feat(agents): per-agent inference — momentum, overdue-task, recent-patterns, focus-area (ADR-0014 step 7)

All four agents bumped to v1.1.0.

momentum (#114): infers engagement_trend ('up'|'stable'|'down') by comparing
done-rate in the last 7 days vs the prior 7 days. Agent surfaces the trend
in its snippet ("trending up — build on the momentum").

overdue-task (#115): infers lateness_tolerance_days (0/1/2) from snooze rate.
Agent now filters tasks against the tolerance so low-urgency users aren't
nagged about tasks that are only hours overdue.

recent-patterns (#116): infers window_days (7/14/30) from feedback event
density — sparse users get a wider window so the snippet isn't always empty.

focus-area (#113): no inferred params (project-level feedback linkage needed,
tracked under #78). preferred_areas pref was declared but ignored; agent now
honours it as a tiebreaker and mentions it in the snippet.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

ml/agents/recent_patterns.py

@@ -1,17 +1,32 @@
 from __future__ import annotations
+
 from collections import Counter
 from datetime import datetime, timezone
 from typing import ClassVar
-from .base import BaseAgent, AgentInput, AgentOutput
-from .manifest import AgentManifest
 
-_SEVEN_DAYS_S = 7 * 86_400
+from .base import BaseAgent, AgentInput, AgentOutput
+from .inference.history import UserHistory
+from .manifest import AgentManifest, InferredParam
+
+
+def _infer_window_days(history: UserHistory) -> int:
+    """Infer the optimal lookback window from feedback event density.
+
+    More events per day → a shorter window captures the user's current state
+    accurately. Sparse feedback → widen the window to gather signal.
+    """
+    n = len(history.events)
+    if n >= 14:
+        return 7
+    if n >= 7:
+        return 14
+    return 30
 
 
 MANIFEST = AgentManifest(
     id="recent-patterns",
-    version="1.0.0",
-    description="Surfaces the user's reaction pattern from the last 7 days of feedback.",
+    version="1.1.0",  # bumped: window_days InferredParam added (#116)
+    description="Surfaces the user's reaction pattern from recent feedback.",
     pref_schema={
         "type": "object",
         "additionalProperties": False,
@@ -29,20 +44,32 @@ MANIFEST = AgentManifest(
     required_consents=["data:core", "agent:recent-patterns"],
     output_contract={"type": "snippet", "format": "free_text"},
     ttl_sec=86_400,
+    inferred_params=[
+        InferredParam(
+            key="window_days",
+            ttl_sec=86_400,        # recompute daily alongside snippet
+            cold_start_default=7,
+            min_history=5,
+            infer=_infer_window_days,
+        ),
+    ],
 )
 
 
 class RecentPatternsAgent(BaseAgent):
-    """Surfaces the user's reaction pattern from the last 7 days of feedback."""
+    """Surfaces the user's reaction pattern from recent feedback."""
     agent_id: ClassVar[str] = MANIFEST.id
     ttl_seconds: ClassVar[int] = MANIFEST.ttl_sec
     version: ClassVar[str] = MANIFEST.version
 
     def compute(self, inp: AgentInput) -> AgentOutput:
+        window_days = max(1, int(inp.agent_prefs.get("window_days", 7)))
+        window_s = window_days * 86_400
         now_ts = inp.now.timestamp()
+
         recent = [
             f for f in inp.feedback_history
-            if self._age_s(f.get("created_at", ""), now_ts) <= _SEVEN_DAYS_S
+            if self._age_s(f.get("created_at", ""), now_ts) <= window_s
         ]
 
         counts: Counter[str] = Counter(f.get("action") for f in recent)
@@ -50,13 +77,13 @@ class RecentPatternsAgent(BaseAgent):
         dwell_ms = inp.profile.get("mean_dwell_ms_30d")
 
         if total == 0:
-            prompt = "No tip reactions recorded in the last 7 days."
+            prompt = f"No tip reactions recorded in the last {window_days} days."
         else:
             done = counts.get("done", 0)
             dismissed = counts.get("dismiss", 0)
             snoozed = counts.get("snooze", 0)
             parts = [
-                f"Last 7 days: {total} tip reaction{'s' if total != 1 else ''} — "
+                f"Last {window_days} days: {total} tip reaction{'s' if total != 1 else ''} — "
                 f"{done} completed, {dismissed} dismissed, {snoozed} snoozed."
             ]
             if dwell_ms is not None:
@@ -74,6 +101,7 @@ class RecentPatternsAgent(BaseAgent):
             prompt = " ".join(parts)
 
         snapshot = {
+            "window_days": window_days,
             "recent_total": total,
             "action_counts": dict(counts),
             "mean_dwell_ms_30d": dwell_ms,