merge: T58 scene compression + thread emission on close

chat/services/event_promotion.py

@@ -0,0 +1,149 @@
+"""Event-completion promotion (T56).
+
+When an event reaches ``status='completed'``, read its ``props_json``
+and emit promotion events into the appropriate state stores.
+Synchronous, no LLM. Skips when the event status is not ``completed``
+(cancelled / expired terminate the event without promoting).
+
+Props recognized:
+
+- ``acquired_objects: list[str]`` — emits a ``manual_edit`` with
+  ``target_kind="memory_pov_summary"`` per object on the host's memory
+  row, recording the acquisition. Phase 3 is a stub: it requires both
+  ``host_bot_id`` and ``host_memory_id`` (an existing memories.id) to
+  be present in props; missing either skips that object cleanly.
+  Phase 4 will introduce a real inventory schema.
+
+- ``knowledge_facts: list[{owner_id, target_id, fact}]`` — emits an
+  ``edge_update`` event on the directed ``owner_id -> target_id`` edge
+  with the fact appended to ``knowledge_facts``. The ``edge_update``
+  projector accepts ``knowledge_facts`` as a list and extends the
+  edge's stored ``knowledge_json``.
+
+- ``relationship_change: {summary, source_id, target_id}`` — emits a
+  ``manual_edit`` with ``target_kind="edge_summary"`` overwriting the
+  edge's ``summary`` field on the directed pair.
+
+Anything else stays in the closed event record (the projector kept
+the row; no further promotion).
+"""
+
+from __future__ import annotations
+
+from sqlite3 import Connection
+
+from chat.eventlog.log import append_and_apply
+from chat.state.events import get_event
+
+
+def promote_completed_event(
+    conn: Connection,
+    *,
+    event_id: str,
+    chat_id: str,
+    chat_clock_at: str | None,
+) -> dict:
+    """Read the completed event's props and emit promotion events.
+
+    Returns a dict of counts keyed by promoted artifact:
+    ``{"acquired_objects", "knowledge_facts", "relationship_change"}``.
+    Skips silently if the event row is missing or its status is not
+    ``completed`` — cancelled / expired events terminate without any
+    promotion.
+    """
+    counts = {
+        "acquired_objects": 0,
+        "knowledge_facts": 0,
+        "relationship_change": 0,
+    }
+
+    event = get_event(conn, event_id)
+    if event is None or event["status"] != "completed":
+        return counts
+
+    props = event.get("props") or {}
+
+    # acquired_objects: each becomes a memory_pov_summary edit (Phase 3
+    # stub). The manual_edit projector requires a valid memory rowid as
+    # ``target_id`` (it does ``int(target_id)``), so skip cleanly when
+    # neither a host_bot_id nor a host_memory_id is supplied.
+    host_bot_id = props.get("host_bot_id")
+    host_memory_id = props.get("host_memory_id")
+    for obj in props.get("acquired_objects", []) or []:
+        if host_bot_id is None or host_memory_id is None:
+            continue
+        append_and_apply(
+            conn,
+            kind="manual_edit",
+            payload={
+                "target_kind": "memory_pov_summary",
+                "target_id": host_memory_id,
+                "owner_id": host_bot_id,
+                "chat_id": chat_id,
+                "prior_value": "",
+                "new_value": f"Acquired: {obj}",
+                "source": "event_promotion",
+                "event_id": event_id,
+                "chat_clock_at": chat_clock_at,
+            },
+        )
+        counts["acquired_objects"] += 1
+
+    # knowledge_facts: each becomes an edge_update appending the fact.
+    for fact_entry in props.get("knowledge_facts", []) or []:
+        owner_id = fact_entry.get("owner_id")
+        target_id = fact_entry.get("target_id")
+        fact = fact_entry.get("fact", "")
+        if not owner_id or not target_id or not fact:
+            continue
+        append_and_apply(
+            conn,
+            kind="edge_update",
+            payload={
+                "source_id": owner_id,
+                "target_id": target_id,
+                "chat_id": chat_id,
+                "affinity_delta": 0,
+                "trust_delta": 0,
+                "knowledge_facts": [fact],
+                "last_interaction_at": chat_clock_at,
+                "last_interaction_chat_id": chat_id,
+                "source": "event_promotion",
+                "event_id": event_id,
+            },
+        )
+        counts["knowledge_facts"] += 1
+
+    # relationship_change: edge_summary manual_edit on the directed pair.
+    # The manual_edit projector for ``edge_summary`` keys on a
+    # ``target_id`` dict ``{source_id, target_id}`` (see
+    # chat/state/manual_edit.py); we shape the payload to match.
+    rc = props.get("relationship_change") or {}
+    if rc:
+        source_id = rc.get("source_id")
+        rc_target_id = rc.get("target_id")
+        summary = rc.get("summary", "")
+        if source_id and rc_target_id and summary:
+            append_and_apply(
+                conn,
+                kind="manual_edit",
+                payload={
+                    "target_kind": "edge_summary",
+                    "target_id": {
+                        "source_id": source_id,
+                        "target_id": rc_target_id,
+                    },
+                    "chat_id": chat_id,
+                    "prior_value": "",
+                    "new_value": summary,
+                    "source": "event_promotion",
+                    "event_id": event_id,
+                    "chat_clock_at": chat_clock_at,
+                },
+            )
+            counts["relationship_change"] += 1
+
+    return counts
+
+
+__all__ = ["promote_completed_event"]

