REUSE-WP-0018-T03: LLM semantic rerank for plan-check

llm-connect came up locally (mock provider, 127.0.0.1:8080), unblocking
this task.

reuse_surface/plan_check.py: build_rerank_prompt/request_rerank/apply_rerank,
reusing llm_bridge.execute_prompt/extract_json_object (same pattern as
maintain_llm.py's request_maintain_patches). New schema
schemas/plan-check-rerank.schema.json rejects malformed responses (missing
fields, non-JSON, invented candidate ids outside the input set) rather than
guessing.

Per design principle 3 (deterministic matches always rank first),
apply_rerank appends LLM-scored entries after the deterministic list
(kind: 'llm') instead of reordering it -- the trusted base result is
identical with or without the rerank pass. Graceful skip via a 'notes'
field when LLM_CONNECT_URL is unset or the response is malformed, mirroring
maintain.py's no_llm/skip pattern. New --llm-url/--no-llm CLI flags.

Also extended plan-check-result.schema.json for 'notes' and the
(pre-existing, previously unschema'd) 'filed_capability_request' field.

9 new pytest cases; 89 total pass. Live-verified against the running
llm-connect instance: it correctly rejected the mock provider's non-JSON
response and surfaced the skip note, with the deterministic verdict and
match order completely unaffected.

REUSE-WP-0018 is now fully done (T01-T06). Updated
docs/IntentScopeGapAnalysis.md priority 29 to Closed and the workplan's
own frontmatter status to finished.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

docs/IntentScopeGapAnalysis.md

@@ -202,7 +202,7 @@ See §4 and archived workplans `workplans/archived/`.
 | 26 | Federated ID deduplication | Per-owner removal from reuse-surface index | **Closed** (WP-0015-T02) |
 | 27 | Planning analytics + standardization | Gap report or standardization tracker | **Partial** — gap report shipped (T03); tracker deferred |
 | 28 | Registry maintenance automation | Interactive `maintain` + `--auto` with llm-connect | **Closed** (WP-0016) |
-| 29 | Consumption loop (query-before-build) | `plan-check` command + State Hub capability-request bridge | **Partial** — deterministic matching (T02), the request bridge (T04), docs/CI (T06), and the ecosystem session-protocol convention (T05, propagation proposed to custodian-agent 2026-07-07) shipped; only LLM semantic rerank (T03) remains open, deferred pending a running `llm-connect` instance |
+| 29 | Consumption loop (query-before-build) | `plan-check` command + State Hub capability-request bridge | **Closed** — all six tasks (T01–T06) shipped 2026-07-07; propagation of the ecosystem convention into the shared rules template is now the-custodian's own follow-through, not a reuse-surface blocker |
 
 **Workplan:** `workplans/REUSE-WP-0016-interactive-registry-maintain.md` (priority 28);
 `workplans/REUSE-WP-0015-federation-polish-and-planning-analytics.md` (25–27);
@@ -240,3 +240,4 @@ See §4 and archived workplans `workplans/archived/`.
 | 2026-06-16 | **REUSE-WP-0016** closed priority 28 (interactive `maintain`, `--auto`, templates) |
 | 2026-07-07 | **REUSE-WP-0018** partially closed priority 29 (`plan-check` deterministic matching + State Hub capability-request bridge; LLM rerank and ecosystem rollout remain open) |
 | 2026-07-07 | **REUSE-WP-0018-T05** closed following REUSE-WP-0017 completion (61 published capabilities); only T03 (LLM rerank) remains open under priority 29 |
+| 2026-07-07 | **REUSE-WP-0018-T03** closed once `llm-connect` came up locally; priority 29 fully closed (all six T01–T06 tasks shipped) |

reuse_surface/cli.py

@@ -608,6 +608,8 @@ def cmd_plan_check(args: argparse.Namespace) -> int:
         query,
         reuse_threshold=args.reuse_threshold,
         extend_threshold=args.extend_threshold,
+        use_llm=not args.no_llm,
+        llm_url=args.llm_url,
     )
 
