import { test, expect } from '@playwright/test';
+
+test('sign-in page loads and shows Google button', async ({ page }) => {
+  await page.goto('/sign-in');
+  await expect(page.getByRole('link', { name: /google/i })).toBeVisible();
+});
+
+test('unauthenticated root redirects to sign-in', async ({ page }) => {
+  await page.goto('/');
+  await expect(page).toHaveURL(/sign-in/);
+});

apps/web/next-env.d.ts

@@ -0,0 +1,6 @@
+/// <reference types="next" />
+/// <reference types="next/image-types/global" />
+/// <reference path="./.next/types/routes.d.ts" />
+
+// NOTE: This file should not be edited
+// see https://nextjs.org/docs/app/api-reference/config/typescript for more information.

apps/web/next.config.ts

@@ -0,0 +1,18 @@
+import type { NextConfig } from 'next';
+import path from 'node:path';
+
+const nextConfig: NextConfig = {
+  output: 'standalone',
+  outputFileTracingRoot: path.join(__dirname, '../../'),
+  async rewrites() {
+    return [
+      {
+        source: '/api/:path*',
+        destination: `${process.env.NEXT_PUBLIC_API_URL ?? 'http://localhost:3078'}/api/:path*`,
+        // In production, Caddy routes /api/* directly to the API — this rewrite only fires in dev
+      },
+    ];
+  },
+};
+
+export default nextConfig;

apps/web/package.json

@@ -0,0 +1,37 @@
+{
+  "name": "@oo/web",
+  "version": "0.0.0",
+  "private": true,
+  "scripts": {
+    "dev": "next dev -p 3079",
+    "build": "next build",
+    "start": "next start -p 3079",
+    "lint": "next lint",
+    "test": "vitest run",
+    "test:watch": "vitest",
+    "test:e2e": "playwright test",
+    "test:e2e:ui": "playwright test --ui",
+    "type-check": "tsc --noEmit",
+    "clean": "rm -rf .next"
+  },
+  "dependencies": {
+    "@oo/shared-types": "workspace:*",
+    "next": "^15.1.6",
+    "react": "^19.0.0",
+    "react-dom": "^19.0.0"
+  },
+  "devDependencies": {
+    "@playwright/test": "^1.59.1",
+    "@testing-library/jest-dom": "^6.9.1",
+    "@testing-library/react": "^16.3.2",
+    "@testing-library/user-event": "^14.6.1",
+    "@types/node": "^22.10.5",
+    "@types/react": "^19.0.0",
+    "@types/react-dom": "^19.0.0",
+    "@vitejs/plugin-react": "^6.0.1",
+    "@vitest/coverage-v8": "^4.1.4",
+    "jsdom": "^29.0.2",
+    "typescript": "^5.7.3",
+    "vitest": "^4.1.4"
+  }
+}

apps/web/playwright.config.ts

@@ -0,0 +1,24 @@
+import { defineConfig, devices } from '@playwright/test';
+
+export default defineConfig({
+  testDir: './e2e',
+  fullyParallel: true,
+  forbidOnly: !!process.env.CI,
+  retries: process.env.CI ? 2 : 0,
+  reporter: 'html',
+  use: {
+    baseURL: process.env.BASE_URL ?? 'http://localhost:3079',
+    trace: 'on-first-retry',
+  },
+  projects: [
+    { name: 'chromium', use: { ...devices['Desktop Chrome'] } },
+  ],
+  // Start dev server automatically in CI; locally, run `pnpm dev` first
+  webServer: process.env.CI
+    ? {
+        command: 'pnpm build && pnpm start',
+        url: 'http://localhost:3079',
+        reuseExistingServer: false,
+      }
+    : undefined,
+});

apps/web/public/manifest.json

@@ -0,0 +1,21 @@
+{
+  "name": "oO",
+  "short_name": "oO",
+  "description": "One tip. Right now.",
+  "start_url": "/tip",
+  "display": "standalone",
+  "background_color": "#000000",
+  "theme_color": "#000000",
+  "icons": [
+    {
+      "src": "/icon-192.png",
+      "sizes": "192x192",
+      "type": "image/png"
+    },
+    {
+      "src": "/icon-512.png",
+      "sizes": "512x512",
+      "type": "image/png"
+    }
+  ]
+}

apps/web/public/sw.js

@@ -0,0 +1,25 @@
+self.addEventListener('push', (event) => {
+  const data = event.data?.json() ?? {};
+  event.waitUntil(
+    self.registration.showNotification(data.title ?? 'oO', {
+      body: data.body ?? '',
+      icon: '/icon-192.png',
+      badge: '/icon-192.png',
+      data: { url: data.url ?? '/tip' },
+    })
+  );
+});
+
+self.addEventListener('notificationclick', (event) => {
+  event.notification.close();
+  event.waitUntil(
+    clients.matchAll({ type: 'window', includeUncontrolled: true }).then((list) => {
+      for (const client of list) {
+        if (client.url.includes(self.location.origin) && 'focus' in client) {
+          return client.focus();
+        }
+      }
+      return clients.openWindow(event.notification.data?.url ?? '/tip');
+    })
+  );
+});

apps/web/src/app/connect/page.tsx

@@ -0,0 +1,179 @@
+'use client';
+
+import { useEffect, useState, useCallback } from 'react';
+import { useSearchParams } from 'next/navigation';
+import { getIntegrations, disconnectIntegration, deleteAccount, logout } from '@/lib/api';
+import type { Integration } from '@oo/shared-types';
+import { Suspense } from 'react';
+
+function ConnectPageInner() {
+  const searchParams = useSearchParams();
+  const [integrations, setIntegrations] = useState<Integration[]>([]);
+  const [loading, setLoading] = useState(true);
+  const [disconnecting, setDisconnecting] = useState<string | null>(null);
+  const [deleting, setDeleting] = useState(false);
+
+  const load = useCallback(async () => {
+    const { integrations: list } = await getIntegrations();
+    setIntegrations(list);
+    setLoading(false);
+  }, []);
+
+  useEffect(() => { load(); }, [load]);
+
+  // Show banner if just connected
+  const justConnected = searchParams.get('connected');
+
+  const isConnected = (provider: string) =>
+    integrations.some((i) => i.provider === provider && i.status === 'connected');
+
+  const handleDeleteAccount = async () => {
+    if (!confirm('Delete your account? This cannot be undone.')) return;
+    setDeleting(true);
+    await deleteAccount();
+    await logout();
+    window.location.href = '/sign-in';
+  };
+
+  const handleDisconnect = async (provider: string) => {
+    setDisconnecting(provider);
+    await disconnectIntegration(provider);
+    await load();
+    setDisconnecting(null);
+  };
+
+  if (loading) {
+    return (
+      <main style={{ minHeight: '100vh', display: 'flex', alignItems: 'center', justifyContent: 'center' }}>
+        <div style={{ color: 'var(--gray)', fontSize: '0.875rem' }}>Loading…</div>
+      </main>
+    );
+  }
+
+  const todoistConnected = isConnected('todoist');
+
+  return (
+    <main style={{ minHeight: '100vh', padding: '4rem 2rem', maxWidth: '480px', margin: '0 auto' }}>
+      <h2 style={{ fontSize: '1.5rem', fontWeight: 300, marginBottom: '0.5rem', letterSpacing: '-0.02em' }}>
+        Connect your apps
+      </h2>
+      <p style={{ color: 'var(--gray)', fontSize: '0.875rem', marginBottom: '3rem' }}>
+        oO reads what you need, when you need it.
+      </p>
+
+      {justConnected && (
+        <div style={{
+          background: 'rgba(255,255,255,0.06)',
+          borderRadius: '0.5rem',
+          padding: '0.75rem 1rem',
+          marginBottom: '1.5rem',
+          fontSize: '0.875rem',
+          color: 'var(--white)',
+        }}>
+          {justConnected} connected.
+        </div>
+      )}
+
+      {/* Todoist card */}
+      <div style={{
+        border: '1px solid rgba(255,255,255,0.1)',
+        borderRadius: '0.75rem',
+        padding: '1.25rem 1.5rem',
+        display: 'flex',
+        alignItems: 'center',
+        justifyContent: 'space-between',
+        marginBottom: '1rem',
+      }}>
+        <div style={{ display: 'flex', alignItems: 'center', gap: '0.875rem' }}>
+          {/* Todoist logomark */}
+          <svg width="28" height="28" viewBox="0 0 24 24" fill="none" aria-label="Todoist">
+            <rect width="24" height="24" rx="6" fill="#DB4035"/>
+            <path d="M6 8.5L11 13l7-7" stroke="#fff" strokeWidth="2" strokeLinecap="round" strokeLinejoin="round"/>
+          </svg>
+          <div>
+            <div style={{ fontWeight: 500, fontSize: '0.9rem' }}>Todoist</div>
+            <div style={{ color: 'var(--gray)', fontSize: '0.75rem', marginTop: '0.1rem' }}>
+              {todoistConnected ? 'Connected' : 'Tasks & to-dos'}
+            </div>
+          </div>
+        </div>
+
+        {todoistConnected ? (
+          <button
+            onClick={() => handleDisconnect('todoist')}
+            disabled={disconnecting === 'todoist'}
+            style={{
+              background: 'transparent',
+              border: '1px solid rgba(255,255,255,0.15)',
+              color: 'var(--gray)',
+              borderRadius: '0.375rem',
+              padding: '0.375rem 0.875rem',
+              fontSize: '0.8rem',
+            }}
+          >
+            {disconnecting === 'todoist' ? '…' : 'Disconnect'}
+          </button>
+        ) : (
+          <a
+            href="/api/integrations/todoist/connect?redirectTo=/connect"
+            style={{
+              background: 'var(--white)',
+              color: 'var(--black)',
+              borderRadius: '0.375rem',
+              padding: '0.375rem 0.875rem',
+              fontSize: '0.8rem',
+              fontWeight: 500,
+            }}
+          >
+            Connect
+          </a>
+        )}
+      </div>
+
+      {todoistConnected && (
+        <div style={{ marginTop: '3rem' }}>
+          <a
+            href="/tip"
+            style={{
+              display: 'block',
+              textAlign: 'center',
+              background: 'var(--white)',
+              color: 'var(--black)',
+              borderRadius: '0.5rem',
+              padding: '0.875rem',
+              fontWeight: 500,
+              fontSize: '0.9rem',
+            }}
+          >
+            See my tip →
+          </a>
+        </div>
+      )}
+
+      <div style={{ marginTop: '4rem', borderTop: '1px solid rgba(255,255,255,0.06)', paddingTop: '2rem' }}>
+        <button
+          onClick={handleDeleteAccount}
+          disabled={deleting}
+          style={{
+            background: 'transparent',
+            border: 'none',
+            color: 'rgba(255,255,255,0.2)',
+            fontSize: '0.8rem',
+            cursor: 'pointer',
+            padding: 0,
+          }}
+        >
+          {deleting ? 'Deleting…' : 'Delete account'}
+        </button>
+      </div>
+    </main>
+  );
+}
+
+export default function ConnectPage() {
+  return (
+    <Suspense>
+      <ConnectPageInner />
+    </Suspense>
+  );
+}

apps/web/src/app/globals.css

@@ -0,0 +1,31 @@
+*, *::before, *::after {
+  box-sizing: border-box;
+  margin: 0;
+  padding: 0;
+}
+
+:root {
+  --black: #000;
+  --white: #fff;
+  --gray: #888;
+  --dim: rgba(255,255,255,0.08);
+  --font: -apple-system, BlinkMacSystemFont, 'SF Pro Display', 'Segoe UI', sans-serif;
+}
+
+html, body {
+  height: 100%;
+  background: var(--black);
+  color: var(--white);
+  font-family: var(--font);
+  -webkit-font-smoothing: antialiased;
+}
+
+a {
+  color: inherit;
+  text-decoration: none;
+}
+
+button {
+  cursor: pointer;
+  font-family: inherit;
+}

apps/web/src/app/layout.tsx

@@ -0,0 +1,21 @@
+import type { Metadata, Viewport } from 'next';
+import './globals.css';
+
+export const metadata: Metadata = {
+  title: 'oO',
+  description: 'One tip. Right now.',
+  manifest: '/manifest.json',
+  appleWebApp: { capable: true, statusBarStyle: 'black', title: 'oO' },
+};
+
+export const viewport: Viewport = {
+  themeColor: '#000000',
+};
+
+export default function RootLayout({ children }: { children: React.ReactNode }) {
+  return (
+    <html lang="en">
+      <body>{children}</body>
+    </html>
+  );
+}

apps/web/src/app/legal/privacy/page.tsx

@@ -0,0 +1,41 @@
+export default function Privacy() {
+  return (
+    <main style={{ maxWidth: '640px', margin: '0 auto', padding: '4rem 2rem', lineHeight: 1.7 }}>
+      <h1 style={{ fontSize: '1.5rem', fontWeight: 300, marginBottom: '2rem', letterSpacing: '-0.02em' }}>Privacy Policy</h1>
+
+      <p style={{ color: 'rgba(255,255,255,0.5)', fontSize: '0.8rem', marginBottom: '2.5rem' }}>Effective: 1 April 2026</p>
+
+      <section style={{ marginBottom: '2rem' }}>
+        <h2 style={{ fontSize: '1rem', fontWeight: 500, marginBottom: '0.75rem' }}>What we collect</h2>
+        <ul style={{ color: 'rgba(255,255,255,0.7)', fontSize: '0.9rem', paddingLeft: '1.25rem' }}>
+          <li style={{ marginBottom: '0.5rem' }}>Your Google account email, name, and profile picture — to identify you.</li>
+          <li style={{ marginBottom: '0.5rem' }}>OAuth tokens for integrations you explicitly connect.</li>
+          <li style={{ marginBottom: '0.5rem' }}>Your reactions to tips (done / snooze / dismiss) — to improve recommendations.</li>
+        </ul>
+      </section>
+
+      <section style={{ marginBottom: '2rem' }}>
+        <h2 style={{ fontSize: '1rem', fontWeight: 500, marginBottom: '0.75rem' }}>What we don't collect</h2>
+        <p style={{ color: 'rgba(255,255,255,0.7)', fontSize: '0.9rem' }}>
+          We do not copy your tasks, calendar events, or any third-party app content into our database. Data is fetched on demand and held in memory for at most 30 seconds.
+        </p>
+      </section>
+
+      <section style={{ marginBottom: '2rem' }}>
+        <h2 style={{ fontSize: '1rem', fontWeight: 500, marginBottom: '0.75rem' }}>How we use it</h2>
+        <p style={{ color: 'rgba(255,255,255,0.7)', fontSize: '0.9rem' }}>
+          Solely to operate the recommendation engine. We do not sell data, share it with third parties, or use it for advertising.
+        </p>
+      </section>
+
+      <section style={{ marginBottom: '2rem' }}>
+        <h2 style={{ fontSize: '1rem', fontWeight: 500, marginBottom: '0.75rem' }}>Your rights</h2>
+        <p style={{ color: 'rgba(255,255,255,0.7)', fontSize: '0.9rem' }}>
+          You can disconnect any integration at any time from the Connect page. You can delete your account, which permanently purges all stored data. Contact the owner for data export requests.
+        </p>
+      </section>
+
+      <a href="/sign-in" style={{ color: 'rgba(255,255,255,0.35)', fontSize: '0.8rem' }}>← Back</a>
+    </main>
+  );
+}

apps/web/src/app/legal/terms/page.tsx

@@ -0,0 +1,39 @@
+export default function Terms() {
+  return (
+    <main style={{ maxWidth: '640px', margin: '0 auto', padding: '4rem 2rem', lineHeight: 1.7 }}>
+      <h1 style={{ fontSize: '1.5rem', fontWeight: 300, marginBottom: '2rem', letterSpacing: '-0.02em' }}>Terms of Service</h1>
+
+      <p style={{ color: 'rgba(255,255,255,0.5)', fontSize: '0.8rem', marginBottom: '2.5rem' }}>Effective: 1 April 2026</p>
+
+      <section style={{ marginBottom: '2rem' }}>
+        <h2 style={{ fontSize: '1rem', fontWeight: 500, marginBottom: '0.75rem' }}>1. The service</h2>
+        <p style={{ color: 'rgba(255,255,255,0.7)', fontSize: '0.9rem' }}>
+          oO is a personal recommendation system. It reads signals from apps you connect and surfaces one tip at a time. The service is provided as-is during the prototype phase.
+        </p>
+      </section>
+
+      <section style={{ marginBottom: '2rem' }}>
+        <h2 style={{ fontSize: '1rem', fontWeight: 500, marginBottom: '0.75rem' }}>2. Your data</h2>
+        <p style={{ color: 'rgba(255,255,255,0.7)', fontSize: '0.9rem' }}>
+          We store OAuth tokens for integrations you connect. We fetch your tasks on demand — we do not copy or cache raw data beyond a 30-second in-memory buffer. You can revoke access or delete your account at any time.
+        </p>
+      </section>
+
+      <section style={{ marginBottom: '2rem' }}>
+        <h2 style={{ fontSize: '1rem', fontWeight: 500, marginBottom: '0.75rem' }}>3. Account deletion</h2>
+        <p style={{ color: 'rgba(255,255,255,0.7)', fontSize: '0.9rem' }}>
+          Deleting your account revokes all integration tokens, purges your feedback history, and anonymises your identity record. No data is retained in identifiable form.
+        </p>
+      </section>
+
+      <section style={{ marginBottom: '2rem' }}>
+        <h2 style={{ fontSize: '1rem', fontWeight: 500, marginBottom: '0.75rem' }}>4. Limitations</h2>
+        <p style={{ color: 'rgba(255,255,255,0.7)', fontSize: '0.9rem' }}>
+          This is a prototype. We make no uptime guarantees. The service may change or be discontinued with reasonable notice.
+        </p>
+      </section>
+
+      <a href="/sign-in" style={{ color: 'rgba(255,255,255,0.35)', fontSize: '0.8rem' }}>← Back</a>
+    </main>
+  );
+}

apps/web/src/app/page.tsx

@@ -0,0 +1,6 @@
+// Root redirect: send users to /tip (auth guard lives there)
+import { redirect } from 'next/navigation';
+
+export default function Home() {
+  redirect('/tip');
+}

apps/web/src/app/sign-in/page.tsx

@@ -0,0 +1,58 @@
+'use client';
+
+// Auth redirect is handled by middleware — no client-side session check needed here.
+export default function SignIn() {
+
+  return (
+    <main style={{
+      minHeight: '100vh',
+      display: 'flex',
+      flexDirection: 'column',
+      alignItems: 'center',
+      justifyContent: 'center',
+      padding: '2rem',
+      gap: '3rem',
+    }}>
+      <div style={{ textAlign: 'center' }}>
+        <h1 style={{ fontSize: '4rem', fontWeight: 200, letterSpacing: '-0.05em', marginBottom: '0.5rem' }}>oO</h1>
+        <p style={{ color: 'var(--gray)', fontSize: '1rem', fontWeight: 300 }}>
+          one tip. right now.
+        </p>
+      </div>
+
+      <div style={{ display: 'flex', flexDirection: 'column', gap: '1rem', width: '100%', maxWidth: '320px' }}>
+        <a
+          href="/api/auth/login?redirectTo=/connect"
+          style={{
+            display: 'flex',
+            alignItems: 'center',
+            justifyContent: 'center',
+            gap: '0.75rem',
+            padding: '0.875rem 1.5rem',
+            background: 'var(--white)',
+            color: 'var(--black)',
+            borderRadius: '0.5rem',
+            fontSize: '0.9rem',
+            fontWeight: 500,
+            letterSpacing: '0.01em',
+          }}
+        >
+          <svg width="18" height="18" viewBox="0 0 18 18" aria-hidden>
+            <path fill="#4285F4" d="M17.64 9.2c0-.637-.057-1.251-.164-1.84H9v3.481h4.844c-.209 1.125-.843 2.078-1.796 2.717v2.258h2.908c1.702-1.567 2.684-3.874 2.684-6.615z"/>
+            <path fill="#34A853" d="M9 18c2.43 0 4.467-.806 5.956-2.184l-2.908-2.258c-.806.54-1.837.86-3.048.86-2.344 0-4.328-1.584-5.036-3.711H.957v2.332A8.997 8.997 0 0 0 9 18z"/>
+            <path fill="#FBBC05" d="M3.964 10.707A5.41 5.41 0 0 1 3.682 9c0-.593.102-1.17.282-1.707V4.961H.957A8.996 8.996 0 0 0 0 9c0 1.452.348 2.827.957 4.039l3.007-2.332z"/>
+            <path fill="#EA4335" d="M9 3.58c1.321 0 2.508.454 3.44 1.345l2.582-2.58C13.463.891 11.426 0 9 0A8.997 8.997 0 0 0 .957 4.96l3.007 2.332C4.672 5.163 6.656 3.58 9 3.58z"/>
+          </svg>
+          Continue with Google
+        </a>
+      </div>
+
+      <p style={{ color: 'var(--gray)', fontSize: '0.75rem', textAlign: 'center', maxWidth: '280px', lineHeight: 1.6 }}>
+        By continuing you agree to our{' '}
+        <a href="/legal/terms" style={{ textDecoration: 'underline' }}>Terms</a>
+        {' '}and{' '}
+        <a href="/legal/privacy" style={{ textDecoration: 'underline' }}>Privacy Policy</a>.
+      </p>
+    </main>
+  );
+}