chat/services/scene_summarize.py

@@ -29,6 +29,8 @@ keeps moving.
 from __future__ import annotations
 
 import json
+import uuid
+from datetime import datetime, timezone
 from sqlite3 import Connection
 
 from pydantic import BaseModel, Field
@@ -167,6 +169,7 @@ async def _summarize_and_apply_for_witness(
     you_name: str,
     dialogue: list[dict],
     timeout_s: float,
+    key_quotes_suffix: str = "",
 ) -> ScenePOVSummary:
     """Run :func:`summarize_scene` for one bot witness and apply the
     three projected updates (memory pov_summary rewrite, edge summary
@@ -175,6 +178,10 @@ async def _summarize_and_apply_for_witness(
     Tolerant of missing pieces in the same way Phase 1 was: no memory
     row -> skip the rewrite; no edge row -> skip the edge_summary write
     (the empty-default classifier output simply yields no rewrites).
+
+    ``key_quotes_suffix`` is appended verbatim to the per-POV summary
+    text before the rewrite lands (T58.1) — empty string is the no-op
+    default for low-significance scenes.
     """
     from chat.state.edges import get_edge
     from chat.state.entities import get_bot
@@ -206,6 +213,7 @@ async def _summarize_and_apply_for_witness(
             # Empty default -> skip the memory rewrite; the seeded
             # per-turn pov_summary stays in place.
             continue
+        new_value = pov.summary + key_quotes_suffix
         append_and_apply(
             conn,
             kind="manual_edit",
@@ -213,7 +221,7 @@ async def _summarize_and_apply_for_witness(
                 "target_kind": "memory_pov_summary",
                 "target_id": int(memory_id),
                 "prior_value": prior_pov,
-                "new_value": pov.summary,
+                "new_value": new_value,
             },
         )
 
@@ -255,6 +263,40 @@ async def _summarize_and_apply_for_witness(
     return pov
 
 
+def _build_key_quotes_suffix(conn: Connection, scene_id: int) -> str:
+    """If the scene's max-turn-significance is >= 2, build the
+    "Key quotes:" suffix from the top-3 highest-significance memory rows
+    (per requirements §11.1). Otherwise return the empty string so the
+    per-POV summaries collapse fully (low-significance scenes lose all
+    raw text in favor of the classifier rewrite).
+
+    Quote source is each memory's current ``pov_summary`` — the raw
+    per-turn narrative seeded by T21, since this helper is called BEFORE
+    the per-POV rewrite. Texts are truncated to 200 chars to bound
+    memory row growth across many witnesses.
+    """
+    row = conn.execute(
+        "SELECT MAX(significance) FROM memories WHERE scene_id = ?",
+        (scene_id,),
+    ).fetchone()
+    max_sig = (row[0] if row else None) or 0
+    if max_sig < 2:
+        return ""
+    cur = conn.execute(
+        "SELECT pov_summary FROM memories WHERE scene_id = ? "
+        "ORDER BY significance DESC, id ASC LIMIT 3",
+        (scene_id,),
+    )
+    quotes = [
+        (r[0] or "")[:200]
+        for r in cur.fetchall()
+    ]
+    if not quotes:
+        return ""
+    lines = "\n".join(f'- "{q}"' for q in quotes)
+    return f"\n\nKey quotes:\n{lines}"
+
+
 async def apply_scene_close_summary(
     conn: Connection,
     client: LLMClient,
@@ -296,8 +338,10 @@ async def apply_scene_close_summary(
     """
     # Local imports to keep the module-level surface tight and avoid
     # any chance of a circular dep through chat.state.*.
+    from chat.services.thread_detection import detect_threads
     from chat.state.entities import get_bot, get_you
     from chat.state.group_node import get_group_node
+    from chat.state.threads import list_open_threads
     from chat.state.world import get_chat
 
