docs: record authorized runner root filesystem expansion

Reviewed-on: #7

.gitea/workflows/env-probe.yml

@@ -29,3 +29,20 @@ jobs:
           (find / -maxdepth 4 \( -name 'lake-manifest.json' -o -name '.lake' \) -not -path '/proc/*' 2>/dev/null | head -20) || true
           (docker images 2>&1 | head -20) || true
           (docker ps -a 2>&1 | head -10) || true
+      - name: Read-only storage diagnosis
+        run: |
+          set -eu
+          hostname
+          lsblk -e 7 -o NAME,PATH,SIZE,FSTYPE,MOUNTPOINTS
+          findmnt -T /var/lib/docker
+          df -hT / /var/lib/docker
+          docker info --format 'storage={{.Driver}} root={{.DockerRootDir}}'
+          docker system df
+          docker builder du 2>/dev/null || true
+          for dir in /var/lib/docker /var/lib/containerd /opt/lean-cache /var/cache /tmp /var/log; do
+            if [ -d "$dir" ]; then du -xhd1 "$dir" 2>/dev/null || true; fi
+          done
+          for tool in sfdisk growpart resize2fs xfs_growfs; do command -v "$tool" || true; done
+          if [ "$(hostname)" = "iZ6we8b3jgd6nc2qehu06lZ" ] && command -v growpart >/dev/null; then
+            growpart -N /dev/nvme0n1 3 || true
+          fi

.gitea/workflows/runner-storage-maintenance.yml

@@ -0,0 +1,49 @@
+name: runner-storage-maintenance
+
+# Manual-only. Never runs on push or pull_request.
+on:
+  workflow_dispatch:
+    inputs:
+      confirm:
+        description: Enter EXPAND_RUNNER_ROOT after owner approval
+        required: true
+        type: string
+
+jobs:
+  expand-root:
+    if: ${{ github.event_name == 'workflow_dispatch' && inputs.confirm == 'EXPAND_RUNNER_ROOT' }}
+    runs-on: ubuntu24.04-x64-lean4.35
+    timeout-minutes: 20
+    steps:
+      - name: Back up partition table and expand the authorized ext4 root
+        run: |
+          # Owner-authorized manual-only root partition/filesystem expansion.
+          set -euo pipefail
+          exec 9>/var/lock/lean-bench-root-maintenance.lock
+          flock -n 9
+          [ "$(hostname)" = "iZ6we8b3jgd6nc2qehu06lZ" ]
+          [ "$(id -u)" = 0 ]
+          [ "$(blkid -s PARTUUID -o value /dev/nvme0n1p3 | tr A-Z a-z)" = 9b694bad-5bbb-4485-860f-e5544ae47410 ]
+          [ "$(findmnt -n -o SOURCE /)" = /dev/nvme0n1p3 ]
+          [ "$(findmnt -n -o FSTYPE /)" = ext4 ]
+          [ "$(lsblk -n -o START /dev/nvme0n1p3 | tr -d ' ')" = 413696 ]
+          [ "$(blockdev --getsize64 /dev/nvme0n1)" -ge 161061273600 ]
+          backup_dir="/root/lean-bench-maintenance/$(date -u +%Y%m%dT%H%M%SZ)"
+          install -d -m 700 "$backup_dir"
+          sfdisk --dump /dev/nvme0n1 > "$backup_dir/nvme0n1.sfdisk"
+          sync
+          printf 'Partition-table backup: %s\n' "$backup_dir/nvme0n1.sfdisk"
+          set +e
+          growpart -N /dev/nvme0n1 3 > "$backup_dir/growpart-dry-run.log" 2>&1
+          probe_status=$?
+          set -e
+          if [ "$probe_status" = 0 ]; then
+            growpart /dev/nvme0n1 3
+          elif ! grep -q '^NOCHANGE:' "$backup_dir/growpart-dry-run.log"; then
+            cat "$backup_dir/growpart-dry-run.log"
+            exit "$probe_status"
+          fi
+          resize2fs /dev/nvme0n1p3
+          [ "$(lsblk -n -o START /dev/nvme0n1p3 | tr -d ' ')" = 413696 ]
+          lsblk -e 7 -o NAME,PATH,SIZE,FSTYPE,MOUNTPOINTS
+          df -hT / /var/lib/docker

docs/experiments/P0-gpt-diagnostic.md

@@ -0,0 +1,127 @@
+# P0: full-cohort GPT-assisted diagnostic (2026-10-28)
+
+**All 65 items have a fresh source-role description, a fresh semantic judgment and a
+completed deterministic alignment. This is a same-assistant diagnostic, not an independent
+benchmark or a completion of the preregistered Qwen gate. No gate decision is issued.**
+
+## Scope and provenance
+
+The owner requested that the current GPT assistant reassess the entire cohort after the
+Qwen run was interrupted by provider billing failures. Every item was reviewed again;
+no Qwen detector output was reused, and the incomplete Qwen run was not patched with GPT
+outputs. The earlier labels and Qwen files remain unchanged in the original worktree.
+This branch starts at main `5d531c9` and does not depend on the separate billing-recovery PR.
+
+The source-role structures and four-way judgments were authored directly by the assistant
+in this chat, frozen before computing the new alignment statistics, and replayed by an
+offline script. They were not responses obtained through a GPT API endpoint. The exact
+deployed model identifier, temperature and chat token usage are unavailable; they are not
+invented. There were **zero new external model API calls** for this diagnostic, and no
+DashScope credential was loaded.
+
+The assistant had already seen the earlier labels, Lean code, detector implementation and
+aggregate compilation statistics. It also viewed passages and Lean together during this
+review. Thus the source descriptions are **not a blinded source-only extraction** and the
+new judgments are **not independent of the reference labels**. Reading only a passage when
+writing a role does not remove prior context exposure. Syntax and proof defects are
+separated from recoverable semantic meaning; no new Lean compilation or library API audit
+was performed. An independent human review remains necessary for research claims.
+
+## Results for all 65 items
+
+| Fresh semantic judgment | Items |
+|---|---:|
+| Faithful | 25 |
+| Minor drift | 13 |
+| Wrong | 24 |
+| Not formalizable from the extracted specification | 3 |
+| Total | 65 |
+
+The strict binary assistant judge flags every verdict except faithful. The full four-way
+judgment, error categories and an individual explanation are retained for every item.
+Explanations and role descriptions are private because they paraphrase the source passages.
+
+The unchanged deterministic role matcher flagged **55/65** items. It flagged all **24**
+items newly judged wrong, but also **16/25** newly judged faithful. These are comparisons
+between dependent components of the same diagnostic, not an independently measured recall
+or false-positive rate. They identify an over-sensitive diagnostic behavior worth auditing.
+
+Common conflict categories across all items include missing objects (41 items), degenerate
+projections (15), goal mismatch (15), missing hypotheses (14), extra hypotheses (13),
+quantifier conflicts (7) and type conflicts (5). Categories overlap. In particular, a named
+source quantity can be computed inline in Lean, a product representation can replace an
+abstract isomorphic group, and a bundled type can encode conditions without separate
+binders. The current lexical matcher does not establish equivalence of those representations.
+These are hypotheses for a later matcher audit, not measured causal explanations for every flag.
+No matching threshold, concept table or authored assessment was changed after the scores
+were inspected.
+
+## Relation to the frozen earlier AI labels
+
+The fresh four-way judgments agree with **59/65** earlier labels. Six changed:
+
+| Blind ID | Earlier AI label | Fresh judgment |
+|---|---|---|
+| P02 | Faithful | Minor drift |
+| P18 | Faithful | Minor drift |
+| P23 | Faithful | Minor drift |
+| P34 | Faithful | Minor drift |
+| P51 | Faithful | Minor drift |
+| P57 | Wrong | Minor drift |
+
+The six changes concern representation, type/scope and coverage judgments. They demonstrate
+annotation instability and should be independently adjudicated, not silently overwritten.
+The 59/65 agreement is **not an accuracy estimate**.
+
+For debugging continuity, the summary contains confusion counts and Wilson intervals against
+the frozen earlier AI labels. The primary comparison excludes earlier minor-drift and
+not-formalizable labels (55 items); the secondary comparison includes minor drift as positive
+(62 items). These tables are explicitly named `reference_agreement`. They cannot establish
+that GPT or role alignment outperforms Qwen. The Qwen coverage is incomplete and this pass
+has different provenance and no independent ground truth. `decision` is null; no GO,
+PARTIAL or NO-GO is computed.
+
+## Artifacts and replay
+
+Tracked, text-free artifacts:
+
+- `experiments/P0-pilot/results/gpt-diagnostic-summary.json`: provenance, input/assessment/code
+  hashes, distributions, fixed matching thresholds and non-independent agreement statistics.
+- `experiments/P0-pilot/results/gpt-diagnostic-items.json`: all 65 blind IDs, verdicts, error
+  categories, compile flags, role scores and conflict categories; no passages or explanations.
+- `experiments/P0-pilot/assistant_diagnostic.py`: validates authored inputs and replays the
+  existing projection, lint, alignment and statistics code offline.
+- `tests/test_assistant_diagnostic.py`: completeness, identity, schema, offline replay and
+  public-output privacy regressions using synthetic text.
+
+Private artifacts under the gitignored `experiments/P0-pilot/data/gpt-diagnostic/`:
+
+- `items.jsonl`: source-inclusive copy of the unchanged cohort.
+- `assistant-assessments.json`: all newly authored source structures and judgments, frozen
+  before alignment statistics were inspected.
+- `results.jsonl`: complete replay outputs for the 65 items.
+- `review.html`: local, self-contained per-item source/Lean/reason/role/alignment review.
+- `original-hashes.json`: snapshot of the earlier Qwen files and reference labels for
+  verifying that this work did not change them.
+
+Run from the repository root with the private files present:
+
+```sh
+PYTHONPATH=. python3 experiments/P0-pilot/assistant_diagnostic.py \
+  --items experiments/P0-pilot/data/gpt-diagnostic/items.jsonl \
+  --key experiments/P0-pilot/labels/key.json \
+  --assessments experiments/P0-pilot/data/gpt-diagnostic/assistant-assessments.json \
+  --labels experiments/P0-pilot/labels/labels.json \
+  --private-out experiments/P0-pilot/data/gpt-diagnostic \
+  --summary experiments/P0-pilot/results/gpt-diagnostic-summary.json \
+  --public-items experiments/P0-pilot/results/gpt-diagnostic-items.json
+```
+
+The replay is deterministic; it does not regenerate GPT judgments, call a model, or compile
+Lean. Without the private assessment file, public readers can inspect the categorical
+results but cannot reconstruct the authored descriptions and explanations from hashes.
+
+152 offline unit tests, repository-wide Ruff and diff checks passed locally without a Lean
+or Docker build. Remote Python and real Lean verification use the owner-confirmed
+`ubuntu24.04-x64-lean4.35` tag; the delivered PR records their current status. The existing
+PR workflow skips the Docker image job. No Phase 1 work has started.

docs/experiments/P0-pilot.md

@@ -2,7 +2,18 @@
 
 Experiment ID **P0**, Phase 0. Registry and conventions: [README.md](README.md).
 