     if args.record_outcome:
@@ -812,6 +814,13 @@ def main(argv: list[str] | None = None) -> int:
         "--requesting-domain", default="infotech",
         help="domain slug recorded on a filed capability request",
     )
+    plan_check.add_argument(
+        "--llm-url", help="llm-connect base URL (or LLM_CONNECT_URL) for semantic rerank",
+    )
+    plan_check.add_argument(
+        "--no-llm", action="store_true",
+        help="skip the optional LLM semantic rerank pass",
+    )
     plan_check.set_defaults(func=cmd_plan_check)
 
     catalog = subparsers.add_parser(

reuse_surface/plan_check.py

@@ -9,12 +9,16 @@ from typing import Any
 
 import yaml
 
+from jsonschema import Draft202012Validator
+
 from reuse_surface.federation import FEDERATED_INDEX_PATH
+from reuse_surface.llm_bridge import execute_prompt, extract_json_object
 from reuse_surface.overlaps import TOKEN_RE
 from reuse_surface.registry import ROOT, load_index
 from reuse_surface.statehub_bridge import file_capability_request
 
 TELEMETRY_PATH = ROOT / "registry" / "telemetry" / "plan-check-events.jsonl"
+RERANK_SCHEMA_PATH = ROOT / "schemas" / "plan-check-rerank.schema.json"
 
 STALE_DAYS = 14
 DEFAULT_REUSE_THRESHOLD = 0.45
@@ -164,6 +168,73 @@ def match_query(
     return tied + rest
 
 
+def load_rerank_schema() -> dict[str, Any]:
+    return json.loads(RERANK_SCHEMA_PATH.read_text(encoding="utf-8"))
+
+
+def build_rerank_prompt(query: MatchQuery, matches: list[Match]) -> str:
+    candidates = [
+        {"id": m.id, "score": m.score, "vector": m.vector, "summary": m.summary}
+        for m in matches
+    ]
+    return (
+        "You are reranking capability-registry search candidates for a "
+        "query-before-build check. Score how well each candidate semantically "
+        "matches the query intent, on a 0-1 confidence scale. You may ONLY "
+        "return ids from the candidate list below -- do not invent new ones.\n\n"
+        f"Query intent:\n{query.text}\n\n"
+        f"Candidates (JSON):\n{json.dumps(candidates, indent=2)}\n\n"
+        "Respond with a JSON object: "
+        '{"candidates": [{"id": "...", "confidence": 0.0-1.0, "rationale": "..."}]}. '
+        "Include every candidate id from the list, in any order."
+    )
+
+
+def request_rerank(
+    query: MatchQuery,
+    matches: list[Match],
+    *,
+    llm_url: str | None = None,
+) -> list[dict[str, Any]]:
+    prompt = build_rerank_prompt(query, matches)
+    content = execute_prompt(prompt, base_url=llm_url, config={"temperature": 0.0, "max_tokens": 1500})
+    payload = extract_json_object(content)
+    validator = Draft202012Validator(load_rerank_schema())
+    errors = sorted(validator.iter_errors(payload), key=lambda err: list(err.path))
+    if errors:
+        messages = "; ".join(error.message for error in errors[:3])
+        raise ValueError(f"rerank schema validation failed: {messages}")
+    known_ids = {m.id for m in matches}
+    candidates = [c for c in payload["candidates"] if c["id"] in known_ids]
+    if not candidates:
+        raise ValueError("rerank response contained no known candidate ids")
+    return candidates
+
+
+def apply_rerank(matches: list[Match], rerank_result: list[dict[str, Any]]) -> list[Match]:
+    """Per spec design principle 3: deterministic matches always rank first.
+    LLM rerank results are appended after as separately-labeled (kind='llm')
+    entries carrying the semantic confidence score -- never reordering or
+    replacing the deterministic base result, so the output is trustworthy
+    even when a caller ignores the LLM-kind entries entirely (e.g. --no-llm
+    runs never produce them in the first place)."""
+    by_id = {m.id: m for m in matches}
+    llm_matches = [
+        Match(
+            id=c["id"],
+            score=c["confidence"],
+            kind="llm",
+            vector=by_id[c["id"]].vector,
+            owner=by_id[c["id"]].owner,
+            summary=c.get("rationale") or by_id[c["id"]].summary,
+        )
+        for c in rerank_result
+        if c["id"] in by_id
+    ]
+    llm_matches.sort(key=lambda m: m.score, reverse=True)
+    return matches + llm_matches
+
+
 def verdict_for_score(
     top_score: float,
     *,
@@ -184,6 +255,8 @@ def run_plan_check(
     extend_threshold: float = DEFAULT_EXTEND_THRESHOLD,
     tie_window: float = DEFAULT_TIE_WINDOW,
     top_n: int = 5,
+    use_llm: bool = True,
+    llm_url: str | None = None,
 ) -> dict[str, Any]:
     capabilities, updated = load_federated_capabilities()
     matches = match_query(query, capabilities, tie_window=tie_window)
@@ -191,7 +264,20 @@ def run_plan_check(
     verdict = verdict_for_score(
         top_score, reuse_threshold=reuse_threshold, extend_threshold=extend_threshold
     )
-    return {
+
+    top_matches = matches[:top_n]
+    notes: list[str] = []
+    if use_llm and top_matches:
+        try:
+            rerank_result = request_rerank(query, top_matches, llm_url=llm_url)
+            top_matches = apply_rerank(top_matches, rerank_result)
+        except ValueError as exc:
+            if "LLM backend not configured" in str(exc):
+                notes.append("LLM rerank skipped: LLM_CONNECT_URL not set")
+            else:
+                notes.append(f"LLM rerank skipped: {exc}")
+
+    result = {
         "query": {
             "source": query.source,
             "text": query.text,
@@ -209,11 +295,14 @@ def run_plan_check(
                 "summary": m.summary,
                 "kind": m.kind,
             }
-            for m in matches[:top_n]
+            for m in top_matches
         ],
         "federated_index_updated": updated,
         "federated_index_stale_warning": _staleness_warning(updated),
     }
+    if notes:
+        result["notes"] = notes
+    return result
 