     you_entity = get_you(conn) or {"name": "you", "persona": ""}
@@ -308,6 +352,11 @@ async def apply_scene_close_summary(
 
     dialogue = _read_recent_dialogue(conn, chat_id)
 
+    # T58.1: build the "Key quotes:" suffix BEFORE the per-POV rewrites
+    # land — quote source is the raw seeded pov_summary text on each
+    # memory row, which the rewrite about to fire would clobber.
+    key_quotes_suffix = _build_key_quotes_suffix(conn, scene_id)
+
     host_pov = await _summarize_and_apply_for_witness(
         conn,
         client,
@@ -318,6 +367,7 @@ async def apply_scene_close_summary(
         you_name=you_name,
         dialogue=dialogue,
         timeout_s=timeout_s,
+        key_quotes_suffix=key_quotes_suffix,
     )
 
     guest_pov: ScenePOVSummary | None = None
@@ -332,6 +382,7 @@ async def apply_scene_close_summary(
             you_name=you_name,
             dialogue=dialogue,
             timeout_s=timeout_s,
+            key_quotes_suffix=key_quotes_suffix,
         )
 
     # Group node update: T70 runs a third classifier call to merge the
@@ -364,6 +415,56 @@ async def apply_scene_close_summary(
             },
         )
 
+    # T58.2: thread detection on close. Reuses the dialogue we already
+    # gathered for per-POV summarization — same {speaker, text} shape
+    # detect_threads expects. Failure-tolerant: classify() returns the
+    # empty default on retry-exhaustion, and the broad except below
+    # protects the close pipeline from any other classifier/mock flap.
+    try:
+        thread_result = await detect_threads(
+            client,
+            classifier_model=classifier_model,
+            scene_transcript=dialogue,
+            open_threads=list_open_threads(conn, chat_id),
+            timeout_s=timeout_s,
+        )
+    except Exception:
+        from chat.services.thread_detection import ThreadDetectionResult
+
+        thread_result = ThreadDetectionResult()
+    for cand in thread_result.candidates:
+        if cand.action == "open":
+            new_thread_id = f"thr_{uuid.uuid4().hex[:12]}"
+            append_and_apply(
+                conn,
+                kind="thread_opened",
+                payload={
+                    "thread_id": new_thread_id,
+                    "chat_id": chat_id,
+                    "title": cand.title,
+                    "summary": cand.summary,
+                },
+            )
+        elif cand.action == "update" and cand.existing_thread_id:
+            append_and_apply(
+                conn,
+                kind="thread_updated",
+                payload={
+                    "thread_id": cand.existing_thread_id,
+                    "summary": cand.summary,
+                    "last_referenced_scene_id": scene_id,
+                },
+            )
+        elif cand.action == "close" and cand.existing_thread_id:
+            append_and_apply(
+                conn,
+                kind="thread_closed",
+                payload={
+                    "thread_id": cand.existing_thread_id,
+                    "closed_at": datetime.now(timezone.utc).isoformat(),
+                },
+            )
+
     return host_pov
 
 

chat/state/memory.py

@@ -94,6 +94,14 @@ def get_pinned(conn: Connection, owner_id: str) -> list[dict]:
 _SIGNIFICANCE_WEIGHT = 0.3
 _RECENCY_WEIGHT = 0.5
 