-Status: **approved 2026-10-22; labels pending. No detector has been run and no API spend has occurred.**
+Status: **approved 2026-10-22; 65 AI labels frozen 2026-10-28; detector execution pending explicit data-transfer approval. No pilot API request has been sent.**
+
+Owner amendment (2026-10-28, in the execution chat): Codex now handles preparation,
+annotation, detector execution and reporting; Kimi's participation is no longer required.
+The frozen labels are from one AI annotator, **not human ground truth**. The annotator saw
+the detector implementation and aggregate compile counts before labeling, but did not see
+per-item compiler outcomes or detector outputs. This departs from the original labeling plan;
+any resulting decision is provisional and cannot substitute for an independent human audit.
+Decision thresholds, detector prompts and the concept table remain fixed. Implementation
+repairs before the first paid call restore the complementary-signal PARTIAL rule, exclude
+minor drift from the primary wrong-versus-faithful comparison, enforce the cumulative HTTP
+request budget, and persist run identity and usage. See `experiments/P0-pilot/README.md`.
 Written 2026-10-22. Companion to `docs/research-plan.md` (what and why), `docs/TODO.md` (task list), `docs/acl-2027-bar.md` (bar). Target: ACL 2027 via ARR, deadline 4 Jan 2027 AoE.
 
 ## 1. Decision (approved by the owner on 2026-10-22)

docs/infrastructure/runner-lean435.md

@@ -3,7 +3,7 @@
 Gitea runner `iZ6we8b3jgd6nc2qehu06lZ` (act_runner v5.2.0, runner id 7), label `ubuntu24.04-x64-lean4.35`. Both `lean-bench` and `lean-agent` CI run here; the old `gitea-cicd-server-for-CODEX` label is no longer used.
 
 ## The host
-- Jobs run **on the host, not in a container**, as root. Ubuntu 24.04.5, kernel 6.8, 4 CPU, 15 GiB RAM, no swap, 99 GB disk (88 GB free at setup).
+- Jobs run **on the host, not in a container**, as root. Ubuntu 24.04.5, kernel 6.8, 4 CPU, 15 GiB RAM, no swap, 150 GiB system disk (expanded from 100 GiB on 2026-10-28); the ext4 root filesystem reports about 148 GiB, with 75 GiB available immediately after expansion.
 - Lean 4.35.0 via elan 4.2.4 in `/root/.elan`. Python 3.12.3, git 2.43, gcc 13.3, curl, jq.
 - **No Node**, so `actions/checkout` and other JavaScript actions cannot run. Workflows clone with `git fetch --depth 1 origin $SHA` using `${{ github.token }}`.
 - Docker was not installed; the lean-bench `image` job installs `docker.io` + `docker-buildx` (Docker 29.1.3) if missing.
@@ -20,3 +20,30 @@ Gitea runner `iZ6we8b3jgd6nc2qehu06lZ` (act_runner v5.2.0, runner id 7), label `
 - Mathlib's post-update hook runs the cache fetch **inside `lake update`**, so retries placed after it never run. Set `MATHLIB_NO_CACHE_ON_UPDATE=1` for `lake update` and fetch in a retry loop. In the image the archives live in a BuildKit cache mount (`/root/.cache/mathlib`), so a retried build resumes.
 - Cold image build about 19 min; with layers cached about 2 min.
 - Gitea 1.26.1 has no cancel-run API; a person cancels in the web UI, then the API can `DELETE` the finished run. The Actions logs endpoint needs a token; the runs/jobs status endpoints work anonymously on this public repo.
+
+## Root capacity expansion (2026-10-28)
+
+The owner expanded the cloud disk to 150 GiB, but root partition `/dev/nvme0n1p3`
+and its ext4 filesystem still occupied about 100 GiB. CI run number 43 (API run ID 438)
+therefore continued to report 28 GiB available and failed its unchanged 30 GiB preflight.
+Rerunning a failed job retains the same UI run number; its job attempt number increments.
+
+Read-only probe run number 45 (API run ID 442) confirmed the raw-disk/partition mismatch.
+Its `growpart -N` output showed that partition 3 could extend from 209301471 to
+314159071 sectors while keeping start sector 413696 and its partition UUID unchanged.
+Temporary files and logs were small; Docker/containerd storage and Mathlib were the main
+consumers. No tagged image, build cache or Mathlib cache was deleted for this repair.
+
+The owner explicitly authorized partition and filesystem expansion in the execution chat.
+Manual maintenance run number 46 (API run ID 443) then backed up the partition table to
+`/root/lean-bench-maintenance/20261028T121919Z/nvme0n1.sfdisk`, expanded partition 3,
+and grew the mounted ext4 filesystem online. The resulting partition is 149.8 GiB;
+`df` reported a 148 GiB filesystem with 75 GiB available. No reboot was required.
+
+`.gitea/workflows/env-probe.yml` now includes read-only storage and cache diagnostics.
+`.gitea/workflows/runner-storage-maintenance.yml` is manual-only and requires the literal
+confirmation `EXPAND_RUNNER_ROOT`. It validates hostname, root device, ext4 type, partition
+UUID, start sector and disk size, takes a lock, and backs up the partition table before any
+change. Future execution still requires explicit owner authorization for that maintenance.
+It never formats a device or prunes images. The failed image job was retried after expansion;
+its actual build, smoke-test and image-retention outcome is recorded in CI run number 43.

experiments/P0-pilot/README.md

@@ -16,16 +16,52 @@ unfaithful formalizations better than a single LLM judge, compile-only, or stati
 
 ## Steps
 
-    cp runs/p85-110/items.jsonl experiments/P0-pilot/data/items.jsonl
+    # Default exports omit source_text. Restore it from the matching private review.
+    python experiments/P0-pilot/prepare_items.py --items runs/p85-110/items.jsonl \
+        --review runs/p85-110/review.json --out experiments/P0-pilot/data/items.jsonl
     python experiments/P0-pilot/make_sheet.py --items experiments/P0-pilot/data/items.jsonl \
         --out experiments/P0-pilot/data --key-dir experiments/P0-pilot/labels --seed 7
     # a person opens data/labelsheet.html, labels all 65 items, downloads labels.json into labels/
     python experiments/P0-pilot/run_pilot.py --items experiments/P0-pilot/data/items.jsonl \
         --out experiments/P0-pilot/data/results.jsonl --dry-run
     python experiments/P0-pilot/run_pilot.py --items experiments/P0-pilot/data/items.jsonl \
-        --out experiments/P0-pilot/data/results.jsonl
+        --out experiments/P0-pilot/data/results.jsonl --labels experiments/P0-pilot/labels/labels.json
     python experiments/P0-pilot/score.py --results experiments/P0-pilot/data/results.jsonl \
         --labels experiments/P0-pilot/labels/labels.json --key experiments/P0-pilot/labels/key.json \
         --summary experiments/P0-pilot/results/summary.json
 
 Labeling must be finished before anyone opens `results.jsonl`.
+
+## Execution safeguards
+
+- Every item must have a nonempty source passage. `prepare_items.py` restores passages only
+  when all exported fields match the archived review; the exported cohort and Lean code stay intact.
+- Freeze all labels before the paid run. The owner changed the labeler to the Codex assistant
+  on 2026-10-28. These are **AI labels, not human gold**; see the metadata in `labels/labels.json`.
+- `--max-calls` counts actual HTTP attempts, including transport and JSON retries, cumulatively
+  across resumes. The hard ceiling is 400. A reservation is saved before each request; an interrupted
+  request may consume a reservation without a known response or token count.
+- Metadata is stored beside the output as `results.meta.json`. Model, endpoint, temperature,
+  input hash, frozen-label hash and prompt hashes must match on resume. Usage is cumulative.
+  A file lock prevents concurrent writers. A budget stop returns exit status 2.
+- The nominal successful path uses 130 calls (one source extraction and one judge per item);
+  malformed replies and network retries may increase the actual count.
+- Scoring requires complete labels and results and no unresolved detector errors. The primary
+  comparison is wrong versus faithful; minor drift is included as positive in the secondary analysis.
+  The complementary-signal PARTIAL rule counts wrong items flagged by role alignment but missed
+  by the judge. No threshold, concept table or detector prompt was tuned for these labels.
+- Raw passages, labeling HTML and model responses remain in the ignored `data/` directory.
+  Only verdicts, abstract annotation notes, hashes and text-free summaries belong in Git.
+
+## Separate GPT-assisted diagnostic
+
+The owner requested a complete 65-item reassessment by the current GPT assistant on
+2026-10-28. This is separate from the incomplete Qwen run: no outputs are mixed and
+neither the earlier labels nor Qwen files are overwritten. The assistant had prior
+exposure to the reference labels and Lean; this is not blind or independent validation.
+No GO/PARTIAL/NO-GO decision is issued.
+
+See `docs/experiments/P0-gpt-diagnostic.md` for all counts, limitations, artifact locations
+and the offline replay command. The tracked `results/gpt-diagnostic-*.json` files contain
+only categorical/numeric outputs and audit metadata. The authored source structures,
+reasons and full review page stay in the ignored `data/gpt-diagnostic/` directory.