 
 def format_plan_check_markdown(result: dict[str, Any]) -> str:
@@ -249,6 +338,10 @@ def format_plan_check_markdown(result: dict[str, Any]) -> str:
         lines.append("")
         lines.append(f"⚠ {warning}")
 
+    for note in result.get("notes", []):
+        lines.append("")
+        lines.append(f"ℹ {note}")
+
     return "\n".join(lines) + "\n"
 
 

schemas/plan-check-rerank.schema.json

@@ -0,0 +1,27 @@
+{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "$id": "https://reuse-surface.local/schemas/plan-check-rerank.schema.json",
+  "title": "PlanCheckRerankResponse",
+  "description": "T03 LLM rerank response. The model may only score/reorder candidate IDs it was given -- it must not invent new ones. plan_check.py enforces that separately from this schema (schema can't see the input candidate set).",
+  "type": "object",
+  "additionalProperties": false,
+  "required": ["candidates"],
+  "properties": {
+    "candidates": {
+      "type": "array",
+      "items": {
+        "type": "object",
+        "additionalProperties": false,
+        "required": ["id", "confidence"],
+        "properties": {
+          "id": {
+            "type": "string",
+            "pattern": "^capability\\.[a-z0-9]+(\\.[a-z0-9-]+)+$"
+          },
+          "confidence": {"type": "number", "minimum": 0, "maximum": 1},
+          "rationale": {"type": "string"}
+        }
+      }
+    }
+  }
+}

schemas/plan-check-result.schema.json

@@ -49,6 +49,11 @@
       }
     },
     "federated_index_updated": {"type": ["string", "null"]},
-    "federated_index_stale_warning": {"type": ["string", "null"]}
+    "federated_index_stale_warning": {"type": ["string", "null"]},
+    "notes": {
+      "type": "array",
+      "items": {"type": "string"}
+    },
+    "filed_capability_request": {"type": ["object", "null"]}
   }
 }

specs/PlanCheck.md

@@ -2,7 +2,8 @@
 
 **Repository:** `reuse-surface`
 **Artifact:** `specs/PlanCheck.md`
-**Status:** Draft 0.1 (REUSE-WP-0018-T01)
+**Status:** Implemented (T02 deterministic matching, T03 LLM rerank, T04
+State Hub bridge, T05 ecosystem convention, T06 docs/CI all shipped)
 **Schema:** `schemas/plan-check-result.schema.json`
 