apps/web/src/app/tip/page.tsx

@@ -0,0 +1,323 @@
+'use client';
+
+import { useEffect, useState, useRef, useCallback } from 'react';
+import { getRecommendation, sendFeedback, getVapidPublicKey, subscribePush } from '@/lib/api';
+import type { Tip } from '@oo/shared-types';
+
+type State = 'loading' | 'tip' | 'empty' | 'actions' | 'done';
+
+// Fade wrapper — children fade in when `visible`, fade out when not
+function Fade({ visible, children, style }: {
+  visible: boolean;
+  children: React.ReactNode;
+  style?: React.CSSProperties;
+}) {
+  return (
+    <div style={{
+      opacity: visible ? 1 : 0,
+      transition: visible ? 'opacity 3.5s ease' : 'opacity 0.3s ease',
+      pointerEvents: visible ? 'auto' : 'none',
+      ...style,
+    }}>
+      {children}
+    </div>
+  );
+}
+
+export default function TipPage() {
+  const [tip, setTip] = useState<Tip | null>(null);
+  const [state, setState] = useState<State>('loading');
+  const [visible, setVisible] = useState(false);
+  const holdTimer = useRef<ReturnType<typeof setTimeout> | null>(null);
+  const [pressed, setPressed] = useState(false);
+  const [pushState, setPushState] = useState<'idle' | 'subscribed' | 'denied'>('idle');
+
+  // Fade in after state change settles
+  useEffect(() => {
+    if (state === 'loading' || state === 'done') {
+      setVisible(false);
+    } else {
+      const t = setTimeout(() => setVisible(true), 30);
+      return () => clearTimeout(t);
+    }
+  }, [state]);
+
+  const loadTip = useCallback(async () => {
+    setVisible(false);
+    setState('loading');
+    try {
+      const rec = await getRecommendation();
+      if (!rec) {
+        setState('empty');
+        return;
+      }
+      setTip(rec.tip);
+      setState('tip');
+    } catch (err: any) {
+      console.error('[tip] loadTip error', err?.status, err?.message);
+      setState('empty');
+    }
+  }, []);
+
+  useEffect(() => { loadTip(); }, [loadTip]);
+
+  // Check existing push permission on mount
+  useEffect(() => {
+    if (typeof Notification !== 'undefined' && Notification.permission === 'granted') {
+      setPushState('subscribed');
+    } else if (typeof Notification !== 'undefined' && Notification.permission === 'denied') {
+      setPushState('denied');
+    }
+  }, []);
+
+  const requestPush = useCallback(async () => {
+    if (!('serviceWorker' in navigator) || !('PushManager' in window)) return;
+    const permission = await Notification.requestPermission();
+    if (permission !== 'granted') { setPushState('denied'); return; }
+    try {
+      const reg = await navigator.serviceWorker.register('/sw.js');
+      const vapidKey = await getVapidPublicKey();
+      const sub = await reg.pushManager.subscribe({
+        userVisibleOnly: true,
+        applicationServerKey: vapidKey,
+      });
+      await subscribePush(sub.toJSON());
+      setPushState('subscribed');
+    } catch { setPushState('denied'); }
+  }, []);
+
+  const react = async (action: 'done' | 'dismiss' | 'snooze' | 'helpful' | 'not_helpful') => {
+    if (!tip) return;
+    const isNavigating = ['done', 'dismiss', 'snooze'].includes(action);
+    if (isNavigating) {
+      setVisible(false);
+      setState('done');
+    } else {
+      setState('tip');
+    }
+    await sendFeedback(tip.id, { action });
+    if (isNavigating) setTimeout(() => loadTip(), 700);
+  };
+
+  const onPointerDown = () => {
+    if (state !== 'tip') return;
+    setPressed(true);
+    holdTimer.current = setTimeout(() => {
+      setState('actions');
+      setVisible(true);
+      setPressed(false);
+    }, 600);
+  };
+
+  const onPointerUp = () => {
+    setPressed(false);
+    if (holdTimer.current) {
+      clearTimeout(holdTimer.current);
+      holdTimer.current = null;
+    }
+  };
+
+  return (
+    <>
+
+      <style>{`
+        @keyframes breathe {
+          0%, 100% { opacity: 0.3; }
+          50%       { opacity: 1;   }
+        }
+      `}</style>
+
+      <main
+        onPointerDown={onPointerDown}
+        onPointerUp={onPointerUp}
+        onPointerLeave={onPointerUp}
+        style={{
+          height: '100dvh',
+          display: 'flex',
+          flexDirection: 'column',
+          alignItems: 'center',
+          justifyContent: 'center',
+          userSelect: 'none',
+          WebkitUserSelect: 'none',
+          cursor: state === 'tip' ? 'default' : 'auto',
+          position: 'relative',
+          overflow: 'hidden',
+        }}
+      >
+        {/* Ambient glow — breathes while loading */}
+        <div style={{
+          position: 'absolute',
+          inset: 0,
+          background: 'radial-gradient(ellipse at center, rgba(255,255,255,0.06) 0%, transparent 65%)',
+          animation: state === 'loading' ? 'breathe 4s ease-in-out infinite' : undefined,
+          opacity: state === 'loading' ? undefined : pressed ? 0.3 : 0,
+          transition: state !== 'loading' ? 'opacity 0.4s ease' : undefined,
+          pointerEvents: 'none',
+        }} />
+
+        {/* Loading label */}
+        {(state === 'loading' || state === 'done') && (
+          <p style={{
+            margin: 0,
+            color: 'rgba(255,255,255,0.55)',
+            fontSize: '0.7rem',
+            letterSpacing: '0.18em',
+            textTransform: 'uppercase',
+            animation: 'breathe 4s ease-in-out infinite',
+          }}>
+            reading you…
+          </p>
+        )}
+
+        {/* Tip */}
+        {(state === 'tip' || state === 'actions') && tip && (
+          <Fade visible={visible && state !== 'actions'} style={{ textAlign: 'center', maxWidth: '420px', padding: '0 2rem' }}>
+            <p style={{
+              fontSize: 'clamp(1.25rem, 4vw, 1.75rem)',
+              fontWeight: 300,
+              lineHeight: 1.45,
+              letterSpacing: '-0.01em',
+              color: 'rgba(255,255,255,1)',
+              transition: 'opacity 0.2s ease',
+              opacity: pressed ? 0.5 : 1,
+            }}>
+              {tip.content}
+            </p>
+            <p style={{
+              marginTop: '2rem',
+              color: 'rgba(255,255,255,0.18)',
+              fontSize: '0.65rem',
+              letterSpacing: '0.12em',
+              textTransform: 'uppercase',
+            }}>
+              hold to act
+            </p>
+            {pushState === 'idle' && (
+              <button
+                onClick={(e) => { e.stopPropagation(); requestPush(); }}
+                style={{
+                  marginTop: '2.5rem',
+                  background: 'transparent',
+                  border: 'none',
+                  color: 'rgba(255,255,255,0.18)',
+                  fontSize: '0.65rem',
+                  letterSpacing: '0.12em',
+                  textTransform: 'uppercase',
+                  cursor: 'pointer',
+                  padding: 0,
+                }}
+              >
+                notify me
+              </button>
+            )}
+          </Fade>
+        )}
+
+        {/* Empty */}
+        {state === 'empty' && (
+          <Fade visible={visible} style={{ textAlign: 'center' }}>
+            <p style={{ fontSize: '1.1rem', fontWeight: 300, color: 'rgba(255,255,255,0.35)' }}>
+              All clear.
+            </p>
+            <button
+              onClick={loadTip}
+              style={{
+                marginTop: '2rem',
+                background: 'transparent',
+                border: '1px solid rgba(255,255,255,0.1)',
+                color: 'rgba(255,255,255,0.35)',
+                borderRadius: '0.375rem',
+                padding: '0.5rem 1rem',
+                fontSize: '0.8rem',
+                cursor: 'pointer',
+              }}
+            >
+              Check again
+            </button>
+          </Fade>
+        )}
+
+        {/* Action sheet */}
+        {state === 'actions' && (
+          <>
+            <div
+              onClick={() => { setState('tip'); }}
+              style={{
+                position: 'fixed',
+                inset: 0,
+                background: 'rgba(0,0,0,0.5)',
+                animation: 'none',
+              }}
+            />
+            <div style={{
+              position: 'fixed',
+              bottom: 0,
+              left: 0,
+              right: 0,
+              background: '#111',
+              borderRadius: '1rem 1rem 0 0',
+              padding: '1.5rem 1.5rem 2.5rem',
+              display: 'flex',
+              flexDirection: 'column',
+              gap: '0.75rem',
+              transform: 'translateY(0)',
+              transition: 'transform 0.3s ease',
+            }}>
+              {tip && (
+                <p style={{
+                  color: 'rgba(255,255,255,0.35)',
+                  fontSize: '0.8rem',
+                  marginBottom: '0.5rem',
+                  lineHeight: 1.4,
+                }}>
+                  {tip.content}
+                </p>
+              )}
+              <ActionButton label="Done ✓" onClick={() => react('done')} primary />
+              <ActionButton label="Helpful" onClick={() => react('helpful')} />
+              <ActionButton label="Not helpful" onClick={() => react('not_helpful')} />
+              <ActionButton label="Snooze" onClick={() => react('snooze')} />
+              <ActionButton label="Dismiss" onClick={() => react('dismiss')} />
+              <button
+                onClick={() => setState('tip')}
+                style={{
+                  background: 'transparent',
+                  border: 'none',
+                  color: 'rgba(255,255,255,0.25)',
+                  padding: '0.5rem',
+                  fontSize: '0.8rem',
+                  cursor: 'pointer',
+                  marginTop: '0.25rem',
+                }}
+              >
+                Cancel
+              </button>
+            </div>
+          </>
+        )}
+      </main>
+    </>
+  );
+}
+
+function ActionButton({ label, onClick, primary }: { label: string; onClick: () => void; primary?: boolean }) {
+  return (
+    <button
+      onClick={onClick}
+      style={{
+        background: primary ? 'var(--white)' : 'rgba(255,255,255,0.06)',
+        color: primary ? 'var(--black)' : 'var(--white)',
+        border: 'none',
+        borderRadius: '0.625rem',
+        padding: '1rem',
+        fontSize: '0.95rem',
+        fontWeight: primary ? 500 : 400,
+        width: '100%',
+        textAlign: 'center',
+        cursor: 'pointer',
+      }}
+    >
+      {label}
+    </button>
+  );
+}

apps/web/src/components/__tests__/TipPage.test.tsx

@@ -0,0 +1,131 @@
+import { describe, it, expect, vi, beforeEach } from 'vitest';
+import { render, screen, waitFor, act, fireEvent } from '@testing-library/react';
+import userEvent from '@testing-library/user-event';
+
+// Mock the API module — we test UI behaviour, not network calls
+vi.mock('@/lib/api', () => ({
+  getRecommendation: vi.fn(),
+  sendFeedback: vi.fn().mockResolvedValue(undefined),
+  getVapidPublicKey: vi.fn(),
+  subscribePush: vi.fn(),
+}));
+
+import { getRecommendation, sendFeedback } from '@/lib/api';
+import TipPage from '@/app/tip/page';
+
+const mockGetRec = getRecommendation as ReturnType<typeof vi.fn>;
+const mockSendFeedback = sendFeedback as ReturnType<typeof vi.fn>;
+
+beforeEach(() => {
+  vi.clearAllMocks();
+});
+
+describe('TipPage — empty / error states', () => {
+  it('shows "All clear." when no tip is returned', async () => {
+    mockGetRec.mockResolvedValue(null);
+    render(<TipPage />);
+    await waitFor(() => expect(screen.getByText('All clear.')).toBeInTheDocument());
+  });
+
+  it('shows "All clear." when getRecommendation throws', async () => {
+    mockGetRec.mockRejectedValue(Object.assign(new Error('Network error'), { status: 503 }));
+    render(<TipPage />);
+    await waitFor(() => expect(screen.getByText('All clear.')).toBeInTheDocument());
+  });
+
+  it('"Check again" button re-calls getRecommendation', async () => {
+    mockGetRec.mockResolvedValue(null);
+    render(<TipPage />);
+    await waitFor(() => screen.getByText('Check again'));
+
+    mockGetRec.mockResolvedValue({
+      tip: { id: 'todoist:2', content: 'New tip', source: 'todoist', createdAt: '' },
+    });
+    fireEvent.click(screen.getByText('Check again'));
+    await waitFor(() => expect(mockGetRec).toHaveBeenCalledTimes(2));
+  });
+});
+
+describe('TipPage — tip display', () => {
+  it('renders tip content after loading', async () => {
+    mockGetRec.mockResolvedValue({
+      tip: { id: 'todoist:1', content: 'Write the test', source: 'todoist', createdAt: '' },
+    });
+    render(<TipPage />);
+    await waitFor(() => expect(screen.getByText('Write the test')).toBeInTheDocument());
+  });
+
+  it('shows "hold to act" hint when tip is displayed', async () => {
+    mockGetRec.mockResolvedValue({
+      tip: { id: 'todoist:3', content: 'Do the thing', source: 'todoist', createdAt: '' },
+    });
+    render(<TipPage />);
+    await waitFor(() => expect(screen.getByText(/hold to act/i)).toBeInTheDocument());
+  });
+
+  it('shows "reading you…" while loading', async () => {
+    // Never resolves during this assertion
+    mockGetRec.mockReturnValue(new Promise(() => {}));
+    render(<TipPage />);
+    expect(screen.getByText(/reading you/i)).toBeInTheDocument();
+  });
+});
+
+describe('TipPage — action sheet', () => {
+  // Render with real timers, THEN switch to fake for hold simulation
+  async function renderTipAndHold(id: string, content: string) {
+    mockGetRec.mockResolvedValue({ tip: { id, content, source: 'todoist', createdAt: '' } });
+    render(<TipPage />);
+    // Wait for tip to appear (real timers — no deadlock)
+    await screen.findByText(content);
+    const main = screen.getByRole('main');
+
+    // Switch to fake timers now that the component is fully loaded
+    vi.useFakeTimers();
+    act(() => { main.dispatchEvent(new PointerEvent('pointerdown', { bubbles: true })); });
+    act(() => { vi.advanceTimersByTime(650); });
+    vi.useRealTimers();
+
+    // Wait for action sheet
+    await screen.findByText('Done ✓');
+    return main;
+  }
+
+  it('action sheet appears after a long press (600 ms)', async () => {
+    await renderTipAndHold('tip:lp', 'Hold me');
+    expect(screen.getByText('Done ✓')).toBeInTheDocument();
+  });
+
+  it('action sheet does not appear on short press (<600 ms)', async () => {
+    mockGetRec.mockResolvedValue({ tip: { id: 'tip:sp', content: 'Short press', source: 'todoist', createdAt: '' } });
+    render(<TipPage />);
+    await screen.findByText('Short press');
+    const main = screen.getByRole('main');
+
+    vi.useFakeTimers();
+    act(() => { main.dispatchEvent(new PointerEvent('pointerdown', { bubbles: true })); });
+    act(() => { vi.advanceTimersByTime(200); });
+    act(() => { main.dispatchEvent(new PointerEvent('pointerup', { bubbles: true })); });
+    vi.useRealTimers();
+
+    expect(screen.queryByText('Done ✓')).not.toBeInTheDocument();
+  });
+
+  it('clicking "Done ✓" calls sendFeedback with action=done', async () => {
+    await renderTipAndHold('tip:d', 'Do it');
+    await act(async () => { fireEvent.click(screen.getByText('Done ✓')); });
+    expect(mockSendFeedback).toHaveBeenCalledWith('tip:d', { action: 'done' });
+  });
+
+  it('clicking "Dismiss" calls sendFeedback with action=dismiss', async () => {
+    await renderTipAndHold('tip:dis', 'Dismiss me');
+    await act(async () => { fireEvent.click(screen.getByText('Dismiss')); });
+    expect(mockSendFeedback).toHaveBeenCalledWith('tip:dis', { action: 'dismiss' });
+  });
+
+  it('clicking "Helpful" calls sendFeedback with action=helpful (non-navigating)', async () => {
+    await renderTipAndHold('tip:help', 'Helpful tip');
+    await act(async () => { fireEvent.click(screen.getByText('Helpful')); });
+    expect(mockSendFeedback).toHaveBeenCalledWith('tip:help', { action: 'helpful' });
+  });
+});

apps/web/src/lib/api.ts

@@ -0,0 +1,83 @@
+import type { RecommendResponse, TipFeedback, IntegrationsResponse, UserProfile } from '@oo/shared-types';
+
+const API = '/api';
+
+async function apiFetch<T>(path: string, init?: RequestInit): Promise<T> {
+  const res = await fetch(`${API}${path}`, {
+    credentials: 'include',
+    ...init,
+    headers: {
+      'Content-Type': 'application/json',
+      ...init?.headers,
+    },
+  });
+  if (!res.ok) {
+    const err = await res.json().catch(() => ({ error: res.statusText }));
+    throw Object.assign(new Error(err.error ?? 'API error'), { status: res.status });
+  }
+  if (res.status === 204) return undefined as T;
+  return res.json() as T;
+}
+
+export async function getSession() {
+  return apiFetch<{ user: { id: string; email: string; name?: string; image?: string } | null }>('/auth/session');
+}
+
+export async function getRecommendation(): Promise<RecommendResponse | null> {
+  try {
+    return await apiFetch<RecommendResponse>('/recommend', { method: 'POST' });
+  } catch (e: any) {
+    if (e.status === 204 || e.status === 422) return null;
+    throw e;
+  }
+}
+
+export async function sendFeedback(tipId: string, feedback: TipFeedback) {
+  return apiFetch<{ ok: boolean }>(`/tip/${encodeURIComponent(tipId)}/feedback`, {
+    method: 'POST',
+    body: JSON.stringify(feedback),
+  });
+}
+
+export async function getIntegrations(): Promise<IntegrationsResponse> {
+  return apiFetch<IntegrationsResponse>('/integrations');
+}
+
+export async function disconnectIntegration(provider: string) {
+  return apiFetch<{ ok: boolean }>(`/integrations/${provider}`, { method: 'DELETE' });
+}
+
+export async function getProfile(): Promise<UserProfile> {
+  return apiFetch<UserProfile>('/user/me');
+}
+
+export async function giveConsent() {
+  return apiFetch<{ ok: boolean }>('/user/consent', { method: 'POST' });
+}
+
+export async function deleteAccount() {
+  return apiFetch<{ ok: boolean }>('/user/me', { method: 'DELETE' });
+}
+
+export async function logout() {
+  return apiFetch<{ ok: boolean }>('/auth/logout', { method: 'POST' });
+}
+
+export async function getVapidPublicKey(): Promise<string> {
+  const { key } = await apiFetch<{ key: string }>('/push/vapid-public-key');
+  return key;
+}
+
+export async function subscribePush(subscription: PushSubscriptionJSON) {
+  return apiFetch<{ ok: boolean }>('/push/subscribe', {
+    method: 'POST',
+    body: JSON.stringify(subscription),
+  });
+}
+
+export async function unsubscribePush(endpoint: string) {
+  return apiFetch<{ ok: boolean }>('/push/subscribe', {
+    method: 'DELETE',
+    body: JSON.stringify({ endpoint }),
+  });
+}