experiments/P0-pilot/assistant_diagnostic.py

@@ -0,0 +1,200 @@
+"""Validate and replay a current-chat assistant review without calling any model.
+
+Private source schemas and reasons stay in data/. Public summaries contain only
+categories, counts, numeric scores, hashes and an explicit non-independent provenance.
+"""
+from __future__ import annotations
+
+import argparse
+import hashlib
+import html
+import json
+import math
+from collections import Counter
+from pathlib import Path
+
+from leanbench.align import DEFAULT_THRESHOLD, GOAL_THRESHOLD, align
+from leanbench.evalstats import auc, confusion, wilson
+from leanbench.lint import lint
+from leanbench.project import project
+from leanbench.srcsimplex import parse_source_simplex
+
+VERDICTS = {"faithful", "minor_drift", "wrong", "not_formalizable"}
+ERRORS = {"missing_hypothesis", "extra_hypothesis", "wrong_type", "quantifier",
+          "wrong_conclusion", "degenerate", "hallucinated_api", "other"}
+
+
+def digest(path: Path) -> str:
+    return hashlib.sha256(path.read_bytes()).hexdigest()
+
+
+def finite(value):
+    if isinstance(value, dict):
+        return {k: finite(v) for k, v in value.items()}
+    if isinstance(value, (list, tuple)):
+        return [finite(v) for v in value]
+    if isinstance(value, float) and not math.isfinite(value):
+        return None
+    return value
+
+
+def unique(rows, field):
+    indexed = {row[field]: row for row in rows}
+    if len(indexed) != len(rows):
+        raise ValueError(f"Duplicate {field}")
+    return indexed
+
+
+def evaluate(items, key, assessment):
+    """Keep model-authored assessments separate from deterministic detector outputs."""
+    by_id = unique(items, "id")
+    records = unique(assessment["records"], "blind_id")
+    if (not key or len(set(key.values())) != len(key) or set(records) != set(key)
+            or set(by_id) != set(key.values())):
+        raise ValueError("Items, key and assessments must cover the same cohort exactly once")
+    output = []
+    for blind, item_id in key.items():
+        item, record = by_id[item_id], records[blind]
+        if record["id"] != item_id or not item.get("source_text", "").strip():
+            raise ValueError(f"Missing source text or mismatched item for {blind}")
+        judge = record["judge"]
+        if (judge.get("verdict") not in VERDICTS or type(judge.get("faithful")) is not bool
+                or judge["faithful"] != (judge["verdict"] == "faithful")
+                or not isinstance(judge.get("reason"), str) or not judge["reason"].strip()
+                or not isinstance(judge.get("errors"), list)
+                or not set(judge["errors"]) <= ERRORS):
+            raise ValueError(f"Invalid authored judgment for {blind}")
+        source = parse_source_simplex(record["source"])
+        projection = project(item["lean_code"])
+        alignment = align(source, projection)
+        output.append({"id": item_id, "blind_id": blind,
+                       "source": source.as_dict(), "judge": judge,
+                       "projection": projection.as_dict(), "role": alignment.as_dict(),
+                       "lint": lint(projection), "compiled": bool(item.get("verified")),
+                       "errors": {}})
+    return output
+
+
+def public_items(rows, labels):
+    if set(labels) != {row["blind_id"] for row in rows}:
+        raise ValueError("Reference labels must cover the entire cohort")
+    out = []
+    for row in rows:
+        reference = labels[row["blind_id"]]["verdict"]
+        if reference not in VERDICTS:
+            raise ValueError("Invalid reference verdict")
+        out.append({"blind_id": row["blind_id"], "reference_verdict": reference,
+                    "assistant_verdict": row["judge"]["verdict"],
+                    "assistant_error_types": row["judge"]["errors"],
+                    "verdict_agrees": reference == row["judge"]["verdict"],
+                    "compiled": row["compiled"], "lint_flagged": bool(row["lint"]),
+                    "role_flagged": row["role"]["flagged"],
+                    "role_score": row["role"]["score"],
+                    "role_conflict_types": row["role"]["errors"],
+                    "source_role_count": len(row["source"]["roles"]),
+                    "lean_role_count": len(row["projection"]["roles"]),
+                    "degenerate_projection": row["projection"]["degenerate"]})
+    return out
+
+
+def agreement(rows, labels, secondary=False):
+    cohort = [r for r in rows if labels[r["blind_id"]]["verdict"] != "not_formalizable"
+              and (secondary or labels[r["blind_id"]]["verdict"] != "minor_drift")]
+    positives = {"wrong", "minor_drift"} if secondary else {"wrong"}
+    target = [labels[r["blind_id"]]["verdict"] in positives for r in cohort]
+    out = {}
+    for name, flags in {
+        "role": [r["role"]["flagged"] for r in cohort],
+        "assistant_judge": [not r["judge"]["faithful"] for r in cohort],
+        "lint": [bool(r["lint"]) for r in cohort],
+        "compile_only": [not r["compiled"] for r in cohort],
+    }.items():
+        counts = confusion(flags, target)
+        out[name] = {**counts.as_dict(), "precision_ci": wilson(counts.tp, counts.tp + counts.fp)}
+    out["role"]["auc"] = auc([-r["role"]["score"] for r in cohort], target)
+    return {"n": len(cohort), "metrics_are_non_independent_reference_agreement": True,
+            "detectors": out}
+
+
+def write_review(path, rows, items):
+    by_id = {r["id"]: r for r in items}
+    sections = []
+    for row in rows:
+        item = by_id[row["id"]]
+        sections.append(
+            f'<section id="{html.escape(row["blind_id"])}"><h2>{row["blind_id"]}</h2>'
+            f'<h3>Passage</h3><pre>{html.escape(item["source_text"])}</pre>'
+            f'<h3>Lean</h3><pre>{html.escape(item["lean_code"])}</pre>'
+            f'<h3>Fresh assistant judgment: {row["judge"]["verdict"]}</h3>'
+            f'<p>{html.escape(row["judge"]["reason"])}</p>'
+            f'<h3>Source roles</h3><pre>{html.escape(json.dumps(row["source"], indent=2, ensure_ascii=False))}</pre>'
+            f'<h3>Deterministic alignment</h3><pre>{html.escape(json.dumps(row["role"], indent=2, ensure_ascii=False))}</pre></section>'
+        )
+    path.write_text('<!doctype html><html lang="en"><meta charset="utf-8">'
+                    '<title>P0 GPT-assisted diagnostic</title><style>'
+                    'body{font:16px/1.6 system-ui;max-width:1050px;margin:32px auto;padding:0 20px}'
+                    'pre{white-space:pre-wrap;overflow-wrap:anywhere;background:#f4f5f6;padding:16px}'
+                    'section{border-top:1px solid #ccc;margin:40px 0}</style>'
+                    '<h1>P0: 65-item GPT-assisted diagnostic</h1>'
+                    '<p>Private review. Same-assistant, non-blind diagnosis; no independent accuracy or gate decision. '
+                    'Passages and model-derived descriptions must remain outside Git.</p>'
+                    + ''.join(sections) + '</html>', encoding="utf-8")
+
+
+def main():
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--items", type=Path, required=True)
+    parser.add_argument("--key", type=Path, required=True)
+    parser.add_argument("--assessments", type=Path, required=True)
+    parser.add_argument("--labels", type=Path, required=True)
+    parser.add_argument("--private-out", type=Path, required=True)
+    parser.add_argument("--summary", type=Path, required=True)
+    parser.add_argument("--public-items", type=Path, required=True)
+    args = parser.parse_args()
+    if "data" not in args.private_out.parts:
+        parser.error("Private output must be under the gitignored data/ directory")
+    items = [json.loads(x) for x in args.items.read_text().splitlines() if x.strip()]
+    key = json.loads(args.key.read_text())["key"]
+    assessment = json.loads(args.assessments.read_text())
+    provenance = assessment["provenance"]
+    if (provenance["items_sha256"] != digest(args.items)
+            or provenance["key_sha256"] != digest(args.key)):
+        parser.error("Authored review is bound to different inputs or blind key")
+    rows = evaluate(items, key, assessment)
+    labels = json.loads(args.labels.read_text())["labels"]
+    public = public_items(rows, labels)
+    summary = {
+        "experiment": "P0-GPT-diagnostic", "status": "complete", "n": len(rows),
+        "provenance": provenance, "decision": None,
+        "decision_withheld_reason": "Same-assistant, non-blind diagnostic; not the preregistered Qwen pilot or independent ground-truth validation.",
+        "hashes": {"items": digest(args.items), "key": digest(args.key),
+                   "assessments": digest(args.assessments), "reference_labels": digest(args.labels),
+                   "replay_script": digest(Path(__file__)),
+                   **{f"leanbench/{name}.py": digest(Path(__file__).resolve().parents[2] / "leanbench" / f"{name}.py")
+                      for name in ("align", "project", "srcsimplex", "lint")}},
+        "fixed_thresholds": {"matching": DEFAULT_THRESHOLD, "goal": GOAL_THRESHOLD},
+        "verdict_counts": dict(Counter(r["judge"]["verdict"] for r in rows)),
+        "role_flagged": sum(r["role"]["flagged"] for r in rows),
+        "lint_flagged": sum(bool(r["lint"]) for r in rows),
+        "compiled": sum(r["compiled"] for r in rows),
+        "degenerate_projection": sum(r["projection"]["degenerate"] for r in rows),
+        "exact_verdict_agreement": sum(r["verdict_agrees"] for r in public),
+        "changed_verdicts": [r["blind_id"] for r in public if not r["verdict_agrees"]],
+        "primary_reference_agreement": agreement(rows, labels),
+        "secondary_reference_agreement": agreement(rows, labels, secondary=True),
+        "role_flagged_by_new_verdict": {v: {"n": sum(r["judge"]["verdict"] == v for r in rows),
+             "flagged": sum(r["judge"]["verdict"] == v and r["role"]["flagged"] for r in rows)}
+             for v in sorted(VERDICTS)},
+    }
+    args.private_out.mkdir(parents=True, exist_ok=True)
+    (args.private_out / "results.jsonl").write_text(''.join(json.dumps(r, ensure_ascii=False) + '\n' for r in rows))
+    write_review(args.private_out / "review.html", rows, items)
+    args.summary.parent.mkdir(parents=True, exist_ok=True)
+    args.public_items.parent.mkdir(parents=True, exist_ok=True)
+    args.summary.write_text(json.dumps(finite(summary), indent=2, allow_nan=False) + '\n')
+    args.public_items.write_text(json.dumps(public, indent=2, allow_nan=False) + '\n')
+    print(json.dumps({k: summary[k] for k in ("n", "status", "verdict_counts", "role_flagged", "exact_verdict_agreement", "decision")}))
+
+
+if __name__ == "__main__":
+    main()