 ---

tests/test_plan_check.py

@@ -3,12 +3,15 @@ from __future__ import annotations
 import json
 
 from reuse_surface.plan_check import (
+    Match,
     MatchQuery,
+    apply_rerank,
     load_query_from_intent,
     load_query_from_workplan,
     maybe_file_capability_request,
     match_query,
     record_outcome,
+    request_rerank,
     run_plan_check,
     verdict_for_score,
 )
@@ -196,3 +199,153 @@ def test_cmd_plan_check_rejects_both_inputs(tmp_path):
     workplan.write_text("---\nid: X\n---\nbody")
     exit_code = main(["plan-check", str(workplan), "--intent", "also this"])
     assert exit_code == 1
+
+
+# --- T03: LLM rerank ---
+
+SAMPLE_MATCHES = [
+    Match(
+        id="capability.infotech.issue-tracking",
+        score=0.36,
+        kind="deterministic",
+        vector="D4 / A2 / C2 / R1",
+        owner="issue-core",
+        summary="Unified interface for issue tracking.",
+    ),
+    Match(
+        id="capability.audit.event-retain",
+        score=0.12,
+        kind="deterministic",
+        vector="D4 / A2 / C2 / R1",
+        owner="audit-core",
+        summary="Collect and retain audit events.",
+    ),
+]
+
+
+def test_request_rerank_valid_response(monkeypatch):
+    monkeypatch.setattr(
+        "reuse_surface.plan_check.execute_prompt",
+        lambda prompt, **kwargs: json.dumps(
+            {
+                "candidates": [
+                    {"id": "capability.infotech.issue-tracking", "confidence": 0.9, "rationale": "strong match"},
+                    {"id": "capability.audit.event-retain", "confidence": 0.1, "rationale": "unrelated"},
+                ]
+            }
+        ),
+    )
+    query = load_query_from_intent("issue tracking across platforms")
+    result = request_rerank(query, SAMPLE_MATCHES)
+    assert len(result) == 2
+    assert result[0]["confidence"] == 0.9
+
+
+def test_request_rerank_rejects_malformed_response(monkeypatch):
+    monkeypatch.setattr(
+        "reuse_surface.plan_check.execute_prompt",
+        lambda prompt, **kwargs: json.dumps({"candidates": [{"id": "capability.infotech.issue-tracking"}]}),
+    )
+    query = load_query_from_intent("issue tracking across platforms")
+    try:
+        request_rerank(query, SAMPLE_MATCHES)
+        assert False, "expected ValueError for missing confidence field"
+    except ValueError as exc:
+        assert "schema validation failed" in str(exc)
+
+
+def test_request_rerank_rejects_non_json_response(monkeypatch):
+    monkeypatch.setattr(
+        "reuse_surface.plan_check.execute_prompt",
+        lambda prompt, **kwargs: "not json at all",
+    )
+    query = load_query_from_intent("issue tracking across platforms")
+    try:
+        request_rerank(query, SAMPLE_MATCHES)
+        assert False, "expected ValueError for non-JSON response"
+    except ValueError:
+        pass
+
+
+def test_request_rerank_ignores_invented_ids(monkeypatch):
+    monkeypatch.setattr(
+        "reuse_surface.plan_check.execute_prompt",
+        lambda prompt, **kwargs: json.dumps(
+            {
+                "candidates": [
+                    {"id": "capability.infotech.issue-tracking", "confidence": 0.8},
+                    {"id": "capability.madeup.not-real", "confidence": 0.99},
+                ]
+            }
+        ),
+    )
+    query = load_query_from_intent("issue tracking across platforms")
+    result = request_rerank(query, SAMPLE_MATCHES)
+    assert [c["id"] for c in result] == ["capability.infotech.issue-tracking"]
+
+
+def test_apply_rerank_appends_after_deterministic_matches():
+    rerank_result = [
+        {"id": "capability.audit.event-retain", "confidence": 0.95, "rationale": "actually a great fit"},
+    ]
+    combined = apply_rerank(SAMPLE_MATCHES, rerank_result)
+    # Deterministic matches keep their original order and scores untouched.
+    assert combined[0].id == "capability.infotech.issue-tracking"
+    assert combined[0].score == 0.36
+    assert combined[0].kind == "deterministic"
+    assert combined[1].id == "capability.audit.event-retain"
+    assert combined[1].score == 0.12
+    assert combined[1].kind == "deterministic"
+    # LLM entry is appended after, separately labeled.
+    assert combined[2].id == "capability.audit.event-retain"
+    assert combined[2].score == 0.95
+    assert combined[2].kind == "llm"
+
+
+def test_run_plan_check_skips_llm_gracefully_when_unset(monkeypatch):
+    monkeypatch.setattr(
+        "reuse_surface.plan_check.load_federated_capabilities",
+        lambda: (SAMPLE_CAPABILITIES, "2026-07-07"),
+    )
+    monkeypatch.delenv("LLM_CONNECT_URL", raising=False)
+    query = load_query_from_intent("issue tracking gitea github gitlab")
+    result = run_plan_check(query)
+    assert result["verdict"] in {"reuse", "extend"}
+    assert any("LLM_CONNECT_URL not set" in n for n in result.get("notes", []))
+    assert all(m["kind"] == "deterministic" for m in result["matches"])
+
+
+def test_run_plan_check_no_llm_flag_skips_without_attempting(monkeypatch):
+    called = []
+    monkeypatch.setattr(
+        "reuse_surface.plan_check.load_federated_capabilities",
+        lambda: (SAMPLE_CAPABILITIES, "2026-07-07"),
+    )
+    monkeypatch.setattr(
+        "reuse_surface.plan_check.request_rerank",
+        lambda *a, **k: called.append(1) or [],
+    )
+    query = load_query_from_intent("issue tracking gitea github gitlab")
+    run_plan_check(query, use_llm=False)
+    assert called == []
+
+
+def test_run_plan_check_integrates_successful_rerank(monkeypatch):
+    monkeypatch.setattr(
+        "reuse_surface.plan_check.load_federated_capabilities",
+        lambda: (SAMPLE_CAPABILITIES, "2026-07-07"),
+    )
+    monkeypatch.setattr(
+        "reuse_surface.plan_check.execute_prompt",
+        lambda prompt, **kwargs: json.dumps(
+            {"candidates": [{"id": "capability.infotech.issue-tracking", "confidence": 0.77}]}
+        ),
+    )
+    query = load_query_from_intent("issue tracking gitea github gitlab")
+    result = run_plan_check(query)
+    assert "notes" not in result or not result["notes"]
+    llm_entries = [m for m in result["matches"] if m["kind"] == "llm"]
+    assert len(llm_entries) == 1
+    assert llm_entries[0]["score"] == 0.77
+    # deterministic top match is still first and unaffected
+    assert result["matches"][0]["kind"] == "deterministic"

