refactor(focus-area): output all clusters as context; remove scoring and preferred_areas

The agent no longer picks a winner — it summarises every cluster so the
orchestrator can decide what's relevant. Scoring by overdue count overlapped
with the overdue-task agent. preferred_areas (project-ID based, broken label
matching) removed entirely.

Output format: numbered list of areas with task titles included.
Snapshot: {cluster_count, clusters: [{label, task_count, tasks}]}.
Version bumped to 3.0.0; inferred_params cleared.

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

ml/agents/tests/test_per_agent_inference.py

@@ -627,86 +627,37 @@ class TestTimeOfDaySnippet:
         assert {"quiet_start", "quiet_end", "peak_hours", "tz"}.issubset(keys)
 
 
-# ── focus-area: preferred_areas wiring ───────────────────────────────────────
+# ── focus-area: cluster summary output ───────────────────────────────────────
 
-class TestFocusAreaPreferredAreas:
+class TestFocusAreaOutput:
     agent = FocusAreaAgent()
 
-    def _task(self, content: str, project_id: str, is_overdue: bool = False) -> dict:
-        return {"id": "t1", "content": content, "is_overdue": is_overdue,
+    def _task(self, content: str, project_id: str) -> dict:
+        return {"id": "t1", "content": content, "is_overdue": False,
                 "task_age_days": 2.0, "priority": 1, "project_id": project_id}
 
-    def test_preferred_area_wins_tie(self):
-        tasks = [
-            self._task("Work thing", "work"),
-            self._task("Home thing", "home"),
-        ]
-        out = self.agent.compute(_inp(tasks=tasks, agent_prefs={"preferred_areas": ["work"]}))
-        assert "work" in out.prompt_text
-        assert "matches the user's stated focus preferences" in out.prompt_text
-
-    def test_no_preferred_areas_uses_congestion_score(self):
-        tasks = [
-            self._task("W1", "work"),
-            self._task("H1", "home"),
-            self._task("H2", "home"),
-        ]
-        out = self.agent.compute(_inp(tasks=tasks))
-        # home has more tasks → wins without any preference
-        assert "home" in out.prompt_text
-
-    def test_snapshot_includes_preferred_areas(self):
-        tasks = [self._task("T", "work")]
-        out = self.agent.compute(_inp(tasks=tasks, agent_prefs={"preferred_areas": ["work"]}))
-        assert out.signals_snapshot["preferred_areas"] == ["work"]
-
-    def test_version_bumped(self):
+    def test_version(self):
         from ml.agents.focus_area import MANIFEST as FA_MANIFEST
-        assert FA_MANIFEST.version == "2.1.0"
+        assert FA_MANIFEST.version == "3.0.0"
 
-    def test_snapshot_uses_cluster_keys(self):
+    def test_all_clusters_in_output(self):
+        tasks = [self._task("Work thing", "work"), self._task("Home thing", "home")]
+        out = self.agent.compute(_inp(tasks=tasks))
+        assert "work" in out.prompt_text.lower()
+        assert "home" in out.prompt_text.lower()
+
+    def test_task_titles_in_output(self):
+        tasks = [self._task("Buy milk", "personal")]
+        out = self.agent.compute(_inp(tasks=tasks))
+        assert '"Buy milk"' in out.prompt_text
+
+    def test_snapshot_shape(self):
         tasks = [self._task("T", "work")]
         out = self.agent.compute(_inp(tasks=tasks))
-        assert "top_cluster_label" in out.signals_snapshot
-        assert "cluster_count" in out.signals_snapshot
-        assert "strategy" in out.signals_snapshot
+        public_keys = {k for k in out.signals_snapshot if not k.startswith("_")}
+        assert public_keys == {"cluster_count", "clusters"}
+        assert isinstance(out.signals_snapshot["clusters"], list)
 
-
-# ── focus-area: preferred_areas inference from task_completions (#113) ────────
-
-class TestFocusAreaPreferredAreasInference:
-    from ml.agents.focus_area import MANIFEST as _FA_MANIFEST
-
-    def _completion(self, project_id: str) -> TaskCompletion:
-        return _completion(project_id, lateness_days=0.0)
-
-    def test_cold_start_no_completions(self):
-        history = _history(completions=[])
+    def test_no_inferred_params(self):
         from ml.agents.focus_area import MANIFEST as FA_MANIFEST
-        result = run_inference(FA_MANIFEST, history)
-        assert result["preferred_areas"] == []
-
-    def test_top_two_projects_returned(self):
-        completions = (
-            [_completion("p1", 0)] * 8
-            + [_completion("p2", 0)] * 5
-            + [_completion("p3", 0)] * 2
-        )
-        history = _history(completions=completions)
-        from ml.agents.focus_area import MANIFEST as FA_MANIFEST
-        result = run_inference(FA_MANIFEST, history)
-        assert result["preferred_areas"] == ["p1", "p2"]
-
-    def test_single_project_returns_one(self):
-        completions = [_completion("work", 0)] * 6
-        history = _history(completions=completions)
-        from ml.agents.focus_area import MANIFEST as FA_MANIFEST
-        result = run_inference(FA_MANIFEST, history)
-        assert result["preferred_areas"] == ["work"]
-
-    def test_none_project_id_ignored(self):
-        completions = [_completion(None, 0)] * 5 + [_completion("real", 0)] * 3
-        history = _history(completions=completions)
-        from ml.agents.focus_area import MANIFEST as FA_MANIFEST
-        result = run_inference(FA_MANIFEST, history)
-        assert result["preferred_areas"] == ["real"]
+        assert FA_MANIFEST.inferred_params == []