Adds four InferredParams (all TTL=24h, min_history=50 except preferred_hour=10):
- quiet_start / quiet_end: longest contiguous below-baseline hour run (HH:MM)
- peak_hours: top-quartile done-event hours, sorted ascending
- tz: cold-start only ("UTC"); populated from auth provider, no inference function
compute() updated:
- in_quiet check (quiet window) takes precedence over peak hours
- in_peak emits "peak productivity hour" language when current hour is in peak_hours
- approaching peak (within 2h) surfaces for orchestrator timing
- tz surfaced in snippet header when not UTC
- snapshot adds peak_hours, in_quiet, in_peak, tz
- Agent bumped to v1.2.0
- 21 new tests: night-owl, early-bird, shift-worker, quiet/peak snippet rendering
- Fixed test_snapshot_keys in test_agents.py to include new snapshot fields
Closes#112
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Each agent now exports a module-level MANIFEST declaring id, version,
pref_schema, required_consents, ttl_sec, and silenced_in_contexts. The
registry surfaces both the agent and its manifest, and rejects on
mismatch so the two cannot drift.
ml/serving exposes GET /agents/registry; services/api proxies it as
GET /api/agents/registry with a 60s in-process cache so admin pageviews
don't hammer upstream. Failures aren't cached.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Adds ml/agents/ — five specialised sub-agents (overdue_task, momentum,
time_of_day, recent_patterns, focus_area) each producing a prompt snippet
from user signals. A registry wires them up; the orchestrator prompt in
ml/serving/prompts.py synthesises their outputs into one tip via LiteLLM.
Also wires /api/agents route in the API and updates the Dockerfile to copy
the full ml/ tree with PYTHONPATH=/app so agent imports resolve correctly.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