experiments/P0-pilot/labels/labels.json

@@ -0,0 +1,427 @@
+{
+  "labeler": "Codex AI assistant (this chat; exact deployed model identifier unavailable)",
+  "labeler_type": "AI; not human gold",
+  "frozen_at": "2026-10-28T10:42:10.032234+00:00",
+  "items_sha256": "487ecd22919a5e3b0174a2846ab8fe7c0daf4d3feccccf8ea6571aec04c41bed",
+  "key_sha256": "f827cac92ee4e907554fadcc7c0e006ef2b829350f74e7f8b54ca11945e62836",
+  "method": "Single-pass semantic annotation in shuffled blind-ID order; per-item compiler outcomes and detector outputs hidden. Pure syntax/proof defects are ignored when meaning is recoverable. No compiler/API-name audit. Full extracted-span coverage is assessed; unspecified design tasks or unresolved contextual references are not formalizable.",
+  "limitations": [
+    "Single AI annotator; no human adjudication or inter-annotator agreement.",
+    "The annotator reviewed detector implementation and aggregate compilation counts before labeling; only per-item outputs were hidden.",
+    "AI labels replace the originally planned human/Kimi labels by explicit owner instruction in this chat; the original human-ground-truth protocol is therefore not fully satisfied."
+  ],
+  "labels": {
+    "P01": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "The field axioms and nontriviality match the stated definition."
+    },
+    "P02": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "The whole carrier and identity singleton are the two specified subgroups; API spelling is not assessed."
+    },
+    "P03": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "Every integer unit is constrained to the two specified values."
+    },
+    "P04": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "Generated subgroup is equated with all integer powers; escaped notation is treated as a syntax defect."
+    },
+    "P05": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "Existence of a bijective multiplication-preserving map matches the definition."
+    },
+    "P06": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "The theorem statement gives exactly the inverse-of-product identity; proof validity is not assessed."
+    },
+    "P07": {
+      "verdict": "wrong",
+      "errors": [
+        "wrong_conclusion",
+        "degenerate"
+      ],
+      "notes": "Only already-assumed prime factors are asserted to exist; no recovery from the totient is specified."
+    },
+    "P08": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "Both identity preservation and inverse preservation are stated under a multiplicative equivalence."
+    },
+    "P09": {
+      "verdict": "wrong",
+      "errors": [
+        "wrong_type",
+        "wrong_conclusion"
+      ],
+      "notes": "The multiplicative ring carrier does not encode the additive cyclic group, and the second extracted exercise is omitted."
+    },
+    "P10": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "Both left and right equations have unique solutions."
+    },
+    "P11": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "The group cardinality is the exponent, with the correct identity and quantification."
+    },
+    "P12": {
+      "verdict": "not_formalizable",
+      "errors": [
+        "other"
+      ],
+      "notes": "The extracted design question provides no formal security or authentication specification for a fidelity comparison."
+    },
+    "P13": {
+      "verdict": "minor_drift",
+      "errors": [
+        "wrong_type"
+      ],
+      "notes": "The intended modular identity is retained, but the integer variable is supplied to a natural-number coprimality predicate."
+    },
+    "P14": {
+      "verdict": "wrong",
+      "errors": [
+        "wrong_conclusion"
+      ],
+      "notes": "Only existence of a ring structure is stated; the identity and unit characterization are omitted."
+    },
+    "P15": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "Unique solvability in both factors expresses the row and column permutation property."
+    },
+    "P16": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "Passing to the product representation preserves the order-divisibility claim; capitalization and namespace errors are not semantic changes."
+    },
+    "P17": {
+      "verdict": "wrong",
+      "errors": [
+        "wrong_conclusion"
+      ],
+      "notes": "An independent non-field example in the extracted passage is omitted."
+    },
+    "P18": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "The norm-one complex carrier and multiplication describe the specified subgroup; bundling/API validity is not assessed."
+    },
+    "P19": {
+      "verdict": "minor_drift",
+      "errors": [
+        "wrong_type"
+      ],
+      "notes": "The natural-valued order convention needs an infinite-order convention absent from the cardinality definition."
+    },
+    "P20": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "A single left-identity action on one group element forces equality to the identity."
+    },
+    "P21": {
+      "verdict": "minor_drift",
+      "errors": [
+        "wrong_type"
+      ],
+      "notes": "The intended commutativity equivalence is visible, but the left operation lacks the carrier annotation needed to identify G."
+    },
+    "P22": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "The two quantified unique-solvability claims express the specified table property."
+    },
+    "P23": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "Prime factors, modulus, lcm exponent and coprimality reproduce the extracted claim; no unstated distinctness assumption is introduced."
+    },
+    "P24": {
+      "verdict": "wrong",
+      "errors": [
+        "wrong_conclusion",
+        "degenerate"
+      ],
+      "notes": "An arbitrary group satisfying an order condition is not identified with the geometric symmetry group."
+    },
+    "P25": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "The two declarations cover both cancellation directions."
+    },
+    "P26": {
+      "verdict": "wrong",
+      "errors": [
+        "extra_hypothesis",
+        "missing_hypothesis"
+      ],
+      "notes": "The inserted divisibility assumption does not express the RSA relationship required by the argument."
+    },
+    "P27": {
+      "verdict": "wrong",
+      "errors": [
+        "wrong_conclusion"
+      ],
+      "notes": "The isomorphism is asserted for a quotient of the ambient group instead of the stabilizer subgroup."
+    },
+    "P28": {
+      "verdict": "wrong",
+      "errors": [
+        "wrong_type",
+        "wrong_conclusion"
+      ],
+      "notes": "Natural exponent division fails to express a square root, and the homomorphism target does not encode the specified automorphism."
+    },
+    "P29": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "A bijective homomorphism supplies the isomorphism assumption and both power assertions are retained."
+    },
+    "P30": {
+      "verdict": "wrong",
+      "errors": [
+        "wrong_type"
+      ],
+      "notes": "An unordered finite product is used for an arbitrary semigroup, losing the ordered nonempty product required by the exercise."
+    },
+    "P31": {
+      "verdict": "not_formalizable",
+      "errors": [
+        "other"
+      ],
+      "notes": "The isolated instruction refers to an earlier map whose definition is absent; the actual proposition cannot be recovered from this span."
+    },
+    "P32": {
+      "verdict": "wrong",
+      "errors": [
+        "wrong_conclusion",
+        "degenerate"
+      ],
+      "notes": "The result merely supplies an unspecified ring homomorphism and does not constrain it to evaluation at the matrix parameter."
+    },
+    "P33": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "The cardinality assumption and the nonidentity involution conclusion match; the missing instance binder is a compilation defect."
+    },
+    "P34": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "The contrasting abelian properties encode the reason these specified groups are not isomorphic."
+    },
+    "P35": {
+      "verdict": "wrong",
+      "errors": [
+        "wrong_type",
+        "quantifier"
+      ],
+      "notes": "One fixed-arity function is applied at incompatible arities instead of specifying a coherent family of products."
+    },
+    "P36": {
+      "verdict": "wrong",
+      "errors": [
+        "wrong_type",
+        "wrong_conclusion"
+      ],
+      "notes": "The ring carrier replaces the concrete root-of-unity group, and neither its order nor the specified generator is stated."
+    },
+    "P37": {
+      "verdict": "wrong",
+      "errors": [
+        "degenerate",
+        "wrong_conclusion"
+      ],
+      "notes": "The declaration has no defining expression for the requested subgroup."
+    },
+    "P38": {
+      "verdict": "wrong",
+      "errors": [
+        "missing_hypothesis"
+      ],
+      "notes": "Nonemptiness is missing, so the empty subset satisfies both closure assumptions."
+    },
+    "P39": {
+      "verdict": "wrong",
+      "errors": [
+        "wrong_type",
+        "wrong_conclusion"
+      ],
+      "notes": "Laurent series replace finite Laurent polynomials, and the requested units are not characterized."
+    },
+    "P40": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "The supplied structure body fixes the function to the canonical integer residue map."
+    },
+    "P41": {
+      "verdict": "wrong",
+      "errors": [
+        "extra_hypothesis"
+      ],
+      "notes": "The cardinality assertion is restricted to the range where noncommutativity holds, dropping the smaller symmetric groups."
+    },
+    "P42": {
+      "verdict": "wrong",
+      "errors": [
+        "missing_hypothesis",
+        "wrong_conclusion"
+      ],
+      "notes": "A necessary closure condition is promoted to sufficiency without inverse closure."
+    },
+    "P43": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "Any two groups of the specified size are related by a multiplicative equivalence."
+    },
+    "P44": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "The defining field is exactly commutativity of the group operation."
+    },
+    "P45": {
+      "verdict": "wrong",
+      "errors": [
+        "quantifier",
+        "wrong_conclusion"
+      ],
+      "notes": "Literal uniqueness of a carrier/structure replaces uniqueness up to group isomorphism."
+    },
+    "P46": {
+      "verdict": "wrong",
+      "errors": [
+        "wrong_type",
+        "wrong_conclusion"
+      ],
+      "notes": "Univariate polynomials over a product ring replace three-variable real polynomials; the units question is omitted."
+    },
+    "P47": {
+      "verdict": "minor_drift",
+      "errors": [
+        "wrong_conclusion"
+      ],
+      "notes": "The integer-span equality captures the generated set, but the equality for opposite generators is not explicitly stated."
+    },
+    "P48": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "The one-sided inverse hypothesis gives the specified inverse element."
+    },
+    "P49": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "The theorem statement is exactly involutivity of group inversion."
+    },
+    "P50": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "The custom structure supplies additive commutative group, associative multiplication and both distributive laws without imposing a unit."
+    },
+    "P51": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "The carrier, multiplication and identity encode the specified finite group; existence of the chosen API is not audited."
+    },
+    "P52": {
+      "verdict": "minor_drift",
+      "errors": [
+        "wrong_conclusion",
+        "degenerate"
+      ],
+      "notes": "Ring structure and unit-to-constant direction are present, but identity characterization is replaced by reflexivity."
+    },
+    "P53": {
+      "verdict": "minor_drift",
+      "errors": [
+        "extra_hypothesis"
+      ],
+      "notes": "Cardinality is represented only for finite groups although the definition is not restricted to them."
+    },
+    "P54": {
+      "verdict": "wrong",
+      "errors": [
+        "wrong_type"
+      ],
+      "notes": "Multiplicative subgroup closure of a residue is used in place of the additive cyclic subgroup generated by it."
+    },
+    "P55": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "The abelian-property equivalence is stated under an isomorphism."
+    },
+    "P56": {
+      "verdict": "not_formalizable",
+      "errors": [
+        "other"
+      ],
+      "notes": "The design question does not specify an authenticity predicate or formal adversarial model."
+    },
+    "P57": {
+      "verdict": "wrong",
+      "errors": [
+        "wrong_conclusion"
+      ],
+      "notes": "The homomorphism criterion is retained but the separate isomorphism definition is absent."
+    },
+    "P58": {
+      "verdict": "wrong",
+      "errors": [
+        "wrong_type"
+      ],
+      "notes": "A multiplicative equivalence on the full residue ring does not represent the additive cyclic group in the comparison."
+    },
+    "P59": {
+      "verdict": "minor_drift",
+      "errors": [
+        "wrong_type"
+      ],
+      "notes": "The inherited-group criterion is recognizable, but operations on the subset are not specified as restricted operations."
+    },
+    "P60": {
+      "verdict": "wrong",
+      "errors": [
+        "wrong_type",
+        "missing_hypothesis"
+      ],
+      "notes": "Global bijections with local differentiability conditions do not specify self-diffeomorphisms of the open subset."
+    },
+    "P61": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "The homeomorphism type supplies the intended carrier and group structure under composition; notation validity is not assessed."
+    },
+    "P62": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "Both least-positive exponent and the bounded-power description are retained, ignoring set-minimum API syntax."
+    },
+    "P63": {
+      "verdict": "faithful",
+      "errors": [],
+      "notes": "Both two-sided identity hypotheses and their equality are stated."
+    },
+    "P64": {
+      "verdict": "wrong",
+      "errors": [
+        "missing_hypothesis",
+        "extra_hypothesis"
+      ],
+      "notes": "The exponent relation uses the ciphertext modulus where the RSA exponent modulus is required."
+    },
+    "P65": {
+      "verdict": "wrong",
+      "errors": [
+        "wrong_conclusion",
+        "degenerate"
+      ],
+      "notes": "The arbitrary finite group is unrelated to the requested geometric symmetries, with the classification left in a comment."
+    }
+  }
+}