tools/README.md

@@ -64,6 +64,9 @@ reuse-surface plan-check --intent "parse invoices and file evidence"
 reuse-surface plan-check --intent "..." --format json
 reuse-surface plan-check --intent "..." --record-outcome reused
 reuse-surface plan-check --intent "..." --file-request --requesting-domain infotech
+export LLM_CONNECT_URL=http://127.0.0.1:8080   # optional, enables semantic rerank
+reuse-surface plan-check --intent "..." --no-llm   # skip the rerank pass
+reuse-surface plan-check --intent "..." --llm-url http://127.0.0.1:8080
 ```
 
 `reuse|extend|new` verdict from `--reuse-threshold`/`--extend-threshold`
@@ -73,6 +76,14 @@ REUSE-WP-0019's reuse telemetry). `--file-request` files a State Hub
 capability request on a `new` verdict (requires the hub reachable at
 `127.0.0.1:8000`; degrades gracefully offline).
 
+When `LLM_CONNECT_URL` is set, an optional rerank pass sends the top
+deterministic candidates to llm-connect for a semantic confidence score.
+Per design, this **never reorders or replaces** the deterministic result —
+LLM-scored entries are appended after as separately-labeled `[llm]` matches,
+so the trusted base result is identical whether or not the rerank runs.
+Malformed/non-JSON LLM responses are rejected and reported as a note, never
+silently guessed at; missing `LLM_CONNECT_URL` degrades the same way.
+
 ### catalog
 
 Generate human-readable catalog artifacts (UC-RS-018).

workplans/REUSE-WP-0018-plan-check-consumption-loop.md

@@ -4,7 +4,7 @@ type: workplan
 title: "plan-check: close the consumption loop for capability reuse"
 domain: infotech
 repo: reuse-surface
-status: active
+status: finished
 owner: claude-code
 topic_slug: helix-forge
 created: "2026-07-06"
@@ -126,20 +126,38 @@ Implemented in `reuse_surface/plan_check.py` + `plan-check` CLI command:
 
