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

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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>
This commit is contained in:
alvis
2026-05-05 11:21:10 +00:00
parent ad6747c242
commit afb0e9b0cb
8 changed files with 383 additions and 26 deletions
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ml/agents/tests/test_agents.py
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@@ -243,7 +243,7 @@ class TestFocusAreaAgent:
def test_snapshot_keys(self):
out = self.agent.compute(_inp(tasks=[_task("T1", project_id="A")]))
assert {"top_project", "top_task_count", "top_overdue_count", "project_count"} == set(out.signals_snapshot)
assert {"top_project", "top_task_count", "top_overdue_count", "project_count", "preferred_areas"} == set(out.signals_snapshot)
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