apps/web/src/middleware.ts

@@ -0,0 +1,34 @@
+import { NextResponse } from 'next/server';
+import type { NextRequest } from 'next/server';
+
+const PUBLIC = ['/sign-in', '/legal'];
+
+export function middleware(req: NextRequest) {
+  const { pathname } = req.nextUrl;
+  const hasCookie = req.cookies.has('sid');
+
+  // Already on a public page with no session — allow through
+  if (!hasCookie && PUBLIC.some((p) => pathname.startsWith(p))) {
+    return NextResponse.next();
+  }
+
+  // No session — redirect to sign-in
+  if (!hasCookie) {
+    const url = req.nextUrl.clone();
+    url.pathname = '/sign-in';
+    return NextResponse.redirect(url);
+  }
+
+  // Has session but hitting sign-in — send to tip
+  if (hasCookie && pathname.startsWith('/sign-in')) {
+    const url = req.nextUrl.clone();
+    url.pathname = '/tip';
+    return NextResponse.redirect(url);
+  }
+
+  return NextResponse.next();
+}
+
+export const config = {
+  matcher: ['/((?!api|_next/static|_next/image|favicon.ico|icon-.*\\.png|manifest\\.json).*)'],
+};

apps/web/src/test/setup.ts

@@ -0,0 +1 @@
+import '@testing-library/jest-dom';

apps/web/tsconfig.json

@@ -0,0 +1,23 @@
+{
+  "compilerOptions": {
+    "target": "ES2017",
+    "lib": ["dom", "dom.iterable", "esnext"],
+    "allowJs": true,
+    "skipLibCheck": true,
+    "strict": true,
+    "noEmit": true,
+    "esModuleInterop": true,
+    "module": "esnext",
+    "moduleResolution": "bundler",
+    "resolveJsonModule": true,
+    "isolatedModules": true,
+    "jsx": "preserve",
+    "incremental": true,
+    "plugins": [{ "name": "next" }],
+    "paths": {
+      "@/*": ["./src/*"]
+    }
+  },
+  "include": ["next-env.d.ts", "**/*.ts", "**/*.tsx", ".next/types/**/*.ts"],
+  "exclude": ["node_modules"]
+}

apps/web/vitest.config.ts

@@ -0,0 +1,23 @@
+import { defineConfig } from 'vitest/config';
+import react from '@vitejs/plugin-react';
+import { resolve } from 'path';
+
+export default defineConfig({
+  plugins: [react()],
+  test: {
+    globals: true,
+    environment: 'jsdom',
+    setupFiles: ['./src/test/setup.ts'],
+    exclude: ['e2e/**', 'node_modules/**'],
+    coverage: {
+      provider: 'v8',
+      reporter: ['text', 'lcov'],
+      include: ['src/**'],
+    },
+  },
+  resolve: {
+    alias: {
+      '@': resolve(__dirname, 'src'),
+    },
+  },
+});

docs/adr/0006-admin-console-framework.md

@@ -0,0 +1,62 @@
+# ADR-0006: Admin console framework — Next.js 15 + Tremor + shadcn/ui + embed specialist tools
+
+## Status
+Accepted — 2026-04-15
+
+## Context
+M1 ships a bandit-driven recommender, an event bus, and a live feedback loop. Without a cockpit to observe these systems, every model change ships blind. An admin console is needed to:
+
+1. **Observe** — DAU/WAU, tip outcomes, reaction rates, LinUCB arm stats, feature distributions
+2. **Inspect** — per-user identity, consents, integrations, reward history
+3. **Act** — revoke tokens, replay signals, reset a per-user bandit, promote a policy
+4. **Audit** — every operator action is logged
+
+The team is two people. The stack is TypeScript/React/Tailwind. Any framework that forks the stack creates a context-switch tax and a second deployment surface.
+
+## Decision
+
+### App shell — `apps/admin`, Next.js 15, App Router
+
+Same stack as `apps/web`. Reuses `packages/shared-types`, the Auth.js session cookie, and the API rewrite convention. Deployed at `admin.o.alogins.net` behind Caddy, port 3080 in dev.
+
+### UI libraries
+
+| Layer | Library | Reason |
+|-------|---------|--------|
+| Charts / KPI | **Tremor** | Analytics-first React + Tailwind components (KPI cards, time-series, bar lists). Designed for dashboards, not bolted on. |
+| CRUD primitives | **shadcn/ui** | Copy-paste Radix components; forms, dialogs, command palette. No version lock-in — code lives in-repo. |
+| Heavy grids | **TanStack Table v8** | Sortable / paginated / virtualized tables for events, users, tips. |
+| Extra charts | **Recharts** | Fallback where Tremor falls short (histograms, distributions). |
+
+### Link out, don't embed
+
+Specialized MLOps tooling runs as **separate external services** with their own auth, linked from the admin shell — not embedded or reimplemented:
+
+- **MLflow** → `https://o.alogins.net/mlflow` — experiment tracking, model registry, artifact browser; own basic-auth for now; see M3 for SSO consolidation
+- **Airflow** → `https://o.alogins.net/airflow` — batch pipeline orchestration, dataset management; own web-auth for now
+- **Grafana panels** → `/admin/infra` (iframed panels) — infra metrics
+- **Marimo notebooks** → launch-out link from admin
+
+The admin shell links to these services; clicking them opens a new tab. The `/experiments` and `/models` admin pages are hub pages with direct links to the relevant MLflow/Airflow views.
+
+### AuthZ
+
+`profile.role` column on the `users` table (values: `'user'` | `'admin'`). First admin seeded via `ADMIN_SEED_EMAIL` env var at startup. Admin-only gate in Next.js middleware checks the session and the role returned by `GET /api/user/me`. Every write action through the admin API is appended to an `admin_actions` audit log.
+
+### Rejected alternatives
+
+| Option | Rejected because |
+|--------|-----------------|
+| Retool / AppSmith | Admin logic leaves the repo; weak analytics affordances |
+| Streamlit / Gradio | Python-first; splits the frontend stack; thin RBAC |
+| React-admin / Refine.dev | Strong CRUD scaffolding, analytics views feel bolted on |
+| Superset / Metabase as the admin surface | Excellent BI, poor operational writes; plan: adopt Superset in M4 for BI alongside batch pipelines |
+
+## Consequences
+
+- One more Next.js app in the monorepo. Build/dev added to Turborepo.
+- Tremor + shadcn/ui are added as dependencies. shadcn components are copied into `apps/admin/src/components/ui/` — no runtime version coupling.
+- MLflow (`o.alogins.net/mlflow*` → port 5000) and Airflow (`o.alogins.net/airflow*` → port 8080) are path-based routes in the existing `o.alogins.net` Caddy block, started via `docker compose --profile mlops up`.
+- Each service manages its own auth (MLflow: built-in basic-auth; Airflow: built-in web UI auth). M3 will consolidate both behind the shared OIDC provider.
+- The `NEXT_PUBLIC_MLFLOW_URL` and `NEXT_PUBLIC_AIRFLOW_URL` build args in `Dockerfile.admin` default to the production URLs; override for dev builds.
+- `admin_actions` audit log grows unboundedly — needs a retention policy before M4.

docs/adr/0007-egreedy-v1-active-policy.md

@@ -0,0 +1,47 @@
+# ADR-0007: ε-greedy v1 as the active recommendation policy
+
+## Status
+Accepted — 2026-04-16
+
+## Context
+
+M1 shipped LinUCB (d=5, α=1.0) as the first learned policy via `ml/serving /score`. After the M1 admin console landed, we ran an offline simulation to compare LinUCB against a new ε-greedy ridge-regression policy before deciding which to keep live.
+
+**ε-greedy v1 design:**
+- Ridge regression estimator, θ updated online (equivalent to LinUCB without the UCB bonus).
+- d=7 feature vector: base 5 (is\_overdue, task\_age\_days, priority, hour\_of\_day, bias) + sin/cos encoding of day\_of\_week.
+- ε=0.10 random exploration; 90% argmax(θ·x).
+- Separate per-user state files (`{user}_egreedy.json`), independent of LinUCB state.
+
+**Simulation setup (rule judge, seed=42):**
+- 5 synthetic personas × 20 rounds × 8 tasks/round = 100 judgments per policy.
+- Reward inferred from dwell-time (same `inferReward` logic as production): dismiss=−1, snooze=+0.1, done<15 s=−0.3, done 15 s–2 min=+1.0, done 2–10 min=+0.6, done>10 min=+0.3.
+- Both policies started from blank state (no warm-up).
+
+**Results:**
+
+| Policy | Total reward | Mean reward/pull | Pulls |
+|--------|-------------|-----------------|-------|
+| egreedy-v1 | −54.80 | −0.548 | 100 |
+| linucb-v1  | −60.60 | −0.606 | 100 |
+
+Winner: **egreedy-v1** (+10.7% mean reward).
+
+Both policies produce negative mean rewards under the dwell-time model — expected: most simulated users don't act in the 15s–2min magic zone on cold models. The gap widens from round 8 onward, consistent with LinUCB's UCB exploration bonus over-favouring high-uncertainty dimensions (is\_overdue, task\_age\_days) regardless of persona fit.
+
+## Decision
+
+Promote **egreedy-v1** to the active serving policy:
+- `POST /recommend` calls `/score/egreedy` instead of `/score`.
+- Feedback loop calls `/reward/egreedy`.
+- LinUCB (`/score`, `/reward`) remains deployed in `ml/serving` as a shadow-eligible fallback.
+
+The simulation does not replace online A/B testing; it is evidence that egreedy-v1 is worth promoting before collecting real-user signal. A future milestone will run live A/B once we have enough daily active users for statistical power.
+
+## Consequences
+
+- Recommendation calls and reward updates now hit the egreedy endpoints only.
+- LinUCB state is preserved on disk; re-activation is a one-line change.
+- `tip_scores.policy` will log `egreedy-v1` for new serves; historical rows remain `linucb-v1` or `random`.
+- The dwell-time reward model (`inferReward`) is now the canonical feedback signal for both online updates and simulation. Explicit helpful/not\_helpful signals are removed.
+- Next evaluation gate: once ≥500 real tips served with egreedy-v1, compare reward distribution to the LinUCB historical baseline in the admin Reward Analytics page before deciding on next policy iteration.

docs/adr/0008-litellm-ai-gateway.md

@@ -0,0 +1,41 @@
+# ADR-0008 — LiteLLM as AI gateway; model aliases decouple code from model names
+
+**Status:** Accepted  
+**Date:** 2026-04-17  
+**Milestone:** M2
+
+## Context
+
+M2 requires LLM inference for tip generation (`ml/serving POST /generate`). We need a way to:
+- Run locally during development without cloud API keys.
+- Switch models (qwen2.5 → llama3.2, or cloud fallback) without touching application code.
+- Share the LLM infrastructure with other local services on Agap.
+
+## Decision
+
+Route all LLM calls through **LiteLLM** (`http://localhost:4000` in dev, `llm.alogins.net` in prod) backed by **Ollama** for local inference.
+
+Application code references model aliases — never bare model names:
+
+| Alias | Default model | Used by |
+|-------|--------------|---------|
+| `tip-generator` | `qwen2.5:7b` | `ml/serving POST /generate` |
+| `embedder` | `nomic-embed-text` | task clustering, dedup (M4) |
+| `judge` | `claude-haiku-4-5` | offline simulation only |
+
+Config is in `infra/litellm/litellm_config.yaml`. Swapping a model = one YAML change, zero code change.
+
+`ml/serving` reads `LITELLM_URL` and `LITELLM_MASTER_KEY` from env. TypeScript services never call LLM endpoints directly — all inference flows through `ml/serving`.
+
+## Consequences
+
+- **Local dev:** `docker compose --profile ai up` starts Ollama + LiteLLM. First run pulls models (~4 GB for qwen2.5:7b).
+- **Prod:** both are shared Agap services; set `LITELLM_URL=http://llm.alogins.net` in `.env.local`.
+- **Offline sim:** `judge` alias points at `claude-haiku-4-5` (cloud) — requires `ANTHROPIC_API_KEY`; simulation is opt-in.
+- **Vendor lock-in:** none at the code level. LiteLLM translates the OpenAI-compatible API to whatever backend.
+- **Observability:** LiteLLM logs all requests; `tip_scores.llm_model` + `tip_scores.prompt_version` track which model + prompt generated each served tip.
+
+## Alternatives considered
+
+- **Call Ollama directly:** cheaper in latency, but ties code to Ollama's API format and makes cloud fallback a code change.
+- **Call Anthropic directly from TS:** violates the rule that TS services never hold model names (CLAUDE.md prime directive 3).

docs/adr/0009-signal-normalization.md

@@ -0,0 +1,53 @@
+# ADR-0009 — Signal normalization strategy
+
+**Status:** Accepted  
+**Date:** 2026-04-18  
+**Issue:** #78
+
+## Context
+
+The recommender was hard-wired to Todoist: task fetch, cache, and feature extraction lived inside `recommender.ts` with no abstraction boundary. Adding Google Calendar, Apple Health, or manual input sources would have required forking the pipeline per source.
+
+## Decision
+
+Introduce two abstractions in `packages/shared-types`:
+
+```typescript
+interface Signal {
+  id: string;
+  source: string;
+  kind: 'task' | 'event' | 'habit' | 'insight';
+  content: string;
+  metadata: Record<string, unknown>;   // raw source fields, not used by bandit
+  features: Record<string, number | boolean>; // bandit-ready features
+  timestamp: string;
+}
+
+interface SignalSource {
+  readonly id: string;
+  fetchSignals(userId: string): Promise<Signal[]>;
+  act?(userId: string, signalId: string, action: string): Promise<void>;
+}
+```
+
+`SignalAggregator` calls all registered sources in parallel, isolating failures per source.  
+`TodoistSignalSource` moves all Todoist-specific logic (fetch, 401 handling, cache, bus events) out of the recommender route.  
+The recommender maps `Signal[]` → `TipCandidate[]` via a thin adapter and registers action dispatch through the aggregator.
+
+## Consequences
+
+**Good:**
+- Adding a new signal source is a single `aggregator.register(new MySource())` call.
+- `TipCandidate.features` is now `Record<string, number | boolean>`, matching `Signal.features`. Sources control their own feature names; the bandit serialises them as-is.
+- Source failures are isolated: a broken Google Calendar connector does not prevent Todoist signals from reaching the bandit.
+- `act()` on the aggregator routes actions back to the owning source (e.g. marking a Todoist task done), replacing ad-hoc source-specific logic in the feedback handler.
+
+**Trade-offs:**
+- Feature names are no longer compile-time typed. Convention: sources document their feature keys in their class JSDoc. The Python bandit already treated features as an opaque dict.
+- Each source is responsible for its own token lookup (DB access injected via module-level `db`). This is acceptable in a modular monolith; extract to a token vault interface if sources move to separate processes.
+
+## Alternatives considered
+
+**Typed feature schema per source kind** — rejected: would require union types across all sources and a discriminant on every consumer. The bandit doesn't benefit from TypeScript types at runtime.
+
+**Aggregator holds tokens, passes to sources** — rejected: leaks auth concerns into the aggregator. Sources know their own auth requirements.

docs/adr/0010-nats-bridge-and-background-sync.md

@@ -0,0 +1,59 @@
+# ADR-0010: NATS bridge over the in-process bus, and Todoist background sync
+
+## Status
+Accepted — 2026-04-18
+
+## Context
+ADR-0005 set protobuf + JetStream as the long-term event substrate. M1 shipped
+an in-process `EventEmitter`-based bus with the right subjects (`signals.*`,
+`feedback.*`) so the swap would be mechanical.
+
+Two pressures pulled forward:
+1. **ml/serving** and future feature pipelines need to consume signals across
+   process boundaries — the in-proc emitter cannot do that.
+2. **Todoist** signals were only fetched on the recommend path. Cold-cache hits
+   added latency and a single 401/429 stalled the request that triggered it.
+
+## Decision
+
+### 1. Bridge, do not replace
+The `Bus` stays the producer. A new `Bus.onPublish(hook)` hook fires on every
+`publish`. When `NATS_URL` is set, `connectNats()` registers a hook that
+JSON-encodes the payload and `js.publish(subject, data)`s it to JetStream.
+
+- Streams are created on startup and are idempotent: `signals` (`signals.>`,
+  7-day file storage, 500k msgs) and `feedback` (`feedback.>`, 30-day, 200k).
+- JetStream publish errors are caught inside the hook so an unhealthy broker
+  cannot crash the in-process publisher or its subscribers.
+- When `NATS_URL` is unset, `connectNats` is a no-op — local dev keeps working.
+
+This preserves the existing `bus.subscribe()` contract for in-process consumers
+(reward inference, ring-buffer tail for the admin event viewer) while making
+events durably consumable across processes.
+
+### 2. Schedule Todoist, keep on-demand as the SLA fallback
+A 15-minute background scheduler (`TODOIST_SYNC_INTERVAL_MS`) walks every
+user with `tokenStatus = 'active'` and calls `todoistSource.fetchSignals(uid)`,
+which in turn emits `signals.task.synced`. The per-request fetch in
+`recommender` stays — when the cache is colder than 30 s it still goes to
+Todoist inline, so freshness on the user's first hit of the day is unchanged.
+
+Per-user failures are isolated with `Promise.allSettled`; one expired token
+cannot stop the rest of the cohort. The whole tick is wrapped so a transient
+SQLite error logs and skips, never crashes the API.
+
+## Consequences
+- ml/serving (and any future Python consumer) can durably tail
+  `signals.task.synced`, `signals.tip.served`, `signals.tip.feedback` from
+  JetStream without coupling to the API process.
+- Local dev still runs without NATS; the bridge is opt-in via env.
+- Wire format is JSON today (envelope per ADR-0005 not enforced yet) — see
+  Open follow-ups.
+
+## Open follow-ups
+- A ml/serving JetStream consumer for the feature pipeline (today nothing
+  reads from JetStream — the API only writes).
+- Move the wire payload to the protobuf envelope from ADR-0005 once the
+  schema-registry CI gate (#54) lands.
+- Graceful shutdown of the scheduler timer on `SIGTERM`.
+- Per-publish failure metrics exported to the admin health view.

docs/architecture/overview.md

@@ -15,7 +15,7 @@
 | `auth` | TS | OAuth (Google; Apple in M1), sessions, JWT | identities, sessions | Node monolith |
 | `profile` | TS | user profile, preferences, consents | profiles | Node monolith |
 | `integrations` | TS | third-party connectors, token vault, signal fetch | credentials, cursors | Node monolith |
-| `events` | TS | event-bus abstraction + durable log (M1) | signal store | Node monolith (in-proc emitter) |
+| `events` | TS | event-bus abstraction + durable log | signal store | Node monolith (in-proc emitter, bridges to NATS JetStream when `NATS_URL` set) |
 | `recommender` | TS | orchestration: candidates → policy → tip; feedback sink | tip history | Node monolith |
 | `notifier` | TS | push/email delivery, quiet hours, dedupe | delivery log | Node monolith (web push in M1) |
 | `ml/serving` | Python | online scoring for policies/models | — (stateless) | **separate process** |
@@ -46,21 +46,44 @@ User reactions (done / snooze / dismiss) are events too. They close the loop as
 - **Protobuf** for event schemas with a schema registry (ADR-0005) — train/serve parity depends on this.
 - **OpenAPI** for HTTP; TS client auto-generated; Python pydantic hand-written while consumers are few.
 - **Feast** for feature store when we get there; homegrown adapter until then (Phase 1 seam).
-- **MLflow** for model registry; artifacts in MinIO/S3.
+- **MLflow** for model registry and experiment tracking; deployed at `o.alogins.net/mlflow`.
+- **Airflow** for batch pipelines; deployed at `o.alogins.net/airflow`.
 - **Auth.js** embedded behind an OIDC-shaped boundary (ADR-0004). Swap to a standalone OIDC provider when mobile ships.
 - **k3s** as the first step beyond docker-compose — no "compose → full k8s" cliff.
 