experiments/P0-pilot/make_sheet.py

@@ -154,6 +154,10 @@ def main() -> int:
 
     items = [json.loads(line) for line in args.items.read_text(encoding="utf-8").splitlines()
              if line.strip()]
+    if not items or any(not item.get("source_text", "").strip() for item in items):
+        parser.error("Every item needs nonempty source_text; use a private source-inclusive export.")
+    if len({item["id"] for item in items}) != len(items):
+        parser.error("Item IDs must be unique.")
     order = list(range(len(items)))
     random.Random(args.seed).shuffle(order)
     blind_ids = [f"P{n:02d}" for n in range(1, len(items) + 1)]

experiments/P0-pilot/prepare_items.py

@@ -0,0 +1,45 @@
+"""Restore source passages from a private archived review without changing the cohort."""
+from __future__ import annotations
+
+import argparse
+import json
+from pathlib import Path
+
+
+def restore(items: list[dict], review: dict) -> list[dict]:
+    archived = review["items"]
+    by_id = {row["id"]: row for row in archived}
+    if len(by_id) != len(archived) or len({row["id"] for row in items}) != len(items):
+        raise ValueError("Duplicate item IDs")
+    restored = []
+    for item in items:
+        original = by_id[item["id"]]
+        comparable = dict(original)
+        if isinstance(comparable.get("imports"), str):
+            comparable["imports"] = json.loads(comparable["imports"])
+        if any(comparable.get(k) != v for k, v in item.items()):
+            raise ValueError(f"Archived review does not match item {item['id']}")
+        passage = original.get("source_text", "")
+        if not passage.strip():
+            raise ValueError(f"Missing archived passage for {item['id']}")
+        restored.append({**item, "source_text": passage})
+    return restored
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--items", required=True, type=Path)
+    parser.add_argument("--review", required=True, type=Path)
+    parser.add_argument("--out", required=True, type=Path)
+    args = parser.parse_args()
+    if args.out.parent.name != "data":
+        parser.error("Source-inclusive output must go in a gitignored data/ directory")
+    items = [json.loads(line) for line in args.items.read_text().splitlines() if line.strip()]
+    rows = restore(items, json.loads(args.review.read_text()))
+    args.out.parent.mkdir(parents=True, exist_ok=True)
+    args.out.write_text("".join(json.dumps(row, ensure_ascii=False) + "\n" for row in rows))
+    print(f"Restored {len(rows)} passages; all exported fields are unchanged")
+
+
+if __name__ == "__main__":
+    main()

experiments/P0-pilot/results/gpt-diagnostic-summary.json

@@ -0,0 +1,275 @@
+{
+  "experiment": "P0-GPT-diagnostic",
+  "status": "complete",
+  "n": 65,
+  "provenance": {
+    "run_kind": "current-chat assistant-authored diagnostic; not an API benchmark",
+    "evaluator": "Codex GPT assistant; exact deployed model identifier unavailable",
+    "authored_at": "2026-10-28T11:23:06.275167+00:00",
+    "items_sha256": "487ecd22919a5e3b0174a2846ab8fe7c0daf4d3feccccf8ea6571aec04c41bed",
+    "key_sha256": "f827cac92ee4e907554fadcc7c0e006ef2b829350f74e7f8b54ca11945e62836",
+    "reference_labels_seen_in_prior_chat": true,
+    "lean_seen_while_authoring_source_roles": true,
+    "new_external_api_calls": 0,
+    "assistant_token_usage": null,
+    "limitations": [
+      "Same assistant previously authored the reference labels; agreement is not independent accuracy.",
+      "Prior context contains the earlier review and detector code. This is not a blinded source-only extraction or a fresh-model replicate.",
+      "All judgments are manually authored in this chat, not responses from a GPT API endpoint.",
+      "Semantics are assessed conditionally on recoverable notation. No new Lean compilation or library API audit is performed.",
+      "The strict Boolean judge flags all verdicts except faithful, including not_formalizable; four-way verdicts are also retained."
+    ]
+  },
+  "decision": null,
+  "decision_withheld_reason": "Same-assistant, non-blind diagnostic; not the preregistered Qwen pilot or independent ground-truth validation.",
+  "hashes": {
+    "items": "487ecd22919a5e3b0174a2846ab8fe7c0daf4d3feccccf8ea6571aec04c41bed",
+    "key": "f827cac92ee4e907554fadcc7c0e006ef2b829350f74e7f8b54ca11945e62836",
+    "assessments": "f12735802ba0d4d94b776a91581a13a508eab0ce90ba8973a6c9c4e4d1390272",
+    "reference_labels": "1552dba85e75426799151384e7e28c9a0b1072ed4c862df0876df89920d2a638",
+    "replay_script": "5c02e3d26761ce0b4e38d4be9e65b95bfd8db048c9c7c73edaac17e654e10c0f",
+    "leanbench/align.py": "730e44f1158e6e441e4745dff7324e565b89b6e5148017c3fd93f4c69c22c9ce",
+    "leanbench/project.py": "8ed76924b463ba418ceb732d0fcb6c572a548d94fe7f23759c67746da24d9430",
+    "leanbench/srcsimplex.py": "d10b785299ceb17cadc4e97737eef74183ed390d04b4571a702cd4fd42b069d0",
+    "leanbench/lint.py": "4396e879312f370cd70beeffcbd7ffeab8a41ee1704cc1f235dbbcd6e843fd68"
+  },
+  "fixed_thresholds": {
+    "matching": 0.3,
+    "goal": 0.2
+  },
+  "verdict_counts": {
+    "faithful": 25,
+    "minor_drift": 13,
+    "wrong": 24,
+    "not_formalizable": 3
+  },
+  "role_flagged": 55,
+  "lint_flagged": 21,
+  "compiled": 10,
+  "degenerate_projection": 15,
+  "exact_verdict_agreement": 59,
+  "changed_verdicts": [
+    "P02",
+    "P18",
+    "P23",
+    "P34",
+    "P51",
+    "P57"
+  ],
+  "primary_reference_agreement": {
+    "n": 55,
+    "metrics_are_non_independent_reference_agreement": true,
+    "detectors": {
+      "role": {
+        "tp": 25,
+        "fp": 21,
+        "fn": 0,
+        "tn": 9,
+        "n": 55,
+        "recall": 1.0,
+        "precision": 0.5434782608695652,
+        "false_flag_rate": 0.7,
+        "f1": 0.704225352112676,
+        "recall_ci": [
+          0.8668035060468213,
+          1.0
+        ],
+        "false_flag_ci": [
+          0.5212387898833981,
+          0.8333543735604105
+        ],
+        "precision_ci": [
+          0.4017993496608042,
+          0.67845489578878
+        ],
+        "auc": 0.61
+      },
+      "assistant_judge": {
+        "tp": 25,
+        "fp": 5,
+        "fn": 0,
+        "tn": 25,
+        "n": 55,
+        "recall": 1.0,
+        "precision": 0.8333333333333334,
+        "false_flag_rate": 0.16666666666666666,
+        "f1": 0.9090909090909091,
+        "recall_ci": [
+          0.8668035060468213,
+          1.0
+        ],
+        "false_flag_ci": [
+          0.07336434240351683,
+          0.33564705185680177
+        ],
+        "precision_ci": [
+          0.6643529481431982,
+          0.9266356575964831
+        ]
+      },
+      "lint": {
+        "tp": 12,
+        "fp": 5,
+        "fn": 13,
+        "tn": 25,
+        "n": 55,
+        "recall": 0.48,
+        "precision": 0.7058823529411765,
+        "false_flag_rate": 0.16666666666666666,
+        "f1": 0.5714285714285713,
+        "recall_ci": [
+          0.30031003928960015,
+          0.6650178204685269
+        ],
+        "false_flag_ci": [
+          0.07336434240351683,
+          0.33564705185680177
+        ],
+        "precision_ci": [
+          0.468664666737861,
+          0.8672020613444361
+        ]
+      },
+      "compile_only": {
+        "tp": 24,
+        "fp": 24,
+        "fn": 1,
+        "tn": 6,
+        "n": 55,
+        "recall": 0.96,
+        "precision": 0.5,
+        "false_flag_rate": 0.8,
+        "f1": 0.6575342465753424,
+        "recall_ci": [
+          0.8045552759497747,
+          0.9929039496133008
+        ],
+        "false_flag_ci": [
+          0.6269395261897256,
+          0.9049502189759876
+        ],
+        "precision_ci": [
+          0.36389098932037767,
+          0.6361090106796223
+        ]
+      }
+    }
+  },
+  "secondary_reference_agreement": {
+    "n": 62,
+    "metrics_are_non_independent_reference_agreement": true,
+    "detectors": {
+      "role": {
+        "tp": 32,
+        "fp": 21,
+        "fn": 0,
+        "tn": 9,
+        "n": 62,
+        "recall": 1.0,
+        "precision": 0.6037735849056604,
+        "false_flag_rate": 0.7,
+        "f1": 0.7529411764705882,
+        "recall_ci": [
+          0.8928172849426366,
+          1.0
+        ],
+        "false_flag_ci": [
+          0.5212387898833981,
+          0.8333543735604105
+        ],
+        "precision_ci": [
+          0.4694123578888073,
+          0.7241078808096105
+        ],
+        "auc": 0.590625
+      },
+      "assistant_judge": {
+        "tp": 32,
+        "fp": 5,
+        "fn": 0,
+        "tn": 25,
+        "n": 62,
+        "recall": 1.0,
+        "precision": 0.8648648648648649,
+        "false_flag_rate": 0.16666666666666666,
+        "f1": 0.927536231884058,
+        "recall_ci": [
+          0.8928172849426366,
+          1.0
+        ],
+        "false_flag_ci": [
+          0.07336434240351683,
+          0.33564705185680177
+        ],
+        "precision_ci": [
+          0.7202227252929444,
+          0.9408679273749238
+        ]
+      },
+      "lint": {
+        "tp": 14,
+        "fp": 5,
+        "fn": 18,
+        "tn": 25,
+        "n": 62,
+        "recall": 0.4375,
+        "precision": 0.7368421052631579,
+        "false_flag_rate": 0.16666666666666666,
+        "f1": 0.5490196078431372,
+        "recall_ci": [
+          0.2816508596944317,
+          0.6067469796877387
+        ],
+        "false_flag_ci": [
+          0.07336434240351683,
+          0.33564705185680177
+        ],
+        "precision_ci": [
+          0.5120803155892935,
+          0.8819376166045982
+        ]
+      },
+      "compile_only": {
+        "tp": 29,
+        "fp": 24,
+        "fn": 3,
+        "tn": 6,
+        "n": 62,
+        "recall": 0.90625,
+        "precision": 0.5471698113207547,
+        "false_flag_rate": 0.8,
+        "f1": 0.6823529411764705,
+        "recall_ci": [
+          0.7578150066422116,
+          0.9675990373736805
+        ],
+        "false_flag_ci": [
+          0.6269395261897256,
+          0.9049502189759876
+        ],
+        "precision_ci": [
+          0.41453742646439184,
+          0.6734263183985253
+        ]
+      }
+    }
+  },
+  "role_flagged_by_new_verdict": {
+    "faithful": {
+      "n": 25,
+      "flagged": 16
+    },
+    "minor_drift": {
+      "n": 13,
+      "flagged": 13
+    },
+    "not_formalizable": {
+      "n": 3,
+      "flagged": 2
+    },
+    "wrong": {
+      "n": 24,
+      "flagged": 24
+    }
+  }
+}