+# T57 (Phase 3, §11.1): significance multiplier applied to the SQL ORDER BY in
+# ``search_memories`` so that the FTS over-fetch already prefers
+# higher-significance rows for tied / near-tied BM25 ranks. Module-level so it
+# can be tuned without a code change. BM25 ``rank`` is lower-is-better, so the
+# bias is *subtracted* from rank in the ASC ordering — equivalent to multiplying
+# a higher-is-better score by a positive constant per the spec wording.
+SIGNIFICANCE_RANK_BIAS = 0.5
+
 
 def search_memories(
     conn: Connection,
@@ -137,10 +145,15 @@ def search_memories(
         "JOIN memories m ON m.id = memories_fts.rowid "
         f"WHERE m.owner_id = ? AND m.{witness_col} = 1 "
         "AND memories_fts MATCH ? "
-        "ORDER BY memories_fts.rank "
+        # T57: significance multiplier biases the FTS over-fetch order. BM25
+        # ``rank`` is lower-is-better, so subtracting ``significance * BIAS``
+        # surfaces higher-significance rows above lower-significance rows with
+        # equal/near-equal match strength. Equivalent to ``score × constant``
+        # per §11.1 once the rank is inverted to a higher-is-better score.
+        "ORDER BY (memories_fts.rank - m.significance * ?) ASC "
         "LIMIT ?"
     )
-    cur = conn.execute(sql, (owner_id, query, over_fetch))
+    cur = conn.execute(sql, (owner_id, query, SIGNIFICANCE_RANK_BIAS, over_fetch))
     rows = cur.fetchall()
     if not rows:
         return []