-## Decision flow for a new tip
+## AI stack
+
+All LLM inference routes through **LiteLLM** (`llm.alogins.net`) backed by **Ollama** (local, `localhost:11434`). This means:
+- Model aliases (`tip-generator`, `embedder`, `judge`) decouple code from model names.
+- Swapping qwen2.5 → llama3.2 = one-line config change in LiteLLM, zero code change in oO.
+- Cloud fallback (Anthropic) is opt-in and gated behind `ANTHROPIC_API_KEY` — used only in offline simulation.
+
+**OpenWebUI** (`ai.alogins.net`) is the human-facing interface for prompt iteration and model testing during development.
+
+## Decision flow for a new tip (Phase 2 target)
 
 ```
-client ─► gateway ─► recommender
-                       │
-                       ├─► candidates:   integrations.fetchCandidates(user)  + advice.library
-                       ├─► context:      FeatureAssembler(user, request)
-                       ├─► policy:       PolicyRegistry.get(policyName).pick(candidates, context)
-                       ├─► shadows:      run shadow policies in parallel, log their picks
-                       └─► persist:      TipInstance{context_snapshot, policy, tip}
-                       ◄─  tip
+client ─► gateway ─► recommender (TS)
+                          │
+                          ▼
+                     ml/serving (Python)
+                          │
+                          ├─► context:    ml/features/context.py
+                          │               (tasks + reactions + time patterns → prompt)
+                          │
+                          ├─► generate:   LiteLLM → Ollama
+                          │               → N TipCandidates {content, kind, model, prompt_version}
+                          │
+                          ├─► score:      bandit policy scores each candidate
+                          │
+                          ├─► shadows:    shadow policies log picks without serving
+                          │
+                          └─► persist:    tip_scores {candidate, policy, features, latency}
+                          ◄─  best TipCandidate
 ```
 
-Feedback travels back the same path: `POST /feedback → events.emit(feedback.reaction)` → pipelines consume → bandit/model updated on next retrain.
+**Phase 1 (shipped M1):** candidates come from Todoist task list, no LLM. The bandit scores tasks directly.
+
+**Phase 2 (shipped M2):** LLM candidates are generated in parallel with Todoist fetch. Both pools are merged, scored by the bandit, and the winner served. `tip_scores` tracks `prompt_version`, `llm_model`, and `tip_kind` for every row.
+
+Feedback: `POST /feedback → events.emit(reaction)` → online bandit update + `prompt_version` tracked for A/B analysis.

infra/ci/ci.yml

@@ -0,0 +1,63 @@
+name: CI
+
+on:
+  push:
+    branches: [main]
+  pull_request:
+    branches: [main]
+
+jobs:
+  type-check-and-lint:
+    name: Type-check & lint
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: pnpm/action-setup@v4
+        with:
+          version: 10
+      - uses: actions/setup-node@v4
+        with:
+          node-version: 22
+          cache: pnpm
+      - run: pnpm install --frozen-lockfile
+      - run: pnpm build --filter=@oo/shared-types
+      - run: pnpm type-check
+
+  test:
+    name: Unit tests
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: pnpm/action-setup@v4
+        with:
+          version: 10
+      - uses: actions/setup-node@v4
+        with:
+          node-version: 22
+          cache: pnpm
+      - run: pnpm install --frozen-lockfile
+      - run: pnpm build --filter=@oo/shared-types
+      - run: pnpm test
+
+  ml-lint:
+    name: Python lint
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: actions/setup-python@v5
+        with:
+          python-version: '3.12'
+      - run: pip install ruff
+      - run: ruff check ml/serving/
+
+  ml-test:
+    name: Python tests
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: actions/setup-python@v5
+        with:
+          python-version: '3.12'
+      - run: python -m venv ml/serving/.venv
+      - run: ml/serving/.venv/bin/pip install -r ml/serving/requirements-dev.txt
+      - run: ml/serving/.venv/bin/python -m pytest ml/serving/tests/ -v

infra/docker/Dockerfile.admin

@@ -0,0 +1,32 @@
+FROM node:22-alpine AS base
+RUN npm install -g pnpm
+
+FROM base AS deps
+WORKDIR /app
+COPY package.json pnpm-workspace.yaml pnpm-lock.yaml* ./
+COPY packages/shared-types/package.json ./packages/shared-types/
+COPY apps/admin/package.json ./apps/admin/
+RUN pnpm install --frozen-lockfile
+
+FROM base AS builder
+WORKDIR /app
+COPY --from=deps /app/node_modules ./node_modules
+COPY --from=deps /app/packages/shared-types/node_modules ./packages/shared-types/node_modules
+COPY --from=deps /app/apps/admin/node_modules ./apps/admin/node_modules
+COPY tsconfig.base.json ./
+COPY packages/shared-types ./packages/shared-types
+COPY apps/admin ./apps/admin
+RUN pnpm --filter @oo/shared-types build
+ARG NEXT_PUBLIC_MLFLOW_URL=/mlflow
+ARG NEXT_PUBLIC_AIRFLOW_URL=/airflow
+ENV NEXT_TELEMETRY_DISABLED=1 \
+    NEXT_PUBLIC_MLFLOW_URL=$NEXT_PUBLIC_MLFLOW_URL \
+    NEXT_PUBLIC_AIRFLOW_URL=$NEXT_PUBLIC_AIRFLOW_URL
+RUN pnpm --filter @oo/admin build
+
+FROM node:22-alpine AS runner
+ENV NODE_ENV=production NEXT_TELEMETRY_DISABLED=1 PORT=3080
+WORKDIR /app
+COPY --from=builder /app/apps/admin/.next/standalone ./
+COPY --from=builder /app/apps/admin/.next/static ./apps/admin/.next/static
+CMD ["node", "apps/admin/server.js"]

infra/docker/Dockerfile.api

@@ -0,0 +1,32 @@
+FROM node:22-alpine AS base
+RUN npm install -g pnpm
+
+FROM base AS deps
+WORKDIR /app
+COPY package.json pnpm-workspace.yaml pnpm-lock.yaml* ./
+COPY packages/shared-types/package.json ./packages/shared-types/
+COPY services/api/package.json ./services/api/
+RUN pnpm install --frozen-lockfile
+
+FROM base AS builder
+WORKDIR /app
+COPY --from=deps /app/node_modules ./node_modules
+COPY --from=deps /app/packages/shared-types/node_modules ./packages/shared-types/node_modules
+COPY --from=deps /app/services/api/node_modules ./services/api/node_modules
+COPY tsconfig.base.json ./
+COPY packages/shared-types ./packages/shared-types
+COPY services/api ./services/api
+RUN pnpm --filter @oo/shared-types build
+RUN pnpm --filter @oo/api build
+
+FROM node:22-alpine AS runner
+WORKDIR /app
+RUN npm install -g pnpm
+COPY package.json pnpm-workspace.yaml pnpm-lock.yaml* ./
+COPY packages/shared-types/package.json ./packages/shared-types/
+COPY services/api/package.json ./services/api/
+RUN pnpm install --prod --frozen-lockfile
+COPY --from=builder /app/packages/shared-types/dist ./packages/shared-types/dist
+COPY --from=builder /app/services/api/dist ./services/api/dist
+WORKDIR /app/services/api
+CMD ["node", "dist/index.js"]

infra/docker/Dockerfile.ml

@@ -0,0 +1,6 @@
+FROM python:3.12-slim
+WORKDIR /app
+COPY ml/serving/requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+COPY ml/serving/main.py .
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]

infra/docker/Dockerfile.web

@@ -0,0 +1,29 @@
+FROM node:22-alpine AS base
+RUN npm install -g pnpm
+
+FROM base AS deps
+WORKDIR /app
+COPY package.json pnpm-workspace.yaml pnpm-lock.yaml* ./
+COPY packages/shared-types/package.json ./packages/shared-types/
+COPY apps/web/package.json ./apps/web/
+RUN pnpm install --frozen-lockfile
+
+FROM base AS builder
+WORKDIR /app
+COPY --from=deps /app/node_modules ./node_modules
+COPY --from=deps /app/packages/shared-types/node_modules ./packages/shared-types/node_modules
+COPY --from=deps /app/apps/web/node_modules ./apps/web/node_modules
+COPY tsconfig.base.json ./
+COPY packages/shared-types ./packages/shared-types
+COPY apps/web ./apps/web
+RUN pnpm --filter @oo/shared-types build
+ENV NEXT_TELEMETRY_DISABLED=1
+RUN pnpm --filter @oo/web build
+
+FROM node:22-alpine AS runner
+ENV NODE_ENV=production NEXT_TELEMETRY_DISABLED=1
+WORKDIR /app
+COPY --from=builder /app/apps/web/.next/standalone ./
+COPY --from=builder /app/apps/web/.next/static ./apps/web/.next/static
+COPY --from=builder /app/apps/web/public ./apps/web/public
+CMD ["node", "apps/web/server.js"]

infra/docker/docker-compose.yml

@@ -0,0 +1,206 @@
+name: oo
+
+services:
+  # ── core profile ──────────────────────────────────────────────────────────
+
+  api:
+    build:
+      context: ../..
+      dockerfile: infra/docker/Dockerfile.api
+    profiles: [core, full]
+    env_file: ../../.env.local
+    environment:
+      NODE_ENV: production
+    volumes:
+      - /mnt/ssd/dbs/oo:/mnt/ssd/dbs/oo
+    ports:
+      - "127.0.0.1:3078:3078"
+    healthcheck:
+      test: ["CMD", "wget", "--spider", "-q", "http://localhost:3078/health"]
+      interval: 10s
+      timeout: 5s
+      retries: 5
+
+  web:
+    build:
+      context: ../..
+      dockerfile: infra/docker/Dockerfile.web
+    profiles: [core, full]
+    env_file: ../../.env.local
+    environment:
+      NODE_ENV: production
+      PORT: "3079"
+      HOSTNAME: "0.0.0.0"
+      NEXT_PUBLIC_API_URL: ""   # Caddy routes /api/* directly to the API in prod
+    ports:
+      - "127.0.0.1:3079:3079"
+    depends_on:
+      api:
+        condition: service_healthy
+
+  admin:
+    build:
+      context: ../..
+      dockerfile: infra/docker/Dockerfile.admin
+    profiles: [core, full]
+    env_file: ../../.env.local
+    environment:
+      NODE_ENV: production
+      PORT: "3080"
+      HOSTNAME: "0.0.0.0"
+      NEXT_PUBLIC_API_URL: ""
+      INTERNAL_API_URL: "http://api:3078"
+    ports:
+      - "127.0.0.1:3080:3080"
+    depends_on:
+      api:
+        condition: service_healthy
+
+  # ── full profile ──────────────────────────────────────────────────────────
+
+  ml-serving:
+    build:
+      context: ../..
+      dockerfile: infra/docker/Dockerfile.ml
+    profiles: [full]
+    env_file: ../../.env.local
+    environment:
+      LITELLM_URL: ${LITELLM_URL:-http://host.docker.internal:4000}
+      OLLAMA_URL: ${OLLAMA_URL:-http://host.docker.internal:11434}
+    extra_hosts:
+      - "host.docker.internal:host-gateway"
+    ports:
+      - "127.0.0.1:8000:8000"
+    healthcheck:
+      test: ["CMD", "python", "-c", "import urllib.request,sys; sys.exit(0 if urllib.request.urlopen('http://localhost:8000/health',timeout=3).status==200 else 1)"]
+      interval: 10s
+      timeout: 5s
+      retries: 5
+
+  # ── mlops profile — MLflow + Airflow ──────────────────────────────────────
+  # Start: docker compose --profile mlops up
+  # MLflow UI:  http://localhost:5000       or https://o.alogins.net/mlflow  (admin / password — change via basic_auth.ini)
+  # Airflow UI: http://localhost:8080/airflow  or https://o.alogins.net/airflow  (admin / AIRFLOW_ADMIN_PASSWORD)
+  # Caddy routes /mlflow* and /airflow* inside the o.alogins.net block
+
+  airflow-db:
+    image: postgres:16-alpine
+    profiles: [mlops]
+    environment:
+      POSTGRES_DB: airflow
+      POSTGRES_USER: airflow
+      POSTGRES_PASSWORD: ${AIRFLOW_DB_PASSWORD:-airflow}
+    volumes:
+      - /mnt/ssd/dbs/oo/airflow-db:/var/lib/postgresql/data
+    healthcheck:
+      test: ["CMD-SHELL", "pg_isready -U airflow"]
+      interval: 10s
+      timeout: 5s
+      retries: 5
+
+  airflow-init:
+    image: apache/airflow:2.9.3
+    profiles: [mlops]
+    entrypoint: /bin/bash
+    command:
+      - -c
+      - |
+        airflow db migrate
+        airflow users create \
+          --username admin \
+          --firstname Admin \
+          --lastname User \
+          --role Admin \
+          --email admin@oo.local \
+          --password "$${AIRFLOW_ADMIN_PASSWORD:-admin}"
+    environment:
+      AIRFLOW__DATABASE__SQL_ALCHEMY_CONN: postgresql+psycopg2://airflow:${AIRFLOW_DB_PASSWORD:-airflow}@airflow-db/airflow
+      AIRFLOW__CORE__EXECUTOR: LocalExecutor
+      AIRFLOW__WEBSERVER__SECRET_KEY: ${AIRFLOW_SECRET_KEY:-change-me-in-prod}
+      AIRFLOW__WEBSERVER__BASE_URL: ${AIRFLOW_BASE_URL:-https://o.alogins.net/airflow}
+    depends_on:
+      airflow-db:
+        condition: service_healthy
+    restart: "no"
+
+  airflow-webserver:
+    image: apache/airflow:2.9.3
+    profiles: [mlops]
+    command: webserver
+    environment:
+      AIRFLOW__DATABASE__SQL_ALCHEMY_CONN: postgresql+psycopg2://airflow:${AIRFLOW_DB_PASSWORD:-airflow}@airflow-db/airflow
+      AIRFLOW__CORE__EXECUTOR: LocalExecutor
+      AIRFLOW__WEBSERVER__SECRET_KEY: ${AIRFLOW_SECRET_KEY:-change-me-in-prod}
+      AIRFLOW__CORE__FERNET_KEY: ${AIRFLOW_FERNET_KEY:-}
+      AIRFLOW__WEBSERVER__BASE_URL: ${AIRFLOW_BASE_URL:-https://o.alogins.net/airflow}
+    volumes:
+      - ../../ml/pipelines:/opt/airflow/dags:ro
+    ports:
+      - "127.0.0.1:8080:8080"
+    depends_on:
+      airflow-init:
+        condition: service_completed_successfully
+    healthcheck:
+      test: ["CMD", "curl", "--fail", "http://localhost:8080/health"]
+      interval: 30s
+      timeout: 10s
+      retries: 5
+      start_period: 60s
+
+  airflow-scheduler:
+    image: apache/airflow:2.9.3
+    profiles: [mlops]
+    command: scheduler
+    environment:
+      AIRFLOW__DATABASE__SQL_ALCHEMY_CONN: postgresql+psycopg2://airflow:${AIRFLOW_DB_PASSWORD:-airflow}@airflow-db/airflow
+      AIRFLOW__CORE__EXECUTOR: LocalExecutor
+      AIRFLOW__CORE__FERNET_KEY: ${AIRFLOW_FERNET_KEY:-}
+    volumes:
+      - ../../ml/pipelines:/opt/airflow/dags:ro
+    depends_on:
+      airflow-init:
+        condition: service_completed_successfully
+
+  # ── events profile — NATS JetStream ─────────────────────────────────────
+  # Start: docker compose --profile events up
+  # NATS monitoring: http://localhost:8222
+  # Enable in the API by setting NATS_URL=nats://nats:4222 in .env.local
+
+  nats:
+    image: nats:2.10-alpine
+    profiles: [events, full]
+    command: ["-js", "-sd", "/data", "-m", "8222"]
+    volumes:
+      - /mnt/ssd/dbs/oo/nats:/data
+    ports:
+      - "127.0.0.1:4222:4222"   # client connections
+      - "127.0.0.1:8222:8222"   # HTTP monitoring
+    healthcheck:
+      test: ["CMD", "wget", "--spider", "-q", "http://localhost:8222/healthz"]
+      interval: 10s
+      timeout: 5s
+      retries: 5
+
+  mlflow:
+    image: ghcr.io/mlflow/mlflow:v2.14.3
+    profiles: [mlops]
+    command: >
+      mlflow server
+      --backend-store-uri sqlite:////mlflow/mlflow.db
+      --default-artifact-root /mlflow/artifacts
+      --host 0.0.0.0
+      --port 5000
+      --app-name basic-auth
+      --static-prefix /mlflow
+    environment:
+      MLFLOW_AUTH_CONFIG_PATH: /mlflow/basic_auth.ini
+    volumes:
+      - /mnt/ssd/dbs/oo/mlflow:/mlflow
+      - ../../infra/mlflow/basic_auth.ini:/mlflow/basic_auth.ini:ro
+    ports:
+      - "127.0.0.1:5000:5000"
+    healthcheck:
+      test: ["CMD", "python", "-c", "import urllib.request,sys; sys.exit(0 if urllib.request.urlopen('http://localhost:5000/health',timeout=3).status==200 else 1)"]
+      interval: 10s
+      timeout: 5s
+      retries: 5

infra/mlflow/basic_auth.ini

@@ -0,0 +1,6 @@
+[mlflow]
+default_permission = NO_PERMISSIONS
+database_uri = sqlite:////mlflow/basic_auth.db
+admin_username = admin
+# Change this before deploying — the admin can reset other users' passwords via the MLflow UI
+admin_password = password

ml/README.md

@@ -4,8 +4,8 @@ Python. Owns models, features, training, online scoring.
 