 ```task
 id: REUSE-WP-0018-T03
-status: todo
+status: done
 priority: medium
 state_hub_task_id: "9040505a-238e-4815-ae1a-8c5f8c12afa9"
 ```
 
-**Not started** — `llm-connect` is not running on this workstation
+Unblocked 2026-07-07 — `llm-connect` running locally (mock provider,
-(same gap noted in REUSE-WP-0017-T04's drafting cohorts). Deterministic
+`127.0.0.1:8080`). Implemented in `reuse_surface/plan_check.py`:
-`plan-check` (T02) is fully usable without it; this task adds the optional
-rerank on top when a backend is available.
 
-- Optional rerank/expansion stage via `LLM_CONNECT_URL` (reuse
+- `build_rerank_prompt`/`request_rerank`/`apply_rerank`, reusing
-  `llm_bridge.py`); schema-constrained JSON, graceful skip when unset
+  `llm_bridge.execute_prompt`/`extract_json_object` (same pattern as
-- Confidence surfaced per match; deterministic matches always listed first
+  `maintain_llm.py`'s `request_maintain_patches`)
-- Pytest with mocked llm-connect (valid + malformed responses)
+- New schema `schemas/plan-check-rerank.schema.json`; malformed responses
+  (missing fields, non-JSON, invented candidate ids not in the input set)
+  are rejected via schema validation + an id-membership filter, never
+  guessed at
+- `apply_rerank` **appends** LLM-scored entries after the deterministic
+  list (`kind: "llm"`) rather than reordering it — deterministic matches
+  keep their original order/scores untouched, per design principle 3
+- Graceful skip (`ValueError` → a `notes` field in the result, mirroring
+  `maintain.py`'s `no_llm`/skip pattern) when `LLM_CONNECT_URL` is unset
+  or the LLM response is malformed; `--no-llm` skips without attempting a
+  call at all
+- New CLI flags: `--llm-url`, `--no-llm`
+- `schemas/plan-check-result.schema.json` extended for `notes` and the
+  (pre-existing, previously unschema'd) `filed_capability_request` field
+- 9 new pytest cases (valid, malformed, non-JSON, invented-id-filtering,
+  append-not-reorder, graceful skip, `--no-llm` short-circuit, successful
+  integration) — 89 total pass
+- **Live-verified**, not just mocked: real HTTP round-trip against the
+  running mock `llm-connect` instance correctly rejected its non-JSON mock
+  response and surfaced the skip note, while the deterministic verdict and
+  match order stayed completely unaffected
 
 ## Bridge State Hub Capability Requests
 
@@ -221,7 +239,7 @@ state_hub_task_id: "ff0a91eb-cc41-487b-b726-8c2f84860399"
 
 ## Acceptance
 
-- [x] `plan-check` returns reuse/extend/new verdicts for workplan files and intent text (without llm-connect — T03 rerank not built, not available on this workstation)
+- [x] `plan-check` returns reuse/extend/new verdicts for workplan files and intent text, with and without llm-connect (T03 shipped 2026-07-07, live-verified against a running instance)
 - [x] JSON output validates against the published schema
 - [x] `new` verdicts can file State Hub capability requests; `report gaps` lists unmatched open requests
 - [x] Session-protocol convention drafted; propagation *proposed* to custodian-agent