tests/test_event_promotion.py

@@ -0,0 +1,256 @@
+"""Tests for the event-completion promotion service (T56).
+
+When an event reaches ``status='completed'``, the orchestrator promotes
+structured artifacts the event carried (``acquired_objects``,
+``knowledge_facts``, ``relationship_change``) into the appropriate
+state stores via downstream events. Cancelled / expired events do NOT
+promote — the closed event row is left in place but no follow-on
+events fire.
+"""
+
+from __future__ import annotations
+
+import json
+
+from chat.db.connection import open_db
+from chat.db.migrate import apply_migrations
+from chat.eventlog.log import append_event
+from chat.eventlog.projector import project
+from chat.services.event_promotion import promote_completed_event
+from chat.state.edges import get_edge
+import chat.state.edges  # noqa: F401  - register edge_update handler
+import chat.state.entities  # noqa: F401  - register handlers
+import chat.state.events  # noqa: F401  - register events handlers
+import chat.state.manual_edit  # noqa: F401  - register manual_edit handler
+import chat.state.world  # noqa: F401  - register handlers
+
+
+def _bot_payload(bot_id: str, name: str) -> dict:
+    return {
+        "id": bot_id,
+        "name": name,
+        "persona": "thoughtful, observant",
+        "voice_samples": [],
+        "traits": [],
+        "backstory": "",
+        "initial_relationship_to_you": "coworker",
+        "kickoff_prose": "",
+    }
+
+
+def _chat_payload(chat_id: str = "chat_bot_a") -> dict:
+    return {
+        "id": chat_id,
+        "host_bot_id": "bot_a",
+        "guest_bot_id": "bot_b",
+        "initial_time": "2026-04-26T20:00:00+00:00",
+        "narrative_anchor": "Day 1 evening",
+        "weather": "clear",
+    }
+
+
+def _seed_chat(conn) -> None:
+    append_event(conn, kind="bot_authored", payload=_bot_payload("bot_a", "BotA"))
+    append_event(conn, kind="bot_authored", payload=_bot_payload("bot_b", "BotB"))
+    append_event(conn, kind="chat_created", payload=_chat_payload())
+
+
+def _seed_event(
+    conn,
+    *,
+    event_id: str,
+    props: dict,
+    terminal_kind: str = "event_completed",
+) -> None:
+    """Append event_planned, then a terminal transition (default completed)."""
+    append_event(
+        conn,
+        kind="event_planned",
+        payload={
+            "event_id": event_id,
+            "chat_id": "chat_bot_a",
+            "kind": "story_event",
+            "props": props,
+            "planned_for": "2026-04-30T18:00:00+00:00",
+        },
+    )
+    append_event(
+        conn,
+        kind=terminal_kind,
+        payload={
+            "event_id": event_id,
+            "completed_at": "2026-04-30T20:00:00+00:00",
+        },
+    )
+    project(conn)
+
+
+def _max_event_id(conn) -> int:
+    return conn.execute("SELECT COALESCE(MAX(id), 0) FROM event_log").fetchone()[0]
+
+
+def _events_after(conn, after_id: int, kind: str) -> list[dict]:
+    rows = conn.execute(
+        "SELECT id, kind, payload_json FROM event_log "
+        "WHERE id > ? AND kind = ? ORDER BY id ASC",
+        (after_id, kind),
+    ).fetchall()
+    return [
+        {"id": r[0], "kind": r[1], "payload": json.loads(r[2])} for r in rows
+    ]
+
+
+def test_empty_props_no_op(tmp_path):
+    """Completed event with empty props produces no promotion events."""
+    db = tmp_path / "t.db"
+    apply_migrations(db)
+    with open_db(db) as conn:
+        _seed_chat(conn)
+        _seed_event(conn, event_id="evt_empty", props={})
+
+        before = _max_event_id(conn)
+        counts = promote_completed_event(
+            conn,
+            event_id="evt_empty",
+            chat_id="chat_bot_a",
+            chat_clock_at="2026-04-30T20:00:00+00:00",
+        )
+
+        assert counts == {
+            "acquired_objects": 0,
+            "knowledge_facts": 0,
+            "relationship_change": 0,
+        }
+        # No new edge_update or manual_edit rows after the promote call.
+        assert _events_after(conn, before, "edge_update") == []
+        assert _events_after(conn, before, "manual_edit") == []
+
+
+def test_knowledge_facts_emits_edge_update(tmp_path):
+    """A knowledge_facts entry promotes to an edge_update on the directed edge."""
+    db = tmp_path / "t.db"
+    apply_migrations(db)