experiments/P0-pilot/run_pilot.py

@@ -15,8 +15,11 @@ Hard stops: --max-calls bounds API calls; a rerun skips items already in --out.
 from __future__ import annotations
 
 import argparse
+import fcntl
 import hashlib
+import inspect
 import json
+import os
 import sys
 from pathlib import Path
 
@@ -24,7 +27,7 @@ from leanbench import srcsimplex
 from leanbench.align import align
 from leanbench.config import Settings
 from leanbench.lint import lint
-from leanbench.llm import OpenAICompatibleClient
+from leanbench.llm import OpenAICompatibleClient, Usage
 from leanbench.project import project
 
 JUDGE_PROMPT_VERSION = "judge-v1"
@@ -41,13 +44,15 @@ def judge(client, passage: str, lean: str) -> dict:
         {"role": "system", "content": JUDGE_SYSTEM},
         {"role": "user", "content": f"Passage:\n{passage}\n\nLean:\n{lean}"},
     ])
-    if not isinstance(reply, dict) or "faithful" not in reply:
+    if not isinstance(reply, dict) or type(reply.get("faithful")) is not bool:
         raise ValueError(f"unusable judge reply: {str(reply)[:200]}")
-    return {"faithful": bool(reply["faithful"]), "confidence": reply.get("confidence"),
+    return {"faithful": reply["faithful"], "confidence": reply.get("confidence"),
             "reason": str(reply.get("reason", ""))[:300]}
 
 
 def run_item(client, item: dict) -> dict:
+    if not item.get("source_text", "").strip():
+        raise ValueError("Missing source_text; use a private source-inclusive export")
     code = item.get("lean_code") or ""
     row: dict = {"id": item["id"], "compiled": bool(item.get("verified")), "errors": {}}
     proj = project(code)
@@ -59,51 +64,154 @@ def run_item(client, item: dict) -> dict:
         al = align(src, proj)
         row["source"] = [r.__dict__ for r in src.roles]
         row["role"] = al.as_dict()
+    except CallBudgetExceeded:
+        raise
     except Exception as error:  # a failed extraction is data, not a crash
         row["errors"]["role"] = str(error)[:300]
     try:
         row["judge"] = judge(client, item.get("source_text", ""), code)
+    except CallBudgetExceeded:
+        raise
     except Exception as error:
         row["errors"]["judge"] = str(error)[:300]
     return row
 
 
+class CallBudgetExceeded(RuntimeError):
+    """Stop before issuing a request that would exceed the cumulative budget."""
+
+
+def digest(path: Path) -> str:
+    return hashlib.sha256(path.read_bytes()).hexdigest()
+
+
+def atomic_json(path: Path, value: dict) -> None:
+    temporary = path.with_suffix(path.suffix + ".tmp")
+    temporary.write_text(json.dumps(value, indent=2, allow_nan=False) + "\n", encoding="utf-8")
+    os.replace(temporary, path)
+
+
+class AuditedClient(OpenAICompatibleClient):
+    """Persist reservations before HTTP requests, including transport and JSON retries."""
+
+    def complete(self, *args, **kwargs):
+        try:
+            return super().complete(*args, **kwargs)
+        finally:
+            self.checkpoint()
+
+
+def execute(args, items, settings) -> int:
+    rows = []
+    if args.out.exists():
+        rows = [json.loads(x) for x in args.out.read_text(encoding="utf-8").splitlines() if x.strip()]
+    ids = {item["id"] for item in items}
+    done = {row["id"] for row in rows}
+    if len(done) != len(rows) or not done <= ids:
+        raise ValueError("Results have duplicate or unknown item IDs")
+    hashes = {
+        "source": hashlib.sha256((srcsimplex.SYSTEM_PROMPT + inspect.getsource(srcsimplex.passage_prompt)).encode()).hexdigest(),
+        "judge": hashlib.sha256(JUDGE_SYSTEM.encode()).hexdigest(),
+    }
+    identity = {"model": settings.llm.model, "base_url": settings.llm.base_url,
+                "temperature": settings.llm.temperature, "items_sha256": digest(args.items),
+                "prompt_hashes": hashes,
+                "prompts": [srcsimplex.PROMPT_VERSION, JUDGE_PROMPT_VERSION]}
+    labels = getattr(args, "labels", None)
+    if labels is not None:
+        identity["labels_sha256"] = digest(labels)
+    meta_path = args.out.with_suffix(".meta.json")
+    meta = {**identity, "request_attempts": 0, "usage": Usage().as_dict(), "status": "ready"}
+    if meta_path.exists():
+        meta = json.loads(meta_path.read_text(encoding="utf-8"))
+        if any(meta.get(k) != v for k, v in identity.items()):
+            raise ValueError("Run identity changed; use a new output path instead of mixing runs")
+    elif rows:
+        raise ValueError("Cannot resume results without their audit metadata")
+    todo = [item for item in items if item["id"] not in done]
+    print(f"items={len(items)} done={len(done)} todo={len(todo)} model={settings.llm.model} "
+          f"nominal_calls={len(todo) * 2} request_attempts={meta['request_attempts']} cap={args.max_calls}")
+    print("prompt_hashes:", json.dumps(hashes))
+    if args.dry_run:
+        return 0
+    if settings.llm.model != "qwen-max" or settings.llm.temperature != 0:
+        raise ValueError("P0 is preregistered for qwen-max at temperature 0")
+    client = AuditedClient.from_settings(settings.llm)
+    client.usage = Usage(**meta["usage"])
+
+    def checkpoint():
+        meta["usage"] = client.usage.as_dict()
+        meta["completed_items"] = len(done)
+        atomic_json(meta_path, meta)
+
+    def reserve():
+        if meta["request_attempts"] >= args.max_calls:
+            raise CallBudgetExceeded("Cumulative request cap reached; no further HTTP request was sent")
+        meta["request_attempts"] += 1
+        checkpoint()
+
+    client.checkpoint = checkpoint
+    client.request_guard = reserve
+    meta["max_calls"] = args.max_calls
+    meta["status"] = "running"
+    checkpoint()
+    try:
+        with args.out.open("a", encoding="utf-8") as stream:
+            for item in todo:
+                row = run_item(client, item)
+                stream.write(json.dumps(row, ensure_ascii=False) + "\n")
+                stream.flush()
+                os.fsync(stream.fileno())
+                done.add(item["id"])
+                checkpoint()
+                print(f"completed={len(done)}/{len(items)} requests={meta['request_attempts']}", flush=True)
+        meta["status"] = "complete"
+    except CallBudgetExceeded as error:
+        meta["status"] = "budget_exhausted"
+        print(str(error), file=sys.stderr)
+    except BaseException:
+        meta["status"] = "interrupted"
+        raise
+    finally:
+        if args.out.exists():
+            meta["results_sha256"] = digest(args.out)
+        checkpoint()
+    print(json.dumps(meta))
+    return 0 if meta["status"] == "complete" else 2
+
+
 def main() -> int:
     ap = argparse.ArgumentParser(description=__doc__.splitlines()[0])
     ap.add_argument("--items", required=True, type=Path)
     ap.add_argument("--out", required=True, type=Path)
     ap.add_argument("--max-calls", type=int, default=400)
     ap.add_argument("--dry-run", action="store_true")
+    ap.add_argument("--labels", type=Path, help="Frozen labels; their hash is bound to the run")
     args = ap.parse_args()
-
+    if not 1 <= args.max_calls <= 400:
+        ap.error("P0 requires a request cap between 1 and 400")
     items = [json.loads(x) for x in args.items.read_text(encoding="utf-8").splitlines() if x.strip()]
-    done = set()
-    if args.out.exists():
-        done = {json.loads(x)["id"] for x in args.out.read_text(encoding="utf-8").splitlines() if x.strip()}
-    todo = [i for i in items if i["id"] not in done]
-    settings = Settings.from_env()
-    est = len(todo) * 3  # extract (<=2 tries) + judge
-    print(f"items={len(items)} done={len(done)} todo={len(todo)} model={settings.llm.model} "
-          f"est_calls<={est} (extract x2 + judge) cap={args.max_calls}")
-    print("prompts:", srcsimplex.PROMPT_VERSION, JUDGE_PROMPT_VERSION,
-          hashlib.sha256((srcsimplex.SYSTEM_PROMPT + JUDGE_SYSTEM).encode()).hexdigest()[:12])
-    if args.dry_run:
-        return 0
-
-    client = OpenAICompatibleClient.from_settings(settings.llm)
+    if not items or len({item["id"] for item in items}) != len(items):
+        ap.error("Input must contain unique item IDs")
+    if any(not item.get("source_text", "").strip() for item in items):
+        ap.error("Every item needs nonempty source_text; use a private source-inclusive export")
+    if not args.dry_run and args.labels is None:
+        ap.error("Freeze all blind labels first, then pass --labels")
+    if args.labels is not None:
+        annotation = json.loads(args.labels.read_text(encoding="utf-8"))
+        key_path = args.labels.with_name("key.json")
+        key = json.loads(key_path.read_text(encoding="utf-8"))["key"]
+        verdicts = {"faithful", "minor_drift", "wrong", "not_formalizable"}
+        if (set(key.values()) != {item["id"] for item in items}
+                or set(annotation["labels"]) != set(key)
+                or any(row.get("verdict") not in verdicts for row in annotation["labels"].values())
+                or annotation.get("items_sha256") != digest(args.items)
+                or annotation.get("key_sha256") != digest(key_path)):
+            ap.error("Frozen labels, key and source-inclusive items must be complete and match")
     args.out.parent.mkdir(parents=True, exist_ok=True)
-    with args.out.open("a", encoding="utf-8") as fh:
-        for item in todo:
-            if client.usage.calls >= args.max_calls:
-                print("call cap reached; rerun to resume", file=sys.stderr)
-                break
-            fh.write(json.dumps(run_item(client, item), ensure_ascii=False) + "\n")
-            fh.flush()
-    meta = {"model": settings.llm.model, "usage": client.usage.as_dict(),
-            "prompts": [srcsimplex.PROMPT_VERSION, JUDGE_PROMPT_VERSION]}
-    (args.out.parent / "run_meta.json").write_text(json.dumps(meta, indent=2), encoding="utf-8")
-    print(json.dumps(meta))
-    return 0
+    with args.out.with_suffix(args.out.suffix + ".lock").open("w") as lock:
+        fcntl.flock(lock, fcntl.LOCK_EX | fcntl.LOCK_NB)
+        return execute(args, items, Settings.from_env())
 