 | Dir | Role | Phase |
 |---|---|---|
-| `serving/` | FastAPI online scorer (`/score`), called by `recommender` | 1 |
-| `features/` | feature definitions + store adapter (Feast later) | 1 |
+| `serving/` | FastAPI online scorer (`/score`, `/generate`) + LiteLLM gateway, called by `recommender` | 1–2 |
+| `features/` | context assembler (`context.py`): signals → `PromptContext`; Feast adapter later | 2 |
 | `pipelines/` | batch feature + training DAGs (Prefect/Airflow) | 4 |
 | `registry/` | MLflow-backed model registry integration | 4 |
 | `experiments/` | A/B assignment + multi-armed bandit policies | 4 |

ml/experiments/sim/llm_judge.py

@@ -0,0 +1,204 @@
+"""
+LLM-based user reaction judge.
+
+Uses Claude Haiku when ANTHROPIC_API_KEY is set; falls back to a
+deterministic persona-based rule when it is not.
+"""
+
+from __future__ import annotations
+
+import os
+import random
+
+from personas import Persona
+
+ACTIONS = ["done", "snooze", "dismiss"]
+
+# Reward is NOT a fixed map anymore — it depends on action + simulated dwell time.
+# Use infer_reward() to compute the final reward after simulating dwell.
+_BASE_REWARDS: dict[str, float] = {
+    "done": 1.0,   # placeholder; real reward computed from dwell
+    "snooze": 0.1,
+    "dismiss": -1.0,
+}
+
+
+def infer_reward(action: str, dwell_ms: int) -> float:
+    """Mirror of production inferReward() in recommender.ts."""
+    if action == "dismiss":
+        return -1.0
+    if action == "snooze":
+        return 0.1
+    # done — dwell-based
+    if dwell_ms < 15_000:
+        return -0.3   # stale / reflex done
+    if dwell_ms < 120_000:
+        return 1.0    # magic zone
+    if dwell_ms < 600_000:
+        return 0.6    # good
+    return 0.3        # eventually done
+
+_HOUR_PERIODS = {
+    (5, 10): "morning",
+    (10, 14): "midday",
+    (14, 18): "afternoon",
+    (18, 22): "evening",
+}
+
+
+def _period(hour: int) -> str:
+    for (lo, hi), name in _HOUR_PERIODS.items():
+        if lo <= hour < hi:
+            return name
+    return "night"
+
+
+# ── Deterministic judge ────────────────────────────────────────────────────
+
+def _engagement_score(persona: Persona, tip: dict, hour: int) -> float:
+    """0–1 score of how well this tip fits this persona right now."""
+    features = tip.get("features", {})
+    priority = features.get("priority", 1)
+    is_overdue = features.get("is_overdue", False)
+
+    p = 0.35
+    priority_norm = (priority - 1) / 3.0
+    p += (priority_norm - 0.5) * persona.prefers_high_priority * 0.4
+    if is_overdue:
+        p += (persona.prefers_overdue - 0.5) * 0.3
+
+    is_morning = 5 <= hour < 10
+    is_evening = 18 <= hour < 22
+    if persona.morning_active and is_morning:
+        p += 0.15
+    elif persona.evening_active and is_evening:
+        p += 0.15
+    elif persona.morning_active and not is_morning and not is_evening:
+        p -= 0.10
+    elif persona.evening_active and not is_evening and not is_morning:
+        p -= 0.10
+
+    return max(0.05, min(0.90, p))
+
+
+def _simulate_dwell_ms(engagement: float, rng: random.Random) -> int:
+    """
+    Simulate how many milliseconds the user takes to act on a tip.
+
+    High engagement → quick action (magic zone, 15s–2min).
+    Medium engagement → slower (2–10min).
+    Low engagement → very slow (>10min) — tip helped eventually but not 'magic'.
+    For snooze/dismiss the dwell doesn't affect reward; return a short value.
+    """
+    if engagement >= 0.70:
+        # Strong match — magic zone: 15s–90s
+        return rng.randint(15_000, 90_000)
+    elif engagement >= 0.50:
+        # Moderate match — good zone: 2–8min
+        return rng.randint(120_000, 480_000)
+    else:
+        # Weak match but still done — eventually: 10–30min
+        return rng.randint(600_000, 1_800_000)
+
+
+def _rule_judge(persona: Persona, tip: dict, hour: int, rng: random.Random) -> tuple[str, int]:
+    """Return (action, dwell_ms) based on persona preferences and task features."""
+    engagement = _engagement_score(persona, tip, hour)
+
+    r = rng.random()
+    if r < engagement * 0.55:
+        # done — dwell depends on engagement
+        dwell = _simulate_dwell_ms(engagement, rng)
+        return "done", dwell
+    elif r < engagement:
+        return "snooze", rng.randint(3_000, 20_000)
+    else:
+        return "dismiss", rng.randint(1_000, 5_000)
+
+
+# ── LLM judge ─────────────────────────────────────────────────────────────
+
+_anthropic_client = None
+
+def _get_client():
+    global _anthropic_client
+    if _anthropic_client is None:
+        try:
+            import anthropic  # type: ignore
+            key = os.environ.get("ANTHROPIC_API_KEY", "")
+            if key:
+                _anthropic_client = anthropic.Anthropic(api_key=key)
+        except ImportError:
+            pass
+    return _anthropic_client
+
+
+def _llm_judge(
+    persona: Persona, tip: dict, hour: int, day_of_week: int, rng: random.Random,
+) -> tuple[str, int]:
+    client = _get_client()
+    if client is None:
+        return _rule_judge(persona, tip, hour, rng)
+
+    features = tip.get("features", {})
+    priority = features.get("priority", 1)
+    is_overdue = features.get("is_overdue", False)
+    age_days = features.get("task_age_days", 0)
+
+    priority_label = {1: "low", 2: "normal", 3: "high", 4: "urgent"}.get(priority, "normal")
+    overdue_str = f", overdue by {age_days:.0f} day(s)" if is_overdue else ""
+    days = ["Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"]
+    day_str = days[day_of_week % 7]
+
+    prompt = (
+        f"You are simulating how a specific user reacts to a task recommendation app.\n\n"
+        f"User persona: {persona.name}\n"
+        f"Persona: {persona.description}\n\n"
+        f'Recommended task: "{tip.get("content", "Unknown task")}"\n'
+        f"Task: priority={priority_label}{overdue_str}\n"
+        f"Current time: {_period(hour)} ({hour}:00, {day_str})\n\n"
+        f"How does this user react? Reply with exactly one word: done | snooze | dismiss\n\n"
+        f"- done: acts on this tip (marks task complete)\n"
+        f"- snooze: acknowledges but not now\n"
+        f"- dismiss: ignores or rejects it"
+    )
+
+    try:
+        message = client.messages.create(
+            model="claude-haiku-4-5-20251001",
+            max_tokens=10,
+            messages=[{"role": "user", "content": prompt}],
+        )
+        raw = message.content[0].text.strip().lower().split()[0]
+        action = raw if raw in ACTIONS else _rule_judge(persona, tip, hour, rng)[0]
+    except Exception:
+        action, _ = _rule_judge(persona, tip, hour, rng)
+
+    # Simulate dwell based on engagement level
+    engagement = _engagement_score(persona, tip, hour)
+    dwell = _simulate_dwell_ms(engagement, rng) if action == "done" else rng.randint(2_000, 15_000)
+    return action, dwell
+
+
+# ── Public API ─────────────────────────────────────────────────────────────
+
+def judge(
+    persona: Persona,
+    tip: dict,
+    hour: int,
+    day_of_week: int,
+    rng: random.Random,
+    use_llm: bool = True,
+) -> tuple[str, int, float]:
+    """Return (action, dwell_ms, reward).
+
+    action   — 'done' | 'snooze' | 'dismiss'
+    dwell_ms — simulated milliseconds between tip appearance and user action
+    reward   — inferred from action + dwell_ms via infer_reward()
+    """
+    if use_llm and os.environ.get("ANTHROPIC_API_KEY"):
+        action, dwell_ms = _llm_judge(persona, tip, hour, day_of_week, rng)
+    else:
+        action, dwell_ms = _rule_judge(persona, tip, hour, rng)
+
+    return action, dwell_ms, infer_reward(action, dwell_ms)

ml/experiments/sim/personas.py

@@ -0,0 +1,79 @@
+"""Synthetic user personas for simulation."""
+
+from dataclasses import dataclass
+
+
+@dataclass
+class Persona:
+    name: str
+    description: str
+    # Feature preference weights — used by deterministic judge
+    prefers_high_priority: float  # 0–1: scales response to priority
+    prefers_overdue: float        # 0–1: scales response to overdue tasks
+    morning_active: bool          # higher engagement hours 6–10
+    evening_active: bool          # higher engagement hours 18–22
+    recency_bias: float           # 0–1: prefers recently-due tasks
+
+
+PERSONAS: list[Persona] = [
+    Persona(
+        name="deadline-driven",
+        description=(
+            "Responds urgently to overdue and high-priority tasks. "
+            "Most active in the morning. Dismisses low-priority tips."
+        ),
+        prefers_high_priority=0.9,
+        prefers_overdue=0.85,
+        morning_active=True,
+        evening_active=False,
+        recency_bias=0.3,
+    ),
+    Persona(
+        name="evening-relaxed",
+        description=(
+            "Reviews tasks in the evenings. Neutral on priority. "
+            "Snoozes morning recommendations."
+        ),
+        prefers_high_priority=0.5,
+        prefers_overdue=0.4,
+        morning_active=False,
+        evening_active=True,
+        recency_bias=0.5,
+    ),
+    Persona(
+        name="low-priority-first",
+        description=(
+            "Clears small tasks first. Snoozes urgent items until deadline. "
+            "Morning person."
+        ),
+        prefers_high_priority=0.2,
+        prefers_overdue=0.6,
+        morning_active=True,
+        evening_active=False,
+        recency_bias=0.7,
+    ),
+    Persona(
+        name="consistent-responder",
+        description=(
+            "Engages consistently across hours and days. "
+            "Acts on helpful tips regardless of priority."
+        ),
+        prefers_high_priority=0.6,
+        prefers_overdue=0.6,
+        morning_active=True,
+        evening_active=True,
+        recency_bias=0.5,
+    ),
+    Persona(
+        name="overdue-ignorer",
+        description=(
+            "Avoids overdue tasks (stress avoidance). "
+            "Focuses on future-due, high-priority items. Evening person."
+        ),
+        prefers_high_priority=0.8,
+        prefers_overdue=0.1,
+        morning_active=False,
+        evening_active=True,
+        recency_bias=0.2,
+    ),
+]