+    with open_db(db) as conn:
+        _seed_chat(conn)
+        _seed_event(
+            conn,
+            event_id="evt_kf",
+            props={
+                "knowledge_facts": [
+                    {
+                        "owner_id": "bot_a",
+                        "target_id": "you",
+                        "fact": "Maya prefers tea over coffee",
+                    }
+                ]
+            },
+        )
+
+        before = _max_event_id(conn)
+        counts = promote_completed_event(
+            conn,
+            event_id="evt_kf",
+            chat_id="chat_bot_a",
+            chat_clock_at="2026-04-30T20:00:00+00:00",
+        )
+
+        assert counts["knowledge_facts"] == 1
+        assert counts["acquired_objects"] == 0
+        assert counts["relationship_change"] == 0
+
+        # An edge_update event landed in the event_log AFTER the promote call.
+        new_edge_updates = _events_after(conn, before, "edge_update")
+        assert len(new_edge_updates) == 1
+        payload = new_edge_updates[0]["payload"]
+        assert payload["source_id"] == "bot_a"
+        assert payload["target_id"] == "you"
+        assert payload["knowledge_facts"] == ["Maya prefers tea over coffee"]
+
+        # And the projected edge has the fact applied.
+        edge = get_edge(conn, "bot_a", "you")
+        assert edge is not None
+        assert "Maya prefers tea over coffee" in edge["knowledge"]
+
+
+def test_relationship_change_emits_manual_edit(tmp_path):
+    """A relationship_change promotes to a manual_edit edge_summary."""
+    db = tmp_path / "t.db"
+    apply_migrations(db)
+    with open_db(db) as conn:
+        _seed_chat(conn)
+        _seed_event(
+            conn,
+            event_id="evt_rc",
+            props={
+                "relationship_change": {
+                    "source_id": "bot_a",
+                    "target_id": "you",
+                    "summary": "they're now dating",
+                }
+            },
+        )
+
+        before = _max_event_id(conn)
+        counts = promote_completed_event(
+            conn,
+            event_id="evt_rc",
+            chat_id="chat_bot_a",
+            chat_clock_at="2026-04-30T20:00:00+00:00",
+        )
+
+        assert counts["relationship_change"] == 1
+        assert counts["knowledge_facts"] == 0
+        assert counts["acquired_objects"] == 0
+
+        new_manual_edits = _events_after(conn, before, "manual_edit")
+        # Filter to edge_summary only — Phase 3 stub may also emit
+        # memory_pov_summary entries for acquired_objects, but here there
+        # are none.
+        edge_summary_edits = [
+            m for m in new_manual_edits
+            if m["payload"].get("target_kind") == "edge_summary"
+        ]
+        assert len(edge_summary_edits) == 1
+        payload = edge_summary_edits[0]["payload"]
+        assert payload["target_kind"] == "edge_summary"
+        assert payload["target_id"] == {"source_id": "bot_a", "target_id": "you"}
+        assert payload["new_value"] == "they're now dating"
+
+
+def test_cancelled_event_does_not_promote(tmp_path):
+    """Cancelled events have promotable props ignored — no follow-on events."""
+    db = tmp_path / "t.db"
+    apply_migrations(db)
+    with open_db(db) as conn:
+        _seed_chat(conn)
+        _seed_event(
+            conn,
+            event_id="evt_canx",
+            props={
+                "knowledge_facts": [
+                    {"owner_id": "bot_a", "target_id": "you", "fact": "x"}
+                ],
+                "relationship_change": {
+                    "source_id": "bot_a",
+                    "target_id": "you",
+                    "summary": "ignored",
+                },
+            },
+            terminal_kind="event_cancelled",
+        )
+
+        before = _max_event_id(conn)
+        counts = promote_completed_event(
+            conn,
+            event_id="evt_canx",
+            chat_id="chat_bot_a",
+            chat_clock_at="2026-04-30T20:00:00+00:00",
+        )
+
+        assert counts == {
+            "acquired_objects": 0,
+            "knowledge_facts": 0,
+            "relationship_change": 0,
+        }
+        assert _events_after(conn, before, "edge_update") == []
+        assert _events_after(conn, before, "manual_edit") == []