 
 if __name__ == "__main__":

experiments/P0-pilot/score.py

@@ -1,9 +1,9 @@
-"""Score the pilot: detectors vs. the blind human labels, with the pre-registered decision.
+"""Score the pilot against frozen blind labels using the pre-registered decision.
 
     python experiments/P0-pilot/score.py --results experiments/P0-pilot/data/results.jsonl \
         --labels experiments/P0-pilot/labels/labels.json --key experiments/P0-pilot/labels/key.json --summary experiments/P0-pilot/results/summary.json
 
-Positive class = unfaithful. Primary: verdict == "wrong", over ALL labeled items (role alignment and
+Positive class = unfaithful. Primary: wrong versus faithful, excluding minor drift (role alignment and
 the judge do not need Lean to accept the code; only 10 of the 65 pilot items compiled, too few to
 decide on). Secondary: wrong or minor_drift; and the compiled-only subset (the paper's claim, reported
 with its interval, not used to decide). "not_formalizable" items are excluded. Decision (fixed before
@@ -19,22 +19,35 @@ With ~65 items every number carries a wide Wilson interval; the pilot checks for
 from __future__ import annotations
 
 import argparse
+import hashlib
 import json
+import math
 from pathlib import Path
 
-from leanbench.evalstats import auc, confusion
+from leanbench.evalstats import auc, confusion, wilson
 
 
 def load(args):
-    results = {json.loads(x)["id"]: json.loads(x) for x in args.results.read_text(encoding="utf-8").splitlines() if x.strip()}
+    result_rows = [json.loads(x) for x in args.results.read_text(encoding="utf-8").splitlines() if x.strip()]
+    results = {row["id"]: row for row in result_rows}
     labels = json.loads(args.labels.read_text(encoding="utf-8"))["labels"]
     key = json.loads(args.key.read_text(encoding="utf-8"))["key"]
+    if not key or len(set(key.values())) != len(key):
+        raise ValueError("The blind key must contain unique item IDs")
+    if len(results) != len(result_rows) or set(results) != set(key.values()):
+        raise ValueError("Results must cover every keyed item exactly once")
+    if set(labels) != set(key):
+        raise ValueError("Labels must cover every blind ID exactly once")
     rows = []
     for blind, item_id in key.items():
         lab = labels.get(blind) or {}
-        if item_id in results and lab.get("verdict"):
-            rows.append({**results[item_id], "blind": blind, "verdict": lab["verdict"],
-                         "human_errors": lab.get("errors", [])})
+        if lab.get("verdict") not in {"faithful", "minor_drift", "wrong", "not_formalizable"}:
+            raise ValueError(f"Missing or invalid verdict for {blind}")
+        row = results[item_id]
+        if row.get("errors") or "judge" not in row or "role" not in row:
+            raise ValueError(f"Unresolved detector failure for {blind}; no decision can be issued")
+        rows.append({**row, "blind": blind, "verdict": lab["verdict"],
+                     "human_errors": lab.get("errors", [])})
     return rows
 
 
@@ -51,19 +64,24 @@ def report(rows, positive):
     out = {}
     for name in ("compile_only", "lint", "role", "judge"):
         out[name] = confusion([flags(r)[name] for r in rows], [positive(r) for r in rows]).as_dict()
+        out[name]["precision_ci"] = wilson(out[name]["tp"], out[name]["tp"] + out[name]["fp"])
     out["role"]["auc_score"] = auc([-(r.get("role", {}).get("score", 1.0)) for r in rows],
                                    [positive(r) for r in rows])
+    out["role"]["complementary_wrong"] = sum(
+        positive(r) and flags(r)["role"] and not flags(r)["judge"] for r in rows
+    )
     return out
 
 
 def decide(sub):
     role, judge = sub["role"], sub["judge"]
-    if role["tp"] + role["fn"] == 0:
-        return "INSUFFICIENT: no wrong items in the labels"
+    if role["tp"] + role["fn"] == 0 or role["fp"] + role["tn"] == 0:
+        return "INSUFFICIENT: both wrong and faithful items are required"
     go = (role["recall"] >= 0.5 and role["false_flag_rate"] <= 0.2
           and role["recall"] >= judge["recall"] + 0.10
           and role["false_flag_rate"] <= judge["false_flag_rate"])
-    partial = (role["recall"] >= 0.4 and role["false_flag_rate"] <= 0.3)
+    partial = ((role["recall"] >= 0.4 and role["false_flag_rate"] <= 0.3)
+               or role.get("complementary_wrong", 0) >= 3)
     return "GO" if go else "PARTIAL" if partial else "NO-GO"
 
 
@@ -75,19 +93,51 @@ def main() -> int:
     ap.add_argument("--summary", type=Path, default=None,
                     help="also write the (text-free) summary here, e.g. results/summary.json")
     args = ap.parse_args()
-    rows = [r for r in load(args) if r["verdict"] != "not_formalizable"]
-    compiled = [r for r in rows if r["compiled"]]
+    meta = json.loads(args.results.with_suffix(".meta.json").read_text(encoding="utf-8"))
+    if (meta.get("status") != "complete"
+            or meta.get("labels_sha256") != hashlib.sha256(args.labels.read_bytes()).hexdigest()
+            or meta.get("results_sha256") != hashlib.sha256(args.results.read_bytes()).hexdigest()):
+        ap.error("Scoring requires a complete run with unchanged frozen labels and results")
+    all_rows = load(args)
+    rows = [r for r in all_rows if r["verdict"] != "not_formalizable"]
+    primary = [r for r in rows if r["verdict"] != "minor_drift"]
+    compiled = [r for r in primary if r["compiled"]]
     summary = {
-        "n_labeled": len(rows), "n_compiled": len(compiled),
+        "run_metadata": meta,
+        "n_labeled": len(all_rows), "n_evaluable": len(rows), "n_primary": len(primary),
+        "n_compiled": len(compiled),
         "verdicts": {v: sum(r["verdict"] == v for r in rows) for v in
-                     ("faithful", "minor_drift", "wrong")},
+                     ("faithful", "minor_drift", "wrong", "not_formalizable")},
         "compiled_but_wrong": sum(r["verdict"] == "wrong" for r in compiled),
-        "primary_all": report(rows, lambda r: r["verdict"] == "wrong"),
+        "primary_all": report(primary, lambda r: r["verdict"] == "wrong"),
         "secondary_all": report(rows, lambda r: r["verdict"] in ("wrong", "minor_drift")),
         "compiled_only": report(compiled, lambda r: r["verdict"] == "wrong"),
     }
+    summary["verdicts"]["not_formalizable"] = len(all_rows) - len(rows)
+    summary["role_recall_by_error"] = {
+        error: {"flagged": sum(flags(r)["role"] for r in rows
+                                if r["verdict"] == "wrong" and error in r["human_errors"]),
+                "total": sum(r["verdict"] == "wrong" and error in r["human_errors"] for r in rows)}
+        for error in sorted({e for r in rows for e in r["human_errors"]})
+    }
+    summary["degenerate_projection"] = {
+        "total": sum(bool(r.get("projection", {}).get("degenerate")) for r in all_rows),
+        "wrong": sum(r["verdict"] == "wrong" and bool(r.get("projection", {}).get("degenerate"))
+                     for r in all_rows),
+    }
+    summary["disagreements"] = [
+        {"blind": r["blind"], "verdict": r["verdict"], "flags": flags(r)}
+        for r in primary if any(f != (r["verdict"] == "wrong") for f in flags(r).values())
+    ]
     summary["decision"] = decide(summary["primary_all"])
-    text = json.dumps(summary, indent=2, default=str)
+    def finite_json(value):
+        if isinstance(value, dict):
+            return {k: finite_json(v) for k, v in value.items()}
+        if isinstance(value, (list, tuple)):
+            return [finite_json(v) for v in value]
+        return None if isinstance(value, float) and not math.isfinite(value) else value
+
+    text = json.dumps(finite_json(summary), indent=2, allow_nan=False)
     if args.summary:
         args.summary.parent.mkdir(parents=True, exist_ok=True)
         args.summary.write_text(text + "\n", encoding="utf-8")

leanbench/llm.py

@@ -14,7 +14,7 @@ import re
 import time
 import urllib.error
 import urllib.request
-from collections.abc import Iterable
+from collections.abc import Callable, Iterable
 from dataclasses import dataclass, field
 from typing import Any, Protocol
 