ml/experiments/sim/runner.py

@@ -0,0 +1,527 @@
+"""
+oO simulation runner — compares two recommendation policies.
+
+Judge modes:
+  rule         Deterministic persona-based rules (default, no external deps)
+  llm          Claude Haiku via Anthropic API (requires ANTHROPIC_API_KEY)
+  claude-code  Two-phase: Claude Code acts as the judge (you are the judge)
+
+Usage — rule/llm (single pass):
+  python runner.py --n-users 5 --n-rounds 10 --no-llm
+  python runner.py --n-users 5 --n-rounds 10
+
+Usage — claude-code judge (two phases):
+  # Phase 1: score candidates, write judgment requests
+  python runner.py --judge claude-code --phase score \\
+      --n-users 5 --n-rounds 10 --out /tmp/oo-cc-sim.json
+
+  # (Claude Code reads /tmp/oo-cc-sim-requests.json and writes /tmp/oo-cc-sim-responses.json)
+
+  # Phase 2: apply responses, run rewards, produce results
+  python runner.py --judge claude-code --phase reward --plan /tmp/oo-cc-sim-plan.json \\
+      --out /tmp/oo-cc-sim.json
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+import random
+import sys
+import time
+import uuid
+from pathlib import Path
+
+sys.path.insert(0, str(Path(__file__).parent))
+
+import httpx
+
+from llm_judge import ACTIONS, infer_reward, judge
+from personas import PERSONAS, Persona
+from task_generator import generate_task_pool
+
+POLICY_SCORE_ENDPOINTS: dict[str, str] = {
+    "linucb-v1": "/score",
+    "egreedy-v1": "/score/egreedy",
+}
+POLICY_REWARD_ENDPOINTS: dict[str, str] = {
+    "linucb-v1": "/reward",
+    "egreedy-v1": "/reward/egreedy",
+}
+
+
+def _call_score(
+    client: httpx.Client, ml_url: str, policy: str,
+    user_id: str, tasks: list[dict], hour: int, dow: int,
+) -> dict | None:
+    endpoint = POLICY_SCORE_ENDPOINTS.get(policy, "/score")
+    body = {
+        "user_id": user_id,
+        "candidates": [
+            {
+                "id": t["id"], "content": t["content"], "source": t["source"],
+                "source_id": None,
+                "features": {
+                    "hour_of_day": hour,
+                    "is_overdue": t["features"]["is_overdue"],
+                    "task_age_days": t["features"]["task_age_days"],
+                    "priority": t["features"]["priority"],
+                },
+            }
+            for t in tasks
+        ],
+        "context": {"hour_of_day": hour, "day_of_week": dow},
+    }
+    try:
+        r = client.post(f"{ml_url}{endpoint}", json=body, timeout=5.0)
+        r.raise_for_status()
+        return r.json()
+    except Exception as e:
+        print(f"  [warn] score {policy}: {e}", file=sys.stderr)
+        return None
+
+
+def _call_reward(
+    client: httpx.Client, ml_url: str, policy: str,
+    user_id: str, tip_id: str, reward: float, features: dict,
+    day_of_week: int = 0,
+) -> None:
+    endpoint = POLICY_REWARD_ENDPOINTS.get(policy, "/reward")
+    try:
+        client.post(
+            f"{ml_url}{endpoint}",
+            json={"user_id": user_id, "tip_id": tip_id, "reward": reward,
+                  "features": features, "day_of_week": day_of_week},
+            timeout=5.0,
+        )
+    except Exception as e:
+        print(f"  [warn] reward {policy}: {e}", file=sys.stderr)
+
+
+# ── Standard single-pass runner (rule / llm modes) ─────────────────────────
+
+def run_simulation(
+    n_users: int, n_rounds: int, tasks_per_round: int,
+    ml_url: str, policies: list[str], use_llm: bool, seed: int,
+) -> dict:
+    rng = random.Random(seed)
+    run_id = str(uuid.uuid4())[:8]
+    started_at = time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime())
+
+    user_personas = [
+        (f"sim-{run_id}-u{i}", PERSONAS[i % len(PERSONAS)])
+        for i in range(n_users)
+    ]
+
+    acc: dict[str, dict] = {
+        p: {
+            "total_reward": 0.0, "n_pulls": 0,
+            "cumulative_rewards": [],
+            "action_counts": {a: 0 for a in ACTIONS},
+        }
+        for p in policies
+    }
+    events: list[dict] = []
+
+    with httpx.Client(trust_env=False) as client:
+        for rnd in range(n_rounds):
+            hour = rng.randint(6, 22)
+            dow = rng.randint(0, 6)
+            round_rewards = {p: 0.0 for p in policies}
+
+            for user_id, persona in user_personas:
+                seed_tasks = rnd * 997 + abs(hash(user_id)) % 997
+                tasks = generate_task_pool(n=tasks_per_round, seed=seed_tasks)
+
+                for policy in policies:
+                    p_user = f"{user_id}-{policy}"
+                    scored = _call_score(client, ml_url, policy, p_user, tasks, hour, dow)
+                    if not scored:
+                        continue
+                    tip_id = scored.get("tip_id")
+                    tip = next((t for t in tasks if t["id"] == tip_id), None)
+                    if not tip:
+                        continue
+
+                    action, dwell_ms, reward = judge(persona, tip, hour, dow, rng, use_llm=use_llm)
+                    _call_reward(client, ml_url, policy, p_user, tip_id, reward, {
+                        "hour_of_day": hour,
+                        "is_overdue": tip["features"]["is_overdue"],
+                        "task_age_days": tip["features"]["task_age_days"],
+                        "priority": tip["features"]["priority"],
+                    }, day_of_week=dow)
+
+                    acc[policy]["total_reward"] += reward
+                    acc[policy]["n_pulls"] += 1
+                    acc[policy]["action_counts"][action] += 1
+                    round_rewards[policy] += reward
+                    events.append({
+                        "round": rnd, "user_id": user_id, "persona": persona.name,
+                        "policy": policy, "tip_content": tip["content"],
+                        "priority": tip["features"]["priority"],
+                        "is_overdue": tip["features"]["is_overdue"],
+                        "action": action, "dwell_ms": dwell_ms, "reward": reward,
+                        "hour": hour, "day_of_week": dow,
+                    })
+
+            for p in policies:
+                prev = acc[p]["cumulative_rewards"][-1] if acc[p]["cumulative_rewards"] else 0.0
+                acc[p]["cumulative_rewards"].append(prev + round_rewards[p])
+
+            mode = "llm" if use_llm else "rule"
+            print(f"  Round {rnd+1:>3}/{n_rounds} [{mode}]  " + "  ".join(
+                f"{p}={acc[p]['cumulative_rewards'][-1]:+.2f}" for p in policies
+            ))
+
+    return _build_result(run_id, started_at, policies, acc, events,
+                         n_users, n_rounds, tasks_per_round, use_llm, seed)
+
+
+# ── Claude Code judge — phase 1: score ─────────────────────────────────────
+
+def run_score_phase(
+    n_users: int, n_rounds: int, tasks_per_round: int,
+    ml_url: str, policies: list[str], seed: int, out_path: str,
+) -> None:
+    """Score all candidates and write judgment requests for Claude Code."""
+    rng = random.Random(seed)
+    run_id = str(uuid.uuid4())[:8]
+    started_at = time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime())
+
+    user_personas = [
+        (f"sim-{run_id}-u{i}", PERSONAS[i % len(PERSONAS)])
+        for i in range(n_users)
+    ]
+
+    plan_rounds: list[dict] = []
+    judgment_requests: list[dict] = []
+
+    print(f"[Phase 1] Scoring {n_rounds} rounds × {n_users} users × {len(policies)} policies…")
+
+    with httpx.Client(trust_env=False) as client:
+        for rnd in range(n_rounds):
+            hour = rng.randint(6, 22)
+            dow = rng.randint(0, 6)
+            round_sessions: list[dict] = []
+
+            for user_id, persona in user_personas:
+                seed_tasks = rnd * 997 + abs(hash(user_id)) % 997
+                tasks = generate_task_pool(n=tasks_per_round, seed=seed_tasks)
+
+                for policy in policies:
+                    p_user = f"{user_id}-{policy}"
+                    scored = _call_score(client, ml_url, policy, p_user, tasks, hour, dow)
+                    if not scored:
+                        continue
+                    tip_id = scored.get("tip_id")
+                    tip = next((t for t in tasks if t["id"] == tip_id), None)
+                    if not tip:
+                        continue
+
+                    req_id = f"r{rnd}_{user_id.split('-')[-1]}_{policy}"
+                    round_sessions.append({
+                        "req_id": req_id,
+                        "p_user": p_user,
+                        "policy": policy,
+                        "user_id": user_id,
+                        "persona_name": persona.name,
+                        "tip_id": tip_id,
+                        "tip_features": tip["features"],
+                        "tip_content": tip["content"],
+                        "ml_score": scored.get("score"),
+                    })
+
+                    judgment_requests.append({
+                        "id": req_id,
+                        "round": rnd,
+                        "hour": hour,
+                        "day_of_week": dow,
+                        "policy": policy,
+                        "persona_name": persona.name,
+                        "persona_description": persona.description,
+                        "tip_content": tip["content"],
+                        "priority": tip["features"]["priority"],
+                        "is_overdue": tip["features"]["is_overdue"],
+                        "age_days": tip["features"]["task_age_days"],
+                        "ml_score": scored.get("score"),
+                    })
+
+            plan_rounds.append({
+                "round": rnd, "hour": hour, "dow": dow,
+                "sessions": round_sessions,
+            })
+            print(f"  Round {rnd+1:>3}/{n_rounds}: {len(round_sessions)} sessions scored")
+
+    plan = {
+        "run_id": run_id,
+        "started_at": started_at,
+        "config": {
+            "n_users": n_users, "n_rounds": n_rounds,
+            "tasks_per_round": tasks_per_round, "policies": policies,
+            "use_llm": False, "seed": seed,
+        },
+        "user_personas": [
+            {"user_id": uid, "persona_name": p.name, "persona_description": p.description}
+            for uid, p in user_personas
+        ],
+        "rounds": plan_rounds,
+    }
+
+    base = out_path.replace(".json", "")
+    plan_path = f"{base}-plan.json"
+    requests_path = f"{base}-requests.json"
+    responses_path = f"{base}-responses.json"
+
+    Path(plan_path).write_text(json.dumps(plan, indent=2))
+    Path(requests_path).write_text(json.dumps(judgment_requests, indent=2))
+
+    print()
+    print("=" * 60)
+    print(f"Phase 1 complete — {len(judgment_requests)} judgment requests.")
+    print()
+    print(f"  Requests : {requests_path}")
+    print(f"  Plan     : {plan_path}")
+    print()
+    print('Claude Code: read the requests file, judge each tip for the persona,')
+    print(f'then write your responses to: {responses_path}')
+    print()
+    print('Response format: { "<id>": "<action>" | { "action": "<action>", "dwell_ms": <int> } }')
+    print('Valid actions: done | snooze | dismiss')
+    print()
+    print('For "done", optionally specify dwell_ms (ms between tip appearing and user acting):')
+    print('  { "r0_u0_linucb-v1": { "action": "done", "dwell_ms": 45000 } }  # magic zone')
+    print('  { "r0_u0_linucb-v1": "snooze" }  # plain string also ok (uses default 60s dwell for done)')
+    print()
+    print('Reward is inferred from action + dwell_ms:')
+    print('  dismiss          → -1.0')
+    print('  snooze           →  0.1')
+    print('  done < 15s       → -0.3  (stale task)')
+    print('  done 15s–2min    →  1.0  (magic!)')
+    print('  done 2–10min     →  0.6  (good)')
+    print('  done > 10min     →  0.3  (eventually)')
+    print()
+    print('Then run Phase 2:')
+    print(f'  python runner.py --judge claude-code --phase reward \\')
+    print(f'    --plan {plan_path} --out {out_path}')
+
+
+# ── Claude Code judge — phase 2: reward ────────────────────────────────────
+
+def run_reward_phase(plan_path: str, out_path: str, ml_url: str) -> dict:
+    """Apply Claude Code judgments, send reward signals, compute metrics."""
+    plan = json.loads(Path(plan_path).read_text())
+    base = plan_path.replace("-plan.json", "")
+    responses_path = f"{base}-responses.json"
+
+    if not Path(responses_path).exists():
+        print(f"ERROR: responses file not found: {responses_path}", file=sys.stderr)
+        sys.exit(1)
+
+    raw_responses = json.loads(Path(responses_path).read_text())
+
+    # Responses can be either { id: "action" } or { id: { action, dwell_ms } }
+    def _parse_response(v) -> tuple[str, int]:
+        if isinstance(v, dict):
+            return v["action"], int(v.get("dwell_ms", 60_000))
+        return str(v), 60_000  # plain string → assume 60s dwell for "done"
+
+    responses: dict[str, tuple[str, int]] = {k: _parse_response(v) for k, v in raw_responses.items()}
+
+    invalid = {k: v[0] for k, v in responses.items() if v[0] not in ACTIONS}
+    if invalid:
+        print(f"ERROR: invalid actions in responses: {invalid}", file=sys.stderr)
+        sys.exit(1)
+
+    policies: list[str] = plan["config"]["policies"]
+    acc: dict[str, dict] = {
+        p: {
+            "total_reward": 0.0, "n_pulls": 0,
+            "cumulative_rewards": [],
+            "action_counts": {a: 0 for a in ACTIONS},
+        }
+        for p in policies
+    }
+    events: list[dict] = []
+    persona_map = {u["user_id"]: u["persona_name"] for u in plan["user_personas"]}
+    missing_responses = 0
+
+    print(f"[Phase 2] Applying {len(responses)} judgments → reward calls…")
+
+    with httpx.Client(trust_env=False) as client:
+        for rnd_data in plan["rounds"]:
+            rnd = rnd_data["round"]
+            round_rewards = {p: 0.0 for p in policies}
+
+            for session in rnd_data["sessions"]:
+                req_id = session["req_id"]
+                resp = responses.get(req_id)
+                if not resp:
+                    print(f"  [warn] no response for {req_id}, defaulting to snooze")
+                    action, dwell_ms = "snooze", 10_000
+                    missing_responses += 1
+                else:
+                    action, dwell_ms = resp
+
+                reward = infer_reward(action, dwell_ms)
+                _call_reward(
+                    client, ml_url, session["policy"], session["p_user"],
+                    session["tip_id"], reward,
+                    {"hour_of_day": rnd_data["hour"], **session["tip_features"]},
+                    day_of_week=rnd_data["dow"],
+                )
+
+                p = session["policy"]
+                acc[p]["total_reward"] += reward
+                acc[p]["n_pulls"] += 1
+                acc[p]["action_counts"][action] += 1
+                round_rewards[p] += reward
+
+                events.append({
+                    "round": rnd,
+                    "user_id": session["user_id"],
+                    "persona": persona_map.get(session["user_id"], "?"),
+                    "policy": p,
+                    "tip_content": session["tip_content"],
+                    "priority": session["tip_features"]["priority"],
+                    "is_overdue": session["tip_features"]["is_overdue"],
+                    "action": action,
+                    "dwell_ms": dwell_ms,
+                    "reward": reward,
+                    "hour": rnd_data["hour"],
+                    "day_of_week": rnd_data["dow"],
+                })
+
+            for p in policies:
+                prev = acc[p]["cumulative_rewards"][-1] if acc[p]["cumulative_rewards"] else 0.0
+                acc[p]["cumulative_rewards"].append(prev + round_rewards[p])
+
+            print(f"  Round {rnd+1:>3}/{plan['config']['n_rounds']} [cc]  " + "  ".join(
+                f"{p}={acc[p]['cumulative_rewards'][-1]:+.2f}" for p in policies
+            ))
+
+    if missing_responses:
+        print(f"  [warn] {missing_responses} requests had no response (defaulted to snooze)")
+
+    cfg = plan["config"]
+    result = _build_result(
+        plan["run_id"], plan["started_at"], policies, acc, events,
+        cfg["n_users"], cfg["n_rounds"], cfg["tasks_per_round"],
+        use_llm=False, seed=cfg["seed"],
+    )
+    result["judge_mode"] = "claude-code"
+    Path(out_path).write_text(json.dumps(result, indent=2))
+    return result
+
+
+# ── Shared result builder ───────────────────────────────────────────────────
+
+def _build_result(
+    run_id: str, started_at: str, policies: list[str],
+    acc: dict, events: list[dict],
+    n_users: int, n_rounds: int, tasks_per_round: int,
+    use_llm: bool, seed: int,
+) -> dict:
+    summary = {
+        p: {
+            "total_reward": acc[p]["total_reward"],
+            "mean_reward": (
+                acc[p]["total_reward"] / acc[p]["n_pulls"]
+                if acc[p]["n_pulls"] > 0 else 0.0
+            ),
+            "n_pulls": acc[p]["n_pulls"],
+            "cumulative_rewards": acc[p]["cumulative_rewards"],
+            "action_counts": acc[p]["action_counts"],
+        }
+        for p in policies
+    }
+    winner = max(policies, key=lambda p: summary[p]["total_reward"])
+
+    persona_breakdown: dict[str, dict] = {}
+    for ev in events:
+        pname = ev["persona"]
+        pol = ev["policy"]
+        persona_breakdown.setdefault(pname, {}).setdefault(pol, {"reward": 0.0, "n": 0})
+        persona_breakdown[pname][pol]["reward"] += ev["reward"]
+        persona_breakdown[pname][pol]["n"] += 1
+
+    return {
+        "run_id": run_id,
+        "started_at": started_at,
+        "finished_at": time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime()),
+        "config": {
+            "n_users": n_users, "n_rounds": n_rounds,
+            "tasks_per_round": tasks_per_round, "policies": policies,
+            "use_llm": use_llm, "seed": seed,
+        },
+        "summary": summary,
+        "winner": winner,
+        "persona_breakdown": persona_breakdown,
+        "events": events,
+    }
+
+
+# ── CLI ─────────────────────────────────────────────────────────────────────
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="oO simulation runner")
+    parser.add_argument("--judge", choices=["rule", "llm", "claude-code"], default="rule")
+    parser.add_argument("--phase", choices=["score", "reward"], default=None,
+                        help="For --judge claude-code only")
+    parser.add_argument("--plan", default=None,
+                        help="Plan file path (for --judge claude-code --phase reward)")
+    parser.add_argument("--n-users", type=int, default=5)
+    parser.add_argument("--n-rounds", type=int, default=20)
+    parser.add_argument("--tasks-per-round", type=int, default=8)
+    parser.add_argument("--ml-url", default="http://localhost:5001")
+    parser.add_argument("--policies", nargs="+", default=["linucb-v1", "egreedy-v1"])
+    parser.add_argument("--no-llm", action="store_true",
+                        help="Alias for --judge rule (backwards compat)")
+    parser.add_argument("--seed", type=int, default=42)
+    parser.add_argument("--out", default=None)
+    args = parser.parse_args()
+
+    if args.no_llm:
+        args.judge = "rule"
+
+    out_path = args.out or f"/tmp/oo-sim-{int(time.time())}.json"
+
+    if args.judge == "claude-code":
+        if args.phase == "score":
+            run_score_phase(
+                n_users=args.n_users, n_rounds=args.n_rounds,
+                tasks_per_round=args.tasks_per_round, ml_url=args.ml_url,
+                policies=args.policies, seed=args.seed, out_path=out_path,
+            )
+        elif args.phase == "reward":
+            if not args.plan:
+                print("ERROR: --plan is required for --phase reward", file=sys.stderr)
+                sys.exit(1)
+            result = run_reward_phase(args.plan, out_path, args.ml_url)
+            print()
+            print(f"Winner : {result['winner']}")
+            for p, s in result["summary"].items():
+                print(f"  {p:20s}  total={s['total_reward']:+.2f}  mean={s['mean_reward']:+.4f}  pulls={s['n_pulls']}")
+            print(f"Results: {out_path}")
+        else:
+            print("ERROR: --judge claude-code requires --phase score or --phase reward",
+                  file=sys.stderr)
+            sys.exit(1)
+    else:
+        use_llm = (args.judge == "llm")
+        print(f"oO simulation: {args.n_users} users × {args.n_rounds} rounds")
+        print(f"Policies : {args.policies}")
+        print(f"ML URL   : {args.ml_url}")
+        print(f"Judge    : {args.judge}")
+        print()
+
+        result = run_simulation(
+            n_users=args.n_users, n_rounds=args.n_rounds,
+            tasks_per_round=args.tasks_per_round, ml_url=args.ml_url,
+            policies=args.policies, use_llm=use_llm, seed=args.seed,
+        )
+        Path(out_path).write_text(json.dumps(result, indent=2))
+        print()
+        print(f"Winner : {result['winner']}")
+        for p, s in result["summary"].items():
+            print(f"  {p:20s}  total={s['total_reward']:+.2f}  mean={s['mean_reward']:+.4f}  pulls={s['n_pulls']}")
+        print(f"Results: {out_path}")

ml/experiments/sim/task_generator.py

@@ -0,0 +1,62 @@
+"""Generate synthetic task pools for simulation."""
+
+from __future__ import annotations
+
+import random
+
+_TEMPLATES = [
+    "Send weekly report to team",
+    "Review pull request #{n}",
+    "Schedule meeting with {name}",
+    "Update project documentation",
+    "Fix bug in authentication module",
+    "Prepare presentation for stakeholders",
+    "Call back {name}",
+    "Submit expense report",
+    "Review quarterly goals",
+    "Clean up inbox",
+    "Follow up on proposal to {name}",
+    "Complete onboarding checklist",
+    "Write tests for feature #{n}",
+    "Deploy hotfix to production",
+    "Respond to support ticket #{n}",
+    "Draft release notes",
+    "Update dependencies",
+    "Review design mockups",
+    "Archive old tickets",
+    "Check in with {name}",
+]
+
+_NAMES = ["Alice", "Bob", "Carol", "David", "Eve", "Frank", "Grace"]
+
+
+def generate_task_pool(n: int = 10, seed: int | None = None) -> list[dict]:
+    """Return n synthetic tasks with randomly sampled features."""
+    rng = random.Random(seed)
+
+    tasks = []
+    for i in range(n):
+        priority = rng.choices([1, 2, 3, 4], weights=[0.3, 0.3, 0.25, 0.15])[0]
+        # age_days: most tasks fresh, a few stale
+        age_days = rng.choices(
+            [0.0, 0.5, 1.0, 3.0, 7.0, 14.0],
+            weights=[0.35, 0.20, 0.20, 0.12, 0.08, 0.05],
+        )[0] + rng.random() * 0.5
+        # is_overdue only meaningful when age > 0
+        is_overdue = age_days > 0.5 and rng.random() < 0.65
+
+        template = rng.choice(_TEMPLATES)
+        content = template.format(n=rng.randint(100, 999), name=rng.choice(_NAMES))
+
+        tasks.append({
+            "id": f"sim:{i}",
+            "content": content,
+            "source": "sim",
+            "features": {
+                "is_overdue": is_overdue,
+                "task_age_days": age_days if is_overdue else 0.0,
+                "priority": priority,
+            },
+        })
+
+    return tasks

ml/features/__init__.py

@@ -0,0 +1,3 @@
+from .context import build_context, PromptContext, TaskSignal
+
+__all__ = ["build_context", "PromptContext", "TaskSignal"]

ml/features/context.py

@@ -0,0 +1,63 @@
+"""
+Context assembler — converts raw user signals into a PromptContext for LLM tip generation.
+
+Usage:
+    from ml.features.context import build_context
+    ctx = build_context(tasks, hour_of_day=9, day_of_week=2)
+"""
+
+from __future__ import annotations
+from dataclasses import dataclass, field
+
+
+@dataclass
+class TaskSignal:
+    id: str
+    content: str
+    priority: int = 1           # 1–4 (Todoist scale)
+    is_overdue: bool = False
+    task_age_days: float = 0.0
+    due_date: str | None = None
+
+
+@dataclass
+class PromptContext:
+    tasks: list[dict] = field(default_factory=list)
+    hour_of_day: int = 12
+    day_of_week: int = 0
+    extra: dict = field(default_factory=dict)
+
+
+def build_context(
+    tasks: list[TaskSignal],
+    hour_of_day: int = 12,
+    day_of_week: int = 0,
+    extra: dict | None = None,
+) -> PromptContext:
+    """
+    Assemble user signals into a PromptContext.
+
+    Signals are sorted so overdue + high-priority tasks appear first,
+    giving the LLM the most actionable context at the top of the prompt.
+    """
+    sorted_tasks = sorted(
+        tasks,
+        key=lambda t: (not t.is_overdue, -t.priority, -t.task_age_days),
+    )
+    task_dicts = [
+        {
+            "id": t.id,
+            "content": t.content,
+            "priority": t.priority,
+            "is_overdue": t.is_overdue,
+            "task_age_days": round(t.task_age_days, 1),
+            "due_date": t.due_date,
+        }
+        for t in sorted_tasks
+    ]
+    return PromptContext(
+        tasks=task_dicts,
+        hour_of_day=hour_of_day,
+        day_of_week=day_of_week,
+        extra=extra or {},
+    )

ml/features/test_context.py

@@ -0,0 +1,64 @@
+"""Tests for ml/features/context.py"""
+import pytest
+import sys, os; sys.path.insert(0, os.path.dirname(__file__))
+from context import build_context, TaskSignal, PromptContext
+
+
+def test_empty_tasks():
+    ctx = build_context([], hour_of_day=9, day_of_week=1)
+    assert ctx.tasks == []
+    assert ctx.hour_of_day == 9
+    assert ctx.day_of_week == 1
+
+
+def test_overdue_tasks_sorted_first():
+    tasks = [
+        TaskSignal(id="a", content="Normal task", priority=1, is_overdue=False),
+        TaskSignal(id="b", content="Overdue task", priority=2, is_overdue=True, task_age_days=3.0),
+    ]
+    ctx = build_context(tasks)
+    assert ctx.tasks[0]["id"] == "b"
+
+
+def test_high_priority_within_non_overdue():
+    tasks = [
+        TaskSignal(id="lo", content="Low prio", priority=1, is_overdue=False),
+        TaskSignal(id="hi", content="High prio", priority=4, is_overdue=False),
+    ]
+    ctx = build_context(tasks)
+    assert ctx.tasks[0]["id"] == "hi"
+
+
+def test_extra_fields_passed_through():
+    ctx = build_context([], extra={"mood": "focused"})
+    assert ctx.extra["mood"] == "focused"
+
+
+def test_task_age_rounded():
+    tasks = [TaskSignal(id="x", content="Task", task_age_days=1.23456)]
+    ctx = build_context(tasks)
+    assert ctx.tasks[0]["task_age_days"] == 1.2
+
+
+def test_overdue_sorted_by_priority():
+    tasks = [
+        TaskSignal(id="lo", content="Low", priority=1, is_overdue=True),
+        TaskSignal(id="hi", content="High", priority=4, is_overdue=True),
+    ]
+    ctx = build_context(tasks)
+    assert ctx.tasks[0]["id"] == "hi"
+
+
+def test_overdue_same_priority_sorted_by_age():
+    tasks = [
+        TaskSignal(id="new", content="New", priority=2, is_overdue=True, task_age_days=1.0),
+        TaskSignal(id="old", content="Old", priority=2, is_overdue=True, task_age_days=5.0),
+    ]
+    ctx = build_context(tasks)
+    assert ctx.tasks[0]["id"] == "old"
+
+
+def test_due_date_none_preserved():
+    tasks = [TaskSignal(id="x", content="No due", due_date=None)]
+    ctx = build_context(tasks)
+    assert ctx.tasks[0]["due_date"] is None