tests/test_memory_search.py

@@ -125,3 +125,37 @@ def test_search_invalid_witness_role_raises(tmp_path):
     with open_db(db) as conn:
         with pytest.raises(ValueError):
             search_memories(conn, "bot_a", "invalid_role", "anything", k=4)
+
+
+def test_higher_significance_outranks_equal_rank(tmp_path):
+    """T57: significance multiplier biases the SQL ORDER BY.
+
+    Two memories with IDENTICAL FTS-matching text yield (effectively) equal
+    BM25 ranks. The significance bias applied in the SQL ORDER BY must
+    surface the higher-significance row first.
+    """
+    db = tmp_path / "t.db"
+    _seed(
+        db,
+        memory_specs=[
+            # Identical pov_summary text -> FTS BM25 rank is the same for both.
+            {"pov_summary": "she swore an oath", "significance": 0},
+            {"pov_summary": "she swore an oath", "significance": 3},
+        ],
+    )
+    with open_db(db) as conn:
+        out = search_memories(conn, "bot_a", "host", "oath", k=5)
+        assert len(out) == 2
+        # Higher significance wins despite tied FTS rank.
+        assert out[0]["significance"] == 3
+        assert out[1]["significance"] == 0
+
+
+def test_significance_bias_is_constant_module_level():
+    """T57: pin ``SIGNIFICANCE_RANK_BIAS`` as a tunable module-level numeric."""
+    from chat.state.memory import SIGNIFICANCE_RANK_BIAS
+
+    assert isinstance(SIGNIFICANCE_RANK_BIAS, (int, float))
+    # Must be non-negative -- a negative bias would invert the desired
+    # "higher significance ranks higher" semantics.
+    assert SIGNIFICANCE_RANK_BIAS >= 0

tests/test_per_pov_summary.py

@@ -504,13 +504,15 @@ async def test_close_with_no_guest_matches_phase1(tmp_path):
             "relationship_summary": "BotA leaned in supportively.",
         }
     )
+    no_threads = json.dumps({"candidates": []})
     with open_db(db) as conn:
         _seed_single_bot_scene(conn)
         project(conn)
 
-        # canned has 2 entries to detect any over-call; the assertion below
+        # 1 host-POV entry + 1 thread-detection entry (T58.2) + 1 spare
-        # confirms only one was consumed.
+        # to detect any over-call. Assertion below confirms exactly two
-        client = MockLLMClient(canned=[canned, canned])
+        # were consumed.
+        client = MockLLMClient(canned=[canned, no_threads, canned])
         await apply_scene_close_summary(
             conn,
             client,
@@ -520,8 +522,8 @@ async def test_close_with_no_guest_matches_phase1(tmp_path):
             host_bot_id="bot_a",
         )
 
-        # Exactly one classifier call -> exactly one canned entry consumed,
+        # Host POV + thread detection -> exactly two canned entries
-        # leaving the second untouched.
+        # consumed, leaving the spare untouched.
         assert len(client._canned) == 1
 