@@ -66,6 +66,7 @@ class OpenAICompatibleClient:
     max_retries: int = 4
     temperature: float = 0.0
     usage: Usage = field(default_factory=Usage)
+    request_guard: Callable[[], None] | None = field(default=None, repr=False)
 
     @classmethod
     def from_settings(cls, settings: LLMSettings) -> OpenAICompatibleClient:
@@ -97,6 +98,8 @@ class OpenAICompatibleClient:
         }
         last: Exception | None = None
         for attempt in range(self.max_retries + 1):
+            if self.request_guard is not None:
+                self.request_guard()
             request = urllib.request.Request(url, data=body, headers=headers, method="POST")
             try:
                 with urllib.request.urlopen(request, timeout=self.timeout) as response:

tests/test_assistant_diagnostic.py

@@ -0,0 +1,74 @@
+"""Current-chat review replay is offline, complete and text-free at its public boundary."""
+import copy
+import importlib.util
+from pathlib import Path
+
+import pytest
+
+PATH = Path(__file__).resolve().parents[1] / "experiments/P0-pilot/assistant_diagnostic.py"
+SPEC = importlib.util.spec_from_file_location("assistant_diagnostic", PATH)
+DIAG = importlib.util.module_from_spec(SPEC)
+SPEC.loader.exec_module(DIAG)
+
+ITEM = {"id": "synthetic", "source_text": "Synthetic private prose.",
+        "lean_code": "theorem t (n : Nat) : n = n := rfl", "verified": True}
+ASSESSMENT = {"records": [{"id": "synthetic", "blind_id": "P01", "source": {
+    "roles": [{"kind": "object", "symbols": ["n"], "description": "Private object wording",
+               "keywords": ["natural"]},
+              {"kind": "goal", "description": "Private goal wording", "keywords": ["equal"]}],
+    "goal_has_exists": False},
+    "judge": {"verdict": "faithful", "faithful": True, "errors": [],
+              "reason": "Private reviewer explanation"}}]}
+
+
+def test_offline_replay_and_text_free_public_output(monkeypatch):
+    def no_network(*args, **kwargs):
+        raise AssertionError("Replay must not call an API")
+
+    monkeypatch.setattr("urllib.request.urlopen", no_network)
+    rows = DIAG.evaluate([ITEM], {"P01": "synthetic"}, ASSESSMENT)
+    assert len(rows) == 1 and rows[0]["errors"] == {}
+    public = DIAG.public_items(rows, {"P01": {"verdict": "faithful"}})
+    assert public[0]["assistant_verdict"] == "faithful"
+    assert not any(word in str(public) for word in ["Private", "Synthetic", "explanation"])
+    assert all(key not in public[0] for key in ["source", "judge", "reason", "lean_code", "source_text"])
+
+
+def test_duplicate_or_missing_assessments_are_rejected():
+    assessment = copy.deepcopy(ASSESSMENT)
+    assessment["records"] *= 2
+    with pytest.raises(ValueError, match="Duplicate"):
+        DIAG.evaluate([ITEM], {"P01": "synthetic"}, assessment)
+    with pytest.raises(ValueError, match="same cohort"):
+        DIAG.evaluate([ITEM], {"P01": "synthetic"}, {"records": []})
+
+
+def test_mismatched_item_and_missing_source_are_rejected():
+    assessment = copy.deepcopy(ASSESSMENT)
+    assessment["records"][0]["id"] = "different"
+    with pytest.raises(ValueError, match="mismatched"):
+        DIAG.evaluate([ITEM], {"P01": "synthetic"}, assessment)
+    with pytest.raises(ValueError, match="Missing source"):
+        DIAG.evaluate([{**ITEM, "source_text": ""}], {"P01": "synthetic"}, ASSESSMENT)
+
+
+def test_judge_cannot_disagree_with_its_boolean_flag():
+    assessment = copy.deepcopy(ASSESSMENT)
+    assessment["records"][0]["judge"]["faithful"] = False
+    with pytest.raises(ValueError, match="Invalid authored judgment"):
+        DIAG.evaluate([ITEM], {"P01": "synthetic"}, assessment)
+
+
+def test_invalid_source_schema_is_rejected():
+    assessment = copy.deepcopy(ASSESSMENT)
+    assessment["records"][0]["source"]["roles"] = []
+    with pytest.raises(ValueError, match="goal"):
+        DIAG.evaluate([ITEM], {"P01": "synthetic"}, assessment)
+
+
+def test_agreement_is_explicitly_not_independent_and_has_no_gate():
+    rows = DIAG.evaluate([ITEM], {"P01": "synthetic"}, ASSESSMENT)
+    result = DIAG.agreement(rows, {"P01": {"verdict": "faithful"}})
+    assert result["metrics_are_non_independent_reference_agreement"] is True
+    assert "decision" not in result
+    assert DIAG.finite(float("nan")) is None

tests/test_pilot_scripts.py

@@ -36,3 +36,108 @@ def test_run_item_and_score(tmp_path):
     out = sc.report(rows, lambda r: r["verdict"] == "wrong")
     assert out["judge"]["n"] == 4
     assert sc.decide(out) in {"GO", "PARTIAL", "NO-GO"}
+
+
+def test_complementary_signal_is_partial():
+    sc = load("score")
+    rows = [
+        {"compiled": True, "lint": [], "role": {"flagged": i < 3, "score": 0.1},
+         "judge": {"faithful": False if 3 <= i < 8 else True}, "verdict": "wrong"}
+        for i in range(10)
+    ] + [
+        {"compiled": True, "lint": [], "role": {"flagged": False, "score": 1},
+         "judge": {"faithful": True}, "verdict": "faithful"}
+    ]
+    summary = sc.report(rows, lambda row: row["verdict"] == "wrong")
+    assert summary["role"]["recall"] == 0.3
+    assert summary["role"]["complementary_wrong"] == 3
+    assert sc.decide(summary) == "PARTIAL"
+
+
+def test_score_rejects_missing_labels_and_detector_failures(tmp_path):
+    import argparse
+    import json
+
+    import pytest
+
+    sc = load("score")
+    args = argparse.Namespace(results=tmp_path / "results.jsonl", labels=tmp_path / "labels.json",
+                              key=tmp_path / "key.json")
+    args.key.write_text(json.dumps({"key": {"P01": "x1"}}))
+    args.labels.write_text(json.dumps({"labels": {"P01": {"verdict": None}}}))
+    args.results.write_text(json.dumps({"id": "x1"}) + "\n")
+    with pytest.raises(ValueError, match="verdict"):
+        sc.load(args)
+    args.labels.write_text(json.dumps({"labels": {"P01": {"verdict": "wrong"}}}))
+    with pytest.raises(ValueError, match="detector failure"):
+        sc.load(args)
+    args.results.write_text("")
+    with pytest.raises(ValueError, match="every keyed item"):
+        sc.load(args)
+
+
+def test_request_budget_survives_resume_and_transport_retries(tmp_path, monkeypatch):
+    import argparse
+    import json
+    import urllib.error
+
+    import pytest
+
+    from leanbench.config import Settings
+
+    rp = load("run_pilot")
+    args = argparse.Namespace(items=tmp_path / "items.jsonl", out=tmp_path / "results.jsonl",
+                              max_calls=2, dry_run=False)
+    args.items.write_text(json.dumps(ITEM) + "\n")
+    monkeypatch.setenv("DASHSCOPE_API_KEY", "test-only")
+    settings = Settings()
+    settings.llm.max_retries = 5
+    requests = []
+
+    def fail(*args, **kwargs):
+        requests.append(1)
+        raise urllib.error.URLError("offline test")
+
+    monkeypatch.setattr("urllib.request.urlopen", fail)
+    monkeypatch.setattr("leanbench.llm.time.sleep", lambda *_: None)
+    assert rp.execute(args, [ITEM], settings) == 2
+    assert len(requests) == 2
+    assert rp.execute(args, [ITEM], settings) == 2
+    assert len(requests) == 2
+    meta = json.loads(args.out.with_suffix(".meta.json").read_text())
+    assert meta["request_attempts"] == 2
+    assert len(meta["prompt_hashes"]["judge"]) == 64
+    assert meta["status"] == "budget_exhausted"
+    settings.llm.model = "other-model"
+    with pytest.raises(ValueError, match="identity changed"):
+        rp.execute(args, [ITEM], settings)
+
+
+def test_run_rejects_missing_source_passage():
+    import pytest
+
+    rp = load("run_pilot")
+    with pytest.raises(ValueError, match="Missing source_text"):
+        rp.run_item(Stub(), {**ITEM, "source_text": ""})
+
+
+def test_restore_passages_checks_cohort_and_normalizes_archived_imports():
+    import pytest
+
+    prepare = load("prepare_items")
+    item = {"id": "x", "lean_code": "example : True := trivial", "imports": ["Mathlib"]}
+    original = {**item, "imports": '["Mathlib"]', "source_text": "A private passage."}
+    restored = prepare.restore([item], {"items": [original]})
+    assert restored == [{**item, "source_text": "A private passage."}]
+    with pytest.raises(ValueError, match="does not match"):
+        prepare.restore([{**item, "lean_code": "changed"}], {"items": [original]})
+
+
+def test_judge_rejects_string_boolean():
+    import pytest
+
+    from leanbench.llm import ScriptedClient
+
+    rp = load("run_pilot")
+    with pytest.raises(ValueError, match="unusable judge"):
+        rp.judge(ScriptedClient(['{"faithful": "false"}']), "passage", "code")