ml/serving/main.py

@@ -0,0 +1,556 @@
+"""
+oO ML Serving — Phase 1: LinUCB contextual bandit.
+
+Contract:
+  POST /score              { user_id, candidates, context } → { tip_id, score, policy }
+  POST /reward             { user_id, tip_id, reward, features } → { ok }
+  POST /reset/{user_id}    → { ok }
+  GET  /stats/{user_id}    → { pulls, cumulative_reward, estimated_mean, last_updated }
+  GET  /features/{user_id} → { history: [{ ts, features, score }] }
+  GET  /health             → { ok }
+
+Features (d=5):
+  hour_sin, hour_cos  — cyclical time-of-day encoding
+  is_overdue          — 0 or 1
+  task_age_days       — days since due date (clipped 0–30, normalised 0–1)
+  priority_norm       — Todoist priority 1–4, normalised to 0–1
+"""
+
+from __future__ import annotations
+
+import json
+import math
+import os
+import time
+from collections import deque
+from pathlib import Path
+from typing import Optional, Deque
+
+import httpx
+import numpy as np
+from fastapi import FastAPI, HTTPException
+from pydantic import BaseModel
+
+app = FastAPI(title="oO ML Serving", version="1.0.0")
+
+LITELLM_URL = os.getenv("LITELLM_URL", "http://localhost:4000")
+LITELLM_MASTER_KEY = os.getenv("LITELLM_MASTER_KEY", "sk-oo-dev")
+
+STATE_DIR = Path(os.getenv("STATE_DIR", "/tmp/oo-bandit-state"))
+STATE_DIR.mkdir(parents=True, exist_ok=True)
+
+ALPHA = 1.0   # LinUCB exploration coefficient
+D = 5         # LinUCB feature dimension
+D7 = 7        # ε-greedy feature dimension (adds day-of-week cyclical encoding)
+EPSILON = 0.1 # ε-greedy exploration rate
+FEATURE_HISTORY_SIZE = 100  # per-user ring buffer
+
+
+# ── Per-user in-memory feature history ────────────────────────────────────
+_feature_history: dict[str, deque] = {}
+
+def get_feature_history(user_id: str) -> deque:
+    if user_id not in _feature_history:
+        _feature_history[user_id] = deque(maxlen=FEATURE_HISTORY_SIZE)
+    return _feature_history[user_id]
+
+
+# ── Feature helpers ────────────────────────────────────────────────────────
+
+def build_feature_vector(features: dict) -> np.ndarray:
+    hour = features.get("hour_of_day", 12)
+    hour_sin = math.sin(2 * math.pi * hour / 24)
+    hour_cos = math.cos(2 * math.pi * hour / 24)
+    is_overdue = float(bool(features.get("is_overdue", False)))
+    age = min(float(features.get("task_age_days", 0)), 30.0) / 30.0
+    priority = (float(features.get("priority", 1)) - 1.0) / 3.0
+    return np.array([hour_sin, hour_cos, is_overdue, age, priority], dtype=np.float64)
+
+
+# ── Per-user bandit state (disjoint LinUCB, global arm) ───────────────────
+
+# ── LinUCB state helpers ───────────────────────────────────────────────────
+
+def state_path(user_id: str) -> Path:
+    safe = "".join(c if c.isalnum() else "_" for c in user_id)
+    return STATE_DIR / f"{safe}.json"
+
+
+def load_state(user_id: str) -> tuple[np.ndarray, np.ndarray, dict]:
+    """Returns (A, b, meta). A is DxD, b is D-vector."""
+    p = state_path(user_id)
+    if p.exists():
+        raw = json.loads(p.read_text())
+        A = np.array(raw["A"], dtype=np.float64)
+        b = np.array(raw["b"], dtype=np.float64)
+        meta = raw.get("meta", {})
+        return A, b, meta
+    return np.identity(D, dtype=np.float64), np.zeros(D, dtype=np.float64), {}
+
+
+def save_state(user_id: str, A: np.ndarray, b: np.ndarray, meta: dict) -> None:
+    p = state_path(user_id)
+    p.write_text(json.dumps({"A": A.tolist(), "b": b.tolist(), "meta": meta}))
+
+
+# ── ε-greedy state helpers (d=7, extended features) ───────────────────────
+
+def build_feature_vector_7(features: dict, day_of_week: int = 0) -> np.ndarray:
+    """d=7: base 5 features + day-of-week cyclical encoding."""
+    base = build_feature_vector(features)
+    dow_sin = math.sin(2 * math.pi * day_of_week / 7)
+    dow_cos = math.cos(2 * math.pi * day_of_week / 7)
+    return np.append(base, [dow_sin, dow_cos])
+
+
+def state7_path(user_id: str) -> Path:
+    safe = "".join(c if c.isalnum() else "_" for c in user_id)
+    return STATE_DIR / f"{safe}_egreedy.json"
+
+
+def load_state7(user_id: str) -> tuple[np.ndarray, np.ndarray, dict]:
+    """Returns (A, b, meta) for ε-greedy d=7 policy."""
+    p = state7_path(user_id)
+    if p.exists():
+        raw = json.loads(p.read_text())
+        A = np.array(raw["A"], dtype=np.float64)
+        b = np.array(raw["b"], dtype=np.float64)
+        return A, b, raw.get("meta", {})
+    return np.identity(D7, dtype=np.float64), np.zeros(D7, dtype=np.float64), {}
+
+
+def save_state7(user_id: str, A: np.ndarray, b: np.ndarray, meta: dict) -> None:
+    p = state7_path(user_id)
+    p.write_text(json.dumps({"A": A.tolist(), "b": b.tolist(), "meta": meta}))
+
+
+# ── API models ─────────────────────────────────────────────────────────────
+
+class CandidateFeatures(BaseModel):
+    hour_of_day: int = 12
+    is_overdue: bool = False
+    task_age_days: float = 0.0
+    priority: int = 1
+
+
+class Candidate(BaseModel):
+    id: str
+    content: str
+    source: str
+    source_id: Optional[str] = None
+    features: CandidateFeatures = CandidateFeatures()
+
+
+class Context(BaseModel):
+    hour_of_day: int = 12
+    day_of_week: int = 0
+
+
+class ScoreRequest(BaseModel):
+    user_id: str
+    candidates: list[Candidate]
+    context: Context = Context()
+
+
+class ScoreResponse(BaseModel):
+    tip_id: str
+    score: float
+    policy: str
+
+
+class RewardRequest(BaseModel):
+    user_id: str
+    tip_id: str
+    reward: float          # +1 done, +0.5 helpful, 0 snooze, -0.5 not_helpful, -1 dismiss
+    features: CandidateFeatures
+    day_of_week: int = 0   # included so egreedy can train dow features correctly
+
+
+class RewardResponse(BaseModel):
+    ok: bool
+
+
+class PromptContext(BaseModel):
+    tasks: list[dict] = []
+    hour_of_day: int = 12
+    day_of_week: int = 0
+    extra: dict = {}
+
+
+class GenerateRequest(BaseModel):
+    user_id: str
+    context: PromptContext = PromptContext()
+    n: int = 3
+
+
+class TipCandidate(BaseModel):
+    id: str
+    content: str
+    source: str = "llm"
+    rationale: Optional[str] = None
+
+
+class GenerateResponse(BaseModel):
+    candidates: list[TipCandidate]
+    model: str
+    prompt_tokens: int = 0
+    completion_tokens: int = 0
+
+
+_GENERATE_SYSTEM = (
+    "You are a personal productivity coach. "
+    "Given the user's current context, generate actionable, specific tips. "
+    "Respond ONLY with a JSON array of objects, each with keys: "
+    '"id" (short slug), "content" (the tip, ≤2 sentences), "rationale" (why now, ≤1 sentence). '
+    "No markdown, no prose outside the JSON array."
+)
+
+
+def _build_prompt(ctx: PromptContext, n: int) -> str:
+    lines = [f"Time: {ctx.hour_of_day:02d}:00, day_of_week={ctx.day_of_week}"]
+    if ctx.tasks:
+        overdue = [t for t in ctx.tasks if t.get("is_overdue")]
+        lines.append(f"Tasks: {len(ctx.tasks)} total, {len(overdue)} overdue")
+        for t in ctx.tasks[:5]:
+            due = t.get("due_date", "no due date")
+            lines.append(f"  - [{t.get('priority','?')}] {t.get('content','?')} (due: {due})")
+    for k, v in ctx.extra.items():
+        lines.append(f"{k}: {v}")
+    lines.append(f"\nGenerate {n} tips as a JSON array.")
+    return "\n".join(lines)
+
+
+# ── Endpoints ──────────────────────────────────────────────────────────────
+
+@app.get("/health")
+def health():
+    return {"ok": True}
+
+
+_RETRY_SUFFIX = (
+    "\n\nYour previous response was not valid JSON. "
+    "Reply ONLY with the JSON array — no prose, no markdown fences."
+)
+
+_MAX_GENERATE_RETRIES = 2
+
+
+def _parse_llm_json(raw: str) -> list[dict]:
+    """Strip markdown fences and parse JSON array. Raises ValueError on failure."""
+    text = raw.strip()
+    if text.startswith("```"):
+        parts = text.split("```")
+        text = parts[1] if len(parts) > 1 else text
+        if text.startswith("json"):
+            text = text[4:]
+    return json.loads(text)
+
+
+@app.post("/generate", response_model=GenerateResponse)
+async def generate(req: GenerateRequest) -> GenerateResponse:
+    """Generate tip candidates via LiteLLM → tip-generator alias.
+
+    Retries up to _MAX_GENERATE_RETRIES times on malformed JSON, appending
+    a correction hint to the conversation so the model can self-correct.
+    """
+    prompt = _build_prompt(req.context, req.n)
+    messages: list[dict] = [
+        {"role": "system", "content": _GENERATE_SYSTEM},
+        {"role": "user", "content": prompt},
+    ]
+    headers = {"Authorization": f"Bearer {LITELLM_MASTER_KEY}"}
+    last_parse_error: str = ""
+    last_raw: str = ""
+    total_usage: dict = {"prompt_tokens": 0, "completion_tokens": 0}
+    model_used = "tip-generator"
+
+    async with httpx.AsyncClient(timeout=30.0) as client:
+        for attempt in range(1 + _MAX_GENERATE_RETRIES):
+            payload = {"model": "tip-generator", "messages": messages, "temperature": 0.7}
+            try:
+                resp = await client.post(
+                    f"{LITELLM_URL}/chat/completions",
+                    json=payload,
+                    headers=headers,
+                )
+                resp.raise_for_status()
+            except httpx.HTTPStatusError as e:
+                raise HTTPException(status_code=502, detail=f"LiteLLM error: {e.response.text}")
+            except httpx.RequestError as e:
+                raise HTTPException(status_code=503, detail=f"LiteLLM unreachable: {e}")
+
+            data = resp.json()
+            usage = data.get("usage", {})
+            total_usage["prompt_tokens"] += usage.get("prompt_tokens", 0)
+            total_usage["completion_tokens"] += usage.get("completion_tokens", 0)
+            model_used = data.get("model", "tip-generator")
+
+            last_raw = data["choices"][0]["message"]["content"]
+            try:
+                items = _parse_llm_json(last_raw)
+                break
+            except (json.JSONDecodeError, ValueError) as e:
+                last_parse_error = str(e)
+                # Feed the bad reply back so the model can self-correct
+                messages.append({"role": "assistant", "content": last_raw})
+                messages.append({"role": "user", "content": _RETRY_SUFFIX})
+        else:
+            raise HTTPException(
+                status_code=502,
+                detail=f"LLM returned invalid JSON after {_MAX_GENERATE_RETRIES} retries: "
+                       f"{last_parse_error}\n{last_raw[:200]}",
+            )
+
+    candidates = [
+        TipCandidate(
+            id=item.get("id", f"tip-{i}"),
+            content=item.get("content", ""),
+            rationale=item.get("rationale"),
+        )
+        for i, item in enumerate(items)
+    ]
+
+    return GenerateResponse(
+        candidates=candidates,
+        model=model_used,
+        prompt_tokens=total_usage["prompt_tokens"],
+        completion_tokens=total_usage["completion_tokens"],
+    )
+
+
+@app.post("/score", response_model=ScoreResponse)
+def score(req: ScoreRequest) -> ScoreResponse:
+    if not req.candidates:
+        raise HTTPException(status_code=422, detail="No candidates")
+
+    A, b, meta = load_state(req.user_id)
+    try:
+        A_inv = np.linalg.inv(A)
+    except np.linalg.LinAlgError:
+        A_inv = np.identity(D, dtype=np.float64)
+
+    theta = A_inv @ b
+
+    best_id = None
+    best_score = -float("inf")
+    best_features: dict = {}
+
+    for candidate in req.candidates:
+        feat_dict = {
+            "hour_of_day": req.context.hour_of_day,
+            "is_overdue": candidate.features.is_overdue,
+            "task_age_days": candidate.features.task_age_days,
+            "priority": candidate.features.priority,
+        }
+        x = build_feature_vector(feat_dict)
+        exploit = float(theta @ x)
+        explore = ALPHA * math.sqrt(float(x @ A_inv @ x))
+        ucb = exploit + explore
+        if ucb > best_score:
+            best_score = ucb
+            best_id = candidate.id
+            best_features = feat_dict
+
+    # Log to feature history ring buffer
+    history = get_feature_history(req.user_id)
+    history.append({
+        "ts": time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime()),
+        "features": best_features,
+        "score": best_score,
+        "tip_id": best_id,
+    })
+
+    # Update meta stats
+    meta["pulls"] = meta.get("pulls", 0) + 1
+    meta["last_updated"] = time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime())
+    save_state(req.user_id, A, b, meta)
+
+    return ScoreResponse(tip_id=best_id, score=best_score, policy="linucb-v1")
+
+
+@app.post("/reward", response_model=RewardResponse)
+def reward(req: RewardRequest) -> RewardResponse:
+    A, b, meta = load_state(req.user_id)
+    feat_dict = {
+        "hour_of_day": req.features.hour_of_day,
+        "is_overdue": req.features.is_overdue,
+        "task_age_days": req.features.task_age_days,
+        "priority": req.features.priority,
+    }
+    x = build_feature_vector(feat_dict)
+    A += np.outer(x, x)
+    b += req.reward * x
+
+    # Track cumulative reward in meta
+    meta["cumulative_reward"] = meta.get("cumulative_reward", 0.0) + req.reward
+    meta["reward_count"] = meta.get("reward_count", 0) + 1
+    meta["last_updated"] = time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime())
+
+    save_state(req.user_id, A, b, meta)
+    return RewardResponse(ok=True)
+
+
+@app.post("/score/egreedy", response_model=ScoreResponse)
+def score_egreedy(req: ScoreRequest) -> ScoreResponse:
+    """ε-greedy policy with d=7 features (adds day-of-week encoding).
+
+    Exploration: pick uniformly at random with probability ε.
+    Exploitation: pick argmax of linear payoff estimate θ·x.
+    Differs from LinUCB in: no UCB bonus, richer feature space.
+    """
+    if not req.candidates:
+        raise HTTPException(status_code=422, detail="No candidates")
+
+    A, b, meta = load_state7(req.user_id)
+    try:
+        A_inv = np.linalg.inv(A)
+    except np.linalg.LinAlgError:
+        A_inv = np.identity(D7, dtype=np.float64)
+    theta = A_inv @ b
+
+    dow = req.context.day_of_week
+    exploring = np.random.random() < EPSILON
+
+    if exploring:
+        chosen = req.candidates[np.random.randint(len(req.candidates))]
+        feat_dict = {
+            "hour_of_day": req.context.hour_of_day,
+            "is_overdue": chosen.features.is_overdue,
+            "task_age_days": chosen.features.task_age_days,
+            "priority": chosen.features.priority,
+        }
+        x = build_feature_vector_7(feat_dict, dow)
+        best_score = float(theta @ x)
+        best_id = chosen.id
+    else:
+        best_id = None
+        best_score = -float("inf")
+        feat_dict = {}
+        for candidate in req.candidates:
+            fd = {
+                "hour_of_day": req.context.hour_of_day,
+                "is_overdue": candidate.features.is_overdue,
+                "task_age_days": candidate.features.task_age_days,
+                "priority": candidate.features.priority,
+            }
+            x = build_feature_vector_7(fd, dow)
+            s = float(theta @ x)
+            if s > best_score:
+                best_score = s
+                best_id = candidate.id
+                feat_dict = fd
+
+    history = get_feature_history(req.user_id)
+    history.append({
+        "ts": time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime()),
+        "features": {**feat_dict, "day_of_week": dow, "exploring": exploring},
+        "score": best_score,
+        "tip_id": best_id,
+        "policy": "egreedy-v1",
+    })
+
+    meta["pulls"] = meta.get("pulls", 0) + 1
+    meta["explore_count"] = meta.get("explore_count", 0) + int(exploring)
+    meta["last_updated"] = time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime())
+    save_state7(req.user_id, A, b, meta)
+
+    return ScoreResponse(tip_id=best_id, score=best_score, policy="egreedy-v1")
+
+
+@app.post("/reward/egreedy", response_model=RewardResponse)
+def reward_egreedy(req: RewardRequest) -> RewardResponse:
+    """Update ε-greedy ridge estimator with observed reward."""
+    A, b, meta = load_state7(req.user_id)
+    feat_dict = {
+        "hour_of_day": req.features.hour_of_day,
+        "is_overdue": req.features.is_overdue,
+        "task_age_days": req.features.task_age_days,
+        "priority": req.features.priority,
+    }
+    x = build_feature_vector_7(feat_dict, day_of_week=req.day_of_week)
+    A += np.outer(x, x)
+    b += req.reward * x
+
+    meta["cumulative_reward"] = meta.get("cumulative_reward", 0.0) + req.reward
+    meta["reward_count"] = meta.get("reward_count", 0) + 1
+    meta["last_updated"] = time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime())
+    save_state7(req.user_id, A, b, meta)
+    return RewardResponse(ok=True)
+
+
+@app.get("/stats/egreedy/{user_id}")
+def stats_egreedy(user_id: str):
+    """ε-greedy policy stats — pulls, cumulative reward, θ vector."""
+    A, b, meta = load_state7(user_id)
+    try:
+        theta = (np.linalg.inv(A) @ b).tolist()
+    except np.linalg.LinAlgError:
+        theta = [0.0] * D7
+
+    pulls = meta.get("pulls", 0)
+    cumulative_reward = meta.get("cumulative_reward", 0.0)
+    reward_count = meta.get("reward_count", 0)
+    explore_count = meta.get("explore_count", 0)
+
+    return {
+        "user_id": user_id,
+        "policy": "egreedy-v1",
+        "pulls": pulls,
+        "reward_count": reward_count,
+        "cumulative_reward": cumulative_reward,
+        "estimated_mean_reward": cumulative_reward / reward_count if reward_count > 0 else 0.0,
+        "exploration_rate": explore_count / pulls if pulls > 0 else 0.0,
+        "theta": theta,
+        "feature_labels": ["hour_sin", "hour_cos", "is_overdue", "task_age", "priority", "dow_sin", "dow_cos"],
+        "last_updated": meta.get("last_updated"),
+    }
+
+
+@app.post("/reset/{user_id}", response_model=RewardResponse)
+def reset(user_id: str) -> RewardResponse:
+    """Reset per-user bandit state (admin action)."""
+    p = state_path(user_id)
+    if p.exists():
+        p.unlink()
+    p7 = state7_path(user_id)
+    if p7.exists():
+        p7.unlink()
+    if user_id in _feature_history:
+        _feature_history[user_id].clear()
+    return RewardResponse(ok=True)
+
+
+@app.get("/stats/{user_id}")
+def stats(user_id: str):
+    """Return current LinUCB state summary for a user."""
+    A, b, meta = load_state(user_id)
+    try:
+        A_inv = np.linalg.inv(A)
+        theta = (A_inv @ b).tolist()
+    except np.linalg.LinAlgError:
+        theta = [0.0] * D
+
+    pulls = meta.get("pulls", 0)
+    cumulative_reward = meta.get("cumulative_reward", 0.0)
+    reward_count = meta.get("reward_count", 0)
+    estimated_mean = cumulative_reward / reward_count if reward_count > 0 else 0.0
+
+    return {
+        "user_id": user_id,
+        "pulls": pulls,
+        "reward_count": reward_count,
+        "cumulative_reward": cumulative_reward,
+        "estimated_mean_reward": estimated_mean,
+        "theta": theta,
+        "last_updated": meta.get("last_updated"),
+    }
+
+
+@app.get("/features/{user_id}")
+def features(user_id: str):
+    """Return recent feature vectors logged at scoring time."""
+    history = get_feature_history(user_id)
+    return {
+        "user_id": user_id,
+        "history": list(history),
+    }

ml/serving/package.json

@@ -0,0 +1,10 @@
+{
+  "name": "@oo/ml-serving",
+  "version": "0.0.0",
+  "private": true,
+  "scripts": {
+    "dev": ".venv/bin/uvicorn main:app --reload --port 8000",
+    "start": ".venv/bin/uvicorn main:app --port 8000",
+    "test": ".venv/bin/python -m pytest tests/ -v"
+  }
+}

ml/serving/requirements-dev.txt

@@ -0,0 +1,4 @@
+-r requirements.txt
+pytest==8.3.5
+pytest-asyncio==0.24.0
+httpx==0.28.1

ml/serving/requirements.txt

@@ -0,0 +1,6 @@
+fastapi==0.115.6
+uvicorn[standard]==0.32.1
+pydantic==2.10.4
+numpy>=1.26.0
+httpx>=0.27.0
+anthropic>=0.40.0