         # Host memory rewritten with the per-POV summary content.
@@ -845,3 +847,251 @@ async def test_group_summary_skipped_when_no_guest(tmp_path):
             "SELECT 1 FROM event_log WHERE kind = 'group_node_updated'"
         ).fetchall()
         assert rows == []
+
+
+# ---------------------------------------------------------------------------
+# T58: significance-driven quote retention + thread detection on close.
+# ---------------------------------------------------------------------------
+
+
+def _seed_single_bot_scene_no_memory(conn) -> None:
+    """Like ``_seed_single_bot_scene`` but skips the memory_written event so
+    callers can seed memories with custom significance / text themselves."""
+    append_event(conn, kind="bot_authored", payload=_bot_payload("bot_a", "BotA"))
+    append_event(
+        conn,
+        kind="you_authored",
+        payload={"name": "Me", "pronouns": "they/them", "persona": "engineer"},
+    )
+    append_event(
+        conn,
+        kind="chat_created",
+        payload={
+            "id": "chat_bot_a",
+            "host_bot_id": "bot_a",
+            "initial_time": "2026-04-26T20:00:00+00:00",
+            "narrative_anchor": "Day 1",
+            "weather": "",
+        },
+    )
+    append_event(
+        conn,
+        kind="container_created",
+        payload={
+            "chat_id": "chat_bot_a",
+            "name": "office",
+            "type": "workplace",
+            "properties": {},
+        },
+    )
+    append_event(
+        conn,
+        kind="scene_opened",
+        payload={
+            "chat_id": "chat_bot_a",
+            "container_id": 1,
+            "started_at": "2026-04-26T20:00:00+00:00",
+            "participants": ["you", "bot_a"],
+        },
+    )
+    append_event(
+        conn,
+        kind="edge_update",
+        payload={
+            "source_id": "bot_a",
+            "target_id": "you",
+            "chat_id": "chat_bot_a",
+        },
+    )
+    append_event(
+        conn,
+        kind="user_turn",
+        payload={
+            "chat_id": "chat_bot_a",
+            "prose": "Quick chat about the deadline",
+            "segments": [],
+        },
+    )
+    append_event(
+        conn,
+        kind="assistant_turn",
+        payload={
+            "chat_id": "chat_bot_a",
+            "speaker_id": "bot_a",
+            "text": "It's going to be okay.",
+            "truncated": False,
+            "user_turn_id": 1,
+        },
+    )
+
+
+def _seed_memory(conn, *, pov_summary: str, significance: int) -> None:
+    append_event(
+        conn,
+        kind="memory_written",
+        payload={
+            "owner_id": "bot_a",
+            "chat_id": "chat_bot_a",
+            "scene_id": 1,
+            "pov_summary": pov_summary,
+            "witness_you": 1,
+            "witness_host": 1,
+            "witness_guest": 0,
+            "significance": significance,
+        },
+    )
+
+
+@pytest.mark.asyncio
+async def test_low_significance_scene_omits_quotes(tmp_path):
+    """When the scene's max-turn-significance is < 2, the per-POV summary
+    rewrite collapses fully — no "Key quotes:" suffix is appended."""
+    db = tmp_path / "t.db"
+    apply_migrations(db)
+    canned = json.dumps(
+        {
+            "summary": "BotA had a low-key chat with you.",
+            "knowledge_facts": [],
+            "relationship_summary": "Nothing major shifted.",
+        }
+    )
+    no_threads = json.dumps({"candidates": []})
+    with open_db(db) as conn:
+        _seed_single_bot_scene_no_memory(conn)
+        _seed_memory(conn, pov_summary="Maya rambled about coffee", significance=1)
+        _seed_memory(conn, pov_summary="Maya glanced at the clock", significance=0)
+        project(conn)
+
+        client = MockLLMClient(canned=[canned, no_threads])
+        await apply_scene_close_summary(
+            conn,
+            client,
+            classifier_model="x",
+            chat_id="chat_bot_a",
+            scene_id=1,
+            host_bot_id="bot_a",
+        )
+
+        rows = conn.execute(
+            "SELECT pov_summary FROM memories WHERE scene_id = 1"
+        ).fetchall()
+        assert rows
+        for (pov,) in rows:
+            assert "Key quotes:" not in pov
+            assert "BotA had a low-key chat" in pov
+
+
+@pytest.mark.asyncio
+async def test_high_significance_scene_includes_top_3_quotes(tmp_path):
+    """When max-turn-significance is >= 2, each per-POV summary text gains
+    a "Key quotes:" suffix listing the top-3 highest-significance memory
+    rows verbatim, ordered by (significance DESC, id ASC)."""
+    db = tmp_path / "t.db"
+    apply_migrations(db)
+    canned = json.dumps(
+        {
+            "summary": "BotA had a heavy talk with you.",
+            "knowledge_facts": [],
+            "relationship_summary": "Things shifted.",
+        }
+    )
+    no_threads = json.dumps({"candidates": []})
+    with open_db(db) as conn:
+        _seed_single_bot_scene_no_memory(conn)
+        # Insertion order matches id ASC. Top-3 by (sig DESC, id ASC):
+        # quote 1 (sig 3) -> quote 2 (sig 2, lower id) -> quote 4 (sig 2,
+        # higher id). quote 3 (sig 1) is dropped.
+        _seed_memory(conn, pov_summary="Maya quote one", significance=3)
+        _seed_memory(conn, pov_summary="Maya quote two", significance=2)
+        _seed_memory(conn, pov_summary="Maya quote three", significance=1)
+        _seed_memory(conn, pov_summary="Maya quote four", significance=2)
+        project(conn)
+
+        client = MockLLMClient(canned=[canned, no_threads])
+        await apply_scene_close_summary(
+            conn,
+            client,
+            classifier_model="x",
+            chat_id="chat_bot_a",
+            scene_id=1,
+            host_bot_id="bot_a",
+        )
+
+        rows = conn.execute(
+            "SELECT pov_summary FROM memories WHERE scene_id = 1"
+        ).fetchall()
+        assert rows
+        for (pov,) in rows:
+            assert "Key quotes:" in pov
+            assert '"Maya quote one"' in pov
+            assert '"Maya quote two"' in pov
+            assert '"Maya quote four"' in pov
+            # The sig-1 quote falls outside the top-3 cap.
+            assert '"Maya quote three"' not in pov
+            # Ordering: sig 3 first, then the two sig-2s by id ASC.
+            i_one = pov.index('"Maya quote one"')
+            i_two = pov.index('"Maya quote two"')
+            i_four = pov.index('"Maya quote four"')
+            assert i_one < i_two < i_four
+
+
+@pytest.mark.asyncio
+async def test_thread_detection_emits_events(tmp_path, monkeypatch):
+    """On scene close, ``detect_threads`` is invoked and each "open"
+    candidate yields a ``thread_opened`` event with a fresh thread_id."""
+    from chat.services import thread_detection as td_mod
+
+    canned = json.dumps(
+        {
+            "summary": "BotA noticed something unresolved.",
+            "knowledge_facts": [],
+            "relationship_summary": "Tension lingered.",
+        }
+    )
+
+    async def fake_detect_threads(client, **kwargs):
+        return td_mod.ThreadDetectionResult(
+            candidates=[
+                td_mod.ThreadCandidate(
+                    action="open",
+                    title="Test thread",
+                    summary="A test",
+                    existing_thread_id=None,
+                ),
+            ]
+        )
+
+    monkeypatch.setattr(td_mod, "detect_threads", fake_detect_threads)
+
+    db = tmp_path / "t.db"
+    apply_migrations(db)
+    with open_db(db) as conn:
+        _seed_single_bot_scene(conn)
+        project(conn)
+
+        client = MockLLMClient(canned=[canned])
+        await apply_scene_close_summary(
+            conn,
+            client,
+            classifier_model="x",
+            chat_id="chat_bot_a",
+            scene_id=1,
+            host_bot_id="bot_a",
+        )
+
+        rows = conn.execute(
+            "SELECT payload_json FROM event_log WHERE kind = 'thread_opened'"
+        ).fetchall()
+        assert len(rows) == 1
+        payload = json.loads(rows[0][0])
+        assert payload["title"] == "Test thread"
+        assert payload["summary"] == "A test"
+        assert payload["chat_id"] == "chat_bot_a"
+        assert payload["thread_id"].startswith("thr_")
+
+        # The threads-table projection ran via append_and_apply.
+        from chat.state.threads import list_open_threads
+
+        open_threads = list_open_threads(conn, "chat_bot_a")
+        assert len(open_threads) == 1
+        assert open_threads[0]["title"] == "Test thread"