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/overdue_task.py

@@ -1,12 +1,32 @@
 from __future__ import annotations
+
 from typing import ClassVar
+
 from .base import BaseAgent, AgentInput, AgentOutput
-from .manifest import AgentManifest
+from .inference.history import UserHistory
+from .manifest import AgentManifest, InferredParam
+
+
+def _infer_lateness_tolerance(history: UserHistory) -> int:
+    """Estimate how many days past due a task needs to be before the user acts.
+
+    High snooze rate → user doesn't act immediately → raise tolerance so the
+    agent doesn't nag them about tasks they'll handle in their own time.
+    """
+    total = len(history.events)
+    if total == 0:
+        return 0
+    snooze_rate = sum(1 for e in history.events if e.action == "snooze") / total
+    if snooze_rate > 0.40:
+        return 2
+    if snooze_rate > 0.20:
+        return 1
+    return 0
 
 
 MANIFEST = AgentManifest(
     id="overdue-task",
-    version="1.0.0",
+    version="1.1.0",  # bumped: lateness_tolerance_days InferredParam added (#115)
     description="Reports the user's overdue tasks by count and age.",
     pref_schema={
         "type": "object",
@@ -25,6 +45,15 @@ MANIFEST = AgentManifest(
     output_contract={"type": "snippet", "format": "free_text"},
     ttl_sec=3600,
     silenced_in_contexts=["vacation"],
+    inferred_params=[
+        InferredParam(
+            key="lateness_tolerance_days",
+            ttl_sec=86_400,          # recompute daily — snooze pattern shifts slowly
+            cold_start_default=0,
+            min_history=10,
+            infer=_infer_lateness_tolerance,
+        ),
+    ],
 )
 
 
@@ -35,7 +64,11 @@ class OverdueTaskAgent(BaseAgent):
     version: ClassVar[str] = MANIFEST.version
 
     def compute(self, inp: AgentInput) -> AgentOutput:
-        overdue = [t for t in inp.tasks if t.get("is_overdue")]
+        tolerance = max(0, int(inp.agent_prefs.get("lateness_tolerance_days", 0)))
+        overdue = [
+            t for t in inp.tasks
+            if t.get("is_overdue") and t.get("task_age_days", 0) >= tolerance
+        ]
         top = sorted(overdue, key=lambda t: -t.get("task_age_days", 0))[:3]
 
         if not overdue:
@@ -59,6 +92,7 @@ class OverdueTaskAgent(BaseAgent):
 
         snapshot = {
             "overdue_count": len(overdue),
+            "lateness_tolerance_days": tolerance,
             "top_overdue": [
                 {"content": t["content"], "task_age_days": t.get("task_age_days", 0)}
                 for t in top