ml/serving/tests/test_generate.py

@@ -0,0 +1,225 @@
+"""
+Tests for POST /generate — LiteLLM gateway.
+LiteLLM is mocked; no real network calls.
+"""
+import json
+import pytest
+import httpx
+from unittest.mock import AsyncMock, patch
+from httpx import AsyncClient, ASGITransport, Response
+
+from main import app, _build_prompt, PromptContext
+
+
+def _litellm_response(candidates: list[dict]) -> Response:
+    import httpx
+    body = {
+        "model": "tip-generator",
+        "choices": [{"message": {"content": json.dumps(candidates)}}],
+        "usage": {"prompt_tokens": 10, "completion_tokens": 20},
+    }
+    req = httpx.Request("POST", "http://litellm/chat/completions")
+    return Response(200, json=body, request=req)
+
+
+@pytest.mark.anyio
+async def test_generate_returns_candidates():
+    fake_items = [
+        {"id": "tip-1", "content": "Do the overdue task now.", "rationale": "It's been waiting."},
+        {"id": "tip-2", "content": "Take a 5-minute break.", "rationale": "You've been working long."},
+    ]
+    mock_resp = _litellm_response(fake_items)
+
+    with patch("main.httpx.AsyncClient") as MockClient:
+        instance = AsyncMock()
+        instance.post = AsyncMock(return_value=mock_resp)
+        instance.__aenter__ = AsyncMock(return_value=instance)
+        instance.__aexit__ = AsyncMock(return_value=False)
+        MockClient.return_value = instance
+
+        async with AsyncClient(transport=ASGITransport(app=app), base_url="http://test") as client:
+            resp = await client.post("/generate", json={"user_id": "u1", "n": 2})
+
+    assert resp.status_code == 200
+    data = resp.json()
+    assert len(data["candidates"]) == 2
+    assert data["candidates"][0]["id"] == "tip-1"
+    assert data["model"] == "tip-generator"
+
+
+@pytest.mark.anyio
+async def test_generate_strips_markdown_fence():
+    fake_items = [{"id": "tip-a", "content": "Focus.", "rationale": "Now."}]
+    fenced = "```json\n" + json.dumps(fake_items) + "\n```"
+    body = {
+        "model": "tip-generator",
+        "choices": [{"message": {"content": fenced}}],
+        "usage": {},
+    }
+    req = httpx.Request("POST", "http://litellm/chat/completions")
+    mock_resp = Response(200, json=body, request=req)
+
+    with patch("main.httpx.AsyncClient") as MockClient:
+        instance = AsyncMock()
+        instance.post = AsyncMock(return_value=mock_resp)
+        instance.__aenter__ = AsyncMock(return_value=instance)
+        instance.__aexit__ = AsyncMock(return_value=False)
+        MockClient.return_value = instance
+
+        async with AsyncClient(transport=ASGITransport(app=app), base_url="http://test") as client:
+            resp = await client.post("/generate", json={"user_id": "u1"})
+
+    assert resp.status_code == 200
+    assert resp.json()["candidates"][0]["id"] == "tip-a"
+
+
+@pytest.mark.anyio
+async def test_generate_503_on_unreachable():
+    import httpx as _httpx
+
+    with patch("main.httpx.AsyncClient") as MockClient:
+        instance = AsyncMock()
+        instance.post = AsyncMock(side_effect=_httpx.ConnectError("refused"))
+        instance.__aenter__ = AsyncMock(return_value=instance)
+        instance.__aexit__ = AsyncMock(return_value=False)
+        MockClient.return_value = instance
+
+        async with AsyncClient(transport=ASGITransport(app=app), base_url="http://test") as client:
+            resp = await client.post("/generate", json={"user_id": "u1"})
+
+    assert resp.status_code == 503
+
+
+def test_build_prompt_includes_tasks():
+    ctx = PromptContext(
+        tasks=[{"content": "Write report", "priority": 4, "is_overdue": True, "due_date": "2026-04-15"}],
+        hour_of_day=9,
+        day_of_week=2,
+    )
+    prompt = _build_prompt(ctx, n=3)
+    assert "Write report" in prompt
+    assert "09:00" in prompt
+    assert "Generate 3 tips" in prompt
+
+
+def test_build_prompt_truncates_at_five():
+    tasks = [{"content": f"Task {i}", "priority": 1, "is_overdue": False, "due_date": None} for i in range(8)]
+    ctx = PromptContext(tasks=tasks, hour_of_day=12)
+    prompt = _build_prompt(ctx, n=2)
+    assert "Task 4" in prompt
+    assert "Task 5" not in prompt
+
+
+def test_build_prompt_extra_fields():
+    ctx = PromptContext(tasks=[], hour_of_day=8, extra={"mood": "focused", "energy": "high"})
+    prompt = _build_prompt(ctx, n=1)
+    assert "mood: focused" in prompt
+    assert "energy: high" in prompt
+
+
+def test_build_prompt_empty_tasks_no_task_line():
+    ctx = PromptContext(tasks=[], hour_of_day=10)
+    prompt = _build_prompt(ctx, n=2)
+    assert "Tasks:" not in prompt
+    assert "Generate 2 tips" in prompt
+
+
+@pytest.mark.anyio
+async def test_generate_retry_succeeds_on_second_attempt():
+    """First response is invalid JSON; second is valid. Should return 200."""
+    valid_items = [{"id": "tip-ok", "content": "Retry worked.", "rationale": "Second try."}]
+    bad_req = httpx.Request("POST", "http://litellm/chat/completions")
+    bad_resp = Response(200, json={
+        "model": "tip-generator",
+        "choices": [{"message": {"content": "this is not json"}}],
+        "usage": {},
+    }, request=bad_req)
+    good_resp = _litellm_response(valid_items)
+
+    with patch("main.httpx.AsyncClient") as MockClient:
+        instance = AsyncMock()
+        instance.post = AsyncMock(side_effect=[bad_resp, good_resp])
+        instance.__aenter__ = AsyncMock(return_value=instance)
+        instance.__aexit__ = AsyncMock(return_value=False)
+        MockClient.return_value = instance
+
+        async with AsyncClient(transport=ASGITransport(app=app), base_url="http://test") as client:
+            resp = await client.post("/generate", json={"user_id": "u1", "n": 1})
+
+    assert resp.status_code == 200
+    assert resp.json()["candidates"][0]["id"] == "tip-ok"
+    assert instance.post.call_count == 2
+    # Retry message should include the correction suffix
+    second_call_messages = instance.post.call_args_list[1][1]["json"]["messages"]
+    assert any("not valid JSON" in m["content"] for m in second_call_messages)
+
+
+@pytest.mark.anyio
+async def test_generate_502_after_all_retries_exhausted():
+    """All attempts return invalid JSON → 502."""
+    bad_req = httpx.Request("POST", "http://litellm/chat/completions")
+
+    def _bad_resp():
+        return Response(200, json={
+            "model": "tip-generator",
+            "choices": [{"message": {"content": "not json at all"}}],
+            "usage": {},
+        }, request=bad_req)
+
+    from main import _MAX_GENERATE_RETRIES
+    responses = [_bad_resp() for _ in range(1 + _MAX_GENERATE_RETRIES)]
+
+    with patch("main.httpx.AsyncClient") as MockClient:
+        instance = AsyncMock()
+        instance.post = AsyncMock(side_effect=responses)
+        instance.__aenter__ = AsyncMock(return_value=instance)
+        instance.__aexit__ = AsyncMock(return_value=False)
+        MockClient.return_value = instance
+
+        async with AsyncClient(transport=ASGITransport(app=app), base_url="http://test") as client:
+            resp = await client.post("/generate", json={"user_id": "u1"})
+
+    assert resp.status_code == 502
+    assert "retries" in resp.json()["detail"]
+
+
+@pytest.mark.anyio
+async def test_generate_502_on_upstream_http_error():
+    """LiteLLM returns 500 → HTTPStatusError → 502."""
+    err_req = httpx.Request("POST", "http://litellm/chat/completions")
+    err_resp = Response(500, text="internal error", request=err_req)
+
+    with patch("main.httpx.AsyncClient") as MockClient:
+        instance = AsyncMock()
+        instance.post = AsyncMock(side_effect=httpx.HTTPStatusError(
+            "500", request=err_req, response=err_resp
+        ))
+        instance.__aenter__ = AsyncMock(return_value=instance)
+        instance.__aexit__ = AsyncMock(return_value=False)
+        MockClient.return_value = instance
+
+        async with AsyncClient(transport=ASGITransport(app=app), base_url="http://test") as client:
+            resp = await client.post("/generate", json={"user_id": "u1"})
+
+    assert resp.status_code == 502
+    assert "LiteLLM error" in resp.json()["detail"]
+
+
+def test_parse_llm_json_bare_fence():
+    from main import _parse_llm_json
+    raw = "```\n[{\"id\":\"x\",\"content\":\"hi\"}]\n```"
+    items = _parse_llm_json(raw)
+    assert items[0]["id"] == "x"
+
+
+def test_parse_llm_json_no_fence():
+    from main import _parse_llm_json
+    raw = '[{"id":"plain","content":"no fence"}]'
+    items = _parse_llm_json(raw)
+    assert items[0]["id"] == "plain"
+
+
+def test_parse_llm_json_raises_on_invalid():
+    from main import _parse_llm_json
+    with pytest.raises((ValueError, Exception)):
+        _parse_llm_json("this is not json")

ml/serving/tests/test_score.py

@@ -0,0 +1,261 @@
+"""
+Unit tests for ml/serving — feature building and scoring contract.
+Run with: pytest ml/serving/tests/
+"""
+import math
+import pytest
+from httpx import AsyncClient, ASGITransport
+
+from main import app, build_feature_vector
+
+
+class TestFeatureVector:
+    def test_shape(self):
+        v = build_feature_vector({"hour_of_day": 8, "is_overdue": True, "task_age_days": 3, "priority": 3})
+        assert v.shape == (5,)
+
+    def test_hour_encoding_noon(self):
+        v = build_feature_vector({"hour_of_day": 12})
+        # sin(2π * 12/24) = sin(π) ≈ 0
+        assert abs(v[0]) < 1e-10
+        # cos(2π * 12/24) = cos(π) = -1
+        assert abs(v[1] - (-1.0)) < 1e-10
+
+    def test_hour_encoding_midnight(self):
+        v = build_feature_vector({"hour_of_day": 0})
+        # sin(0) = 0
+        assert abs(v[0]) < 1e-10
+        # cos(0) = 1
+        assert abs(v[1] - 1.0) < 1e-10
+
+    def test_hour_encoding_6am(self):
+        v = build_feature_vector({"hour_of_day": 6})
+        # sin(2π * 6/24) = sin(π/2) = 1
+        assert abs(v[0] - 1.0) < 1e-10
+        # cos(π/2) = 0
+        assert abs(v[1]) < 1e-10
+
+    def test_age_clipped_at_30(self):
+        v_long = build_feature_vector({"task_age_days": 100})
+        v_cap = build_feature_vector({"task_age_days": 30})
+        assert v_long[3] == v_cap[3] == 1.0
+
+    def test_age_zero(self):
+        v = build_feature_vector({"task_age_days": 0})
+        assert v[3] == pytest.approx(0.0)
+
+    def test_age_15_days_normalised(self):
+        v = build_feature_vector({"task_age_days": 15})
+        assert v[3] == pytest.approx(0.5)
+
+    def test_priority_normalised(self):
+        v1 = build_feature_vector({"priority": 1})
+        v4 = build_feature_vector({"priority": 4})
+        assert v1[4] == pytest.approx(0.0)
+        assert v4[4] == pytest.approx(1.0)
+
+    def test_priority_2_and_3(self):
+        v2 = build_feature_vector({"priority": 2})
+        v3 = build_feature_vector({"priority": 3})
+        assert v2[4] == pytest.approx(1 / 3)
+        assert v3[4] == pytest.approx(2 / 3)
+
+    def test_is_overdue_true(self):
+        v = build_feature_vector({"is_overdue": True})
+        assert v[2] == 1.0
+
+    def test_is_overdue_false(self):
+        v = build_feature_vector({"is_overdue": False})
+        assert v[2] == 0.0
+
+    def test_defaults_when_no_keys(self):
+        v = build_feature_vector({})
+        # hour=12 → sin(π)≈0, cos(π)=-1
+        assert abs(v[0]) < 1e-10
+        assert abs(v[1] - (-1.0)) < 1e-10
+        assert v[2] == 0.0   # is_overdue=False
+        assert v[3] == 0.0   # task_age_days=0
+        assert v[4] == 0.0   # priority=1 → (1-1)/3=0
+
+
+@pytest.mark.asyncio
+async def test_health():
+    async with AsyncClient(transport=ASGITransport(app=app), base_url="http://test") as client:
+        r = await client.get("/health")
+    assert r.status_code == 200
+    assert r.json()["ok"] is True
+
+
+@pytest.mark.asyncio
+async def test_score_returns_a_candidate():
+    payload = {
+        "user_id": "test-user",
+        "candidates": [
+            {"id": "t:1", "content": "Task A", "source": "todoist", "source_id": "1",
+             "features": {"is_overdue": True, "task_age_days": 2, "priority": 3}},
+            {"id": "t:2", "content": "Task B", "source": "todoist", "source_id": "2",
+             "features": {"is_overdue": False, "task_age_days": 0, "priority": 1}},
+        ],
+        "context": {"hour_of_day": 9, "day_of_week": 1},
+    }
+    async with AsyncClient(transport=ASGITransport(app=app), base_url="http://test") as client:
+        r = await client.post("/score", json=payload)
+    assert r.status_code == 200
+    body = r.json()
+    assert body["tip_id"] in {"t:1", "t:2"}
+    assert "policy" in body
+    assert body["policy"] == "linucb-v1"
+    assert isinstance(body["score"], float)
+
+
+@pytest.mark.asyncio
+async def test_score_single_candidate_always_selected():
+    """With a single candidate there is no choice — it must be returned."""
+    payload = {
+        "user_id": "solo-user",
+        "candidates": [
+            {"id": "only:1", "content": "Only task", "source": "todoist",
+             "features": {"is_overdue": False, "task_age_days": 0, "priority": 1}},
+        ],
+        "context": {"hour_of_day": 10, "day_of_week": 0},
+    }
+    async with AsyncClient(transport=ASGITransport(app=app), base_url="http://test") as client:
+        r = await client.post("/score", json=payload)
+    assert r.status_code == 200
+    assert r.json()["tip_id"] == "only:1"
+
+
+@pytest.mark.asyncio
+async def test_score_empty_candidates_returns_422():
+    payload = {"user_id": "u", "candidates": [], "context": {"hour_of_day": 9, "day_of_week": 1}}
+    async with AsyncClient(transport=ASGITransport(app=app), base_url="http://test") as client:
+        r = await client.post("/score", json=payload)
+    assert r.status_code == 422
+
+
+@pytest.mark.asyncio
+async def test_reward_accepted():
+    payload = {
+        "user_id": "reward-user",
+        "tip_id": "t:1",
+        "reward": 1.0,
+        "features": {"hour_of_day": 9, "is_overdue": True, "task_age_days": 2, "priority": 3},
+    }
+    async with AsyncClient(transport=ASGITransport(app=app), base_url="http://test") as client:
+        r = await client.post("/reward", json=payload)
+    assert r.status_code == 200
+    assert r.json()["ok"] is True
+
+
+@pytest.mark.asyncio
+async def test_reward_updates_stats():
+    """Posting a reward should increase cumulative_reward in /stats."""
+    user_id = "reward-stats-user"
+    async with AsyncClient(transport=ASGITransport(app=app), base_url="http://test") as client:
+        r0 = await client.get(f"/stats/{user_id}")
+        before = r0.json()["cumulative_reward"]
+
+        await client.post("/reward", json={
+            "user_id": user_id,
+            "tip_id": "tip:x",
+            "reward": 1.0,
+            "features": {"hour_of_day": 8, "is_overdue": False, "task_age_days": 0, "priority": 2},
+        })
+        r1 = await client.get(f"/stats/{user_id}")
+    assert r1.json()["cumulative_reward"] == pytest.approx(before + 1.0)
+
+
+@pytest.mark.asyncio
+async def test_score_increments_pulls():
+    user_id = "pull-counter-user"
+    payload = {
+        "user_id": user_id,
+        "candidates": [
+            {"id": "t:p1", "content": "Pull task", "source": "todoist",
+             "features": {"is_overdue": False, "task_age_days": 1, "priority": 2}},
+        ],
+        "context": {"hour_of_day": 10, "day_of_week": 2},
+    }
+    async with AsyncClient(transport=ASGITransport(app=app), base_url="http://test") as client:
+        r0 = await client.get(f"/stats/{user_id}")
+        pulls_before = r0.json()["pulls"]
+
+        await client.post("/score", json=payload)
+        await client.post("/score", json=payload)
+
+        r1 = await client.get(f"/stats/{user_id}")
+    assert r1.json()["pulls"] == pulls_before + 2
+
+
+@pytest.mark.asyncio
+async def test_reset_clears_state():
+    user_id = "reset-user"
+    async with AsyncClient(transport=ASGITransport(app=app), base_url="http://test") as client:
+        # Score once to build state
+        await client.post("/score", json={
+            "user_id": user_id,
+            "candidates": [
+                {"id": "t:r", "content": "Reset task", "source": "todoist",
+                 "features": {"is_overdue": True, "task_age_days": 5, "priority": 4}},
+            ],
+            "context": {"hour_of_day": 14, "day_of_week": 3},
+        })
+        r_reset = await client.post(f"/reset/{user_id}")
+        assert r_reset.json()["ok"] is True
+
+        r_stats = await client.get(f"/stats/{user_id}")
+    assert r_stats.json()["pulls"] == 0
+
+
+@pytest.mark.asyncio
+async def test_features_endpoint_returns_history():
+    user_id = "features-user"
+    payload = {
+        "user_id": user_id,
+        "candidates": [
+            {"id": "t:f1", "content": "Feature task", "source": "todoist",
+             "features": {"is_overdue": False, "task_age_days": 0, "priority": 1}},
+        ],
+        "context": {"hour_of_day": 7, "day_of_week": 0},
+    }
+    async with AsyncClient(transport=ASGITransport(app=app), base_url="http://test") as client:
+        await client.post("/score", json=payload)
+        r = await client.get(f"/features/{user_id}")
+    body = r.json()
+    assert r.status_code == 200
+    assert "history" in body
+    assert len(body["history"]) >= 1
+    entry = body["history"][-1]
+    assert "ts" in entry
+    assert "score" in entry
+    assert "tip_id" in entry
+
+
+@pytest.mark.asyncio
+async def test_stats_for_fresh_user():
+    """A user with no history should return zero/default stats without error."""
+    async with AsyncClient(transport=ASGITransport(app=app), base_url="http://test") as client:
+        r = await client.get("/stats/brand-new-user-xyz-abc")
+    body = r.json()
+    assert r.status_code == 200
+    assert body["pulls"] == 0
+    assert body["cumulative_reward"] == 0.0
+    assert body["estimated_mean_reward"] == 0.0
+
+
+@pytest.mark.asyncio
+async def test_reward_negative_value():
+    """Dismissing a tip should decrease cumulative_reward."""
+    user_id = "dismiss-user-neg"
+    async with AsyncClient(transport=ASGITransport(app=app), base_url="http://test") as client:
+        r0 = await client.get(f"/stats/{user_id}")
+        before = r0.json()["cumulative_reward"]
+
+        await client.post("/reward", json={
+            "user_id": user_id,
+            "tip_id": "t:neg",
+            "reward": -1.0,
+            "features": {"hour_of_day": 20, "is_overdue": False, "task_age_days": 0, "priority": 1},
+        })
+        r1 = await client.get(f"/stats/{user_id}")
+    assert r1.json()["cumulative_reward"] == pytest.approx(before - 1.0)

package.json

@@ -0,0 +1,22 @@
+{
+  "name": "oo-monorepo",
+  "private": true,
+  "version": "0.0.0",
+  "packageManager": "pnpm@10.33.0",
+  "scripts": {
+    "build": "turbo build",
+    "dev": "turbo dev",
+    "lint": "turbo lint",
+    "type-check": "turbo type-check",
+    "test": "turbo test",
+    "clean": "turbo clean"
+  },
+  "pnpm": {
+    "onlyBuiltDependencies": ["better-sqlite3", "esbuild", "sharp"]
+  },
+  "devDependencies": {
+    "turbo": "^2.3.3",
+    "typescript": "^5.7.3",
+    "@types/node": "^22.10.5"
+  }
+}