Audit pipeline PR #9: determinism + fact extraction + verifier gate + KB stats #9
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Summary
Closes the determinism + learning-loop gaps surfaced by the 9-consecutive-audit empirical test on PR #8. Five commits (A-E), ~650 LOC net.
A. N=3 consensus on cloud inference (
2afad0f)Primary reviewer (gpt-oss:120b) runs N=3 times in parallel, majority-vote per claim. Tie-breaker:
qwen3-coder:480b— newer coding specialist, distinct architecture. Every run-to-run disagreement logged todata/_kb/audit_discrepancies.jsonl. Verified: 2 back-to-back audits on unchanged PR #8 produced identical 8 findings — previously theproven escalation ladderblock was flipping.B. scrum_master fact extraction (
181c35b)Accepted scrum reviews route through
fact_extractor(same llm_team extract pipeline as inference) and append toaudit_facts.jsonltaggedsource:"scrum_review". One KB, two producers.C. Verifier-gated persistence + schema_version (
181c35b)fact_extractorparses the verifier's per-fact verdicts (CORRECT/INCORRECT/UNVERIFIABLE/UNCHECKED). Drops facts marked INCORRECT; keeps UNVERIFIABLE (verifier's prior-knowledge doesn't cover Lakehouse internals, so UNVERIFIABLE is the default for real domain signal). Addsschema_version: 2to new rows, old rows remain readable.D. scrum_master_reviewed flag (
181c35b)scrum_master_reviewed: trueon accepted scrum review rows + their fact-extraction rows.E. kb_stats.ts observability (
a264bcf)One TS script that reads every KB jsonl and prints: verdict distribution, per-PR verdict instability, consensus discrepancy rate, KB size + distinct signatures, verifier verdict histogram, top recurring entities. --json for machine-readable output. The Grafana alternative — zero infra.
Explicitly deferred to PR #10+
playbook_memory/seed(Rust hybrid indexing matrix) — waiting on canonical schema keys before building the mapper.kb_stats.tsgives 90% of the dashboard value at 0 ops cost; we revisit if scale demands it.Test plan
🤖 Generated with Claude Code
Real end-to-end test of the Lakehouse pipeline at scale. Runs the PRD (63 KB, 901 lines → 93 chunks) through 6 iterations with cloud inference, intentional failure injection, and tight context budget to force every Phase 21 primitive to fire. What the test exercises: - Sidecar /embed for 93 chunks (nomic-embed-text) - In-memory cosine retrieval for top-K per iteration - Tree-split (shard → summarize → scratchpad → merge) when context chunks exceed the 4000-char budget - Scratchpad truncation to keep compounding context bounded - Cloud inference via /v1/chat provider=ollama_cloud (gpt-oss:120b) - Injected primary-cloud failure on iter 3 (invalid model name) + rescue with gpt-oss:20b — proves catch-and-retry isn't dead code - Playbook seeding per iteration (real HTTP against gateway) - Prior-iteration answer injection for compounding (not just IDs — the first version passed IDs only and the model ignored them) Live run results (tests/real-world/runs/moamj810/): 6/6 iterations complete, 42 cloud calls total, 245s end-to-end tree-splits: 6/6 (every iter overflowed 4K budget) continuations: 0 (no responses hit max_tokens) rescues: 1 (iter 3 injected failure → gpt-oss:20b → valid answer) iter 6 answer explicitly cites [pb:pb-seed-82e1] — compounding real scratchpad truncation fired on iter 6 as designed What this PROVES: - Tree-split primitives work under real context pressure, not just in unit tests. The 4000-char budget forced every iteration to shard 12 chunks → 6 shards → scratchpad → final answer. - Rescue on primary failure is wired and produces answers from a weaker model rather than erroring out. - Compounding context injection works: iter 6's prompt had the 5 prior answers in its citation block, and the cloud model acknowledged at least one via [pb:...] notation. - The existence claims in Phase 21 (continuation + tree-split) are backed by executable evidence, not just unit tests. What this DOESN'T prove (deliberate — scoped for follow-up): - Continuation retries (no iter hit max_tokens in this run; would need a harder prompt or lower max_tokens to force) - Real integration with /vectors/hybrid endpoint (test does in-memory cosine instead, bypassing gateway vector surface) - Observer consumption of these runs (nothing posted to :3800 during the test — adding that is Phase A integration, handled separately) Files: tests/real-world/enrich_prd_pipeline.ts (333 LOC) tests/real-world/runs/moamj810/{iter_1..6.json, summary.json} — artifacts from the stress run, committed for inspection Follow-ups worth doing: 1. Lower max_tokens / harder prompt to force continuation path 2. Route retrieval through /vectors/hybrid for real Phase 19 boost 3. POST per-iteration summary to observer :3800 so runs accumulate like scenario runs do Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>Two distinct retry loops now both cap at 6 and serve different purposes: 1. Per-cloud-call continuation (Phase 21 primitive) — when a single cloud call returns empty or truncated, stitches up to 6 continuation calls. Handles output-overflow. 2. Per-TASK retry (this commit) — when the whole task errors (500/404, thin answer, etc.), retries the full task up to 6 times. Each retry gets PRIOR ATTEMPTS' failures injected into the prompt as learning context, so attempt N+1 is informed by what N failed at. Handles error-recovery with compounding context. Both loops fired on iter 3 of the stress run, proving them independent and composable: FORCING TASK-RETRY LOOP — iter 3 will cycle through 5 invalid models + 1 valid attempt 1/6: model=deliberately-invalid-model-attempt-1 /v1/chat 502: ollama.com 404: model not found attempt 2/6: [with prior-failure context] ... (5 failures total, each with the full chain of prior errors) attempt 6/6: model=gpt-oss:20b [with prior-failure context] continuation retry 1..6 (empty responses) SUCCEEDED after 5 prior failures (441 chars) What J was asking to prove: "I expect it to retry the process six times to build on the knowledge database... when an error is legitimately triggered that it will go through six times... without getting caught in a loop" Proof: - 6/6 attempts fired on the FORCED iteration - Each retry embedded the preceding attempts' errors as "do not repeat" context - Hard cap at MAX_TASK_RETRIES (6) prevents infinite loops - Last-ditch local fallback exists if all 6 still fail - Other iterations succeed on attempt 1 — the loop ONLY fires when errors are legitimately triggered Stress run totals (runs/moan4h71/): 6/6 iterations complete, 58 cloud calls, 306s end-to-end tree-splits: 6/6 continuations: 10 rescues: 2 iter 3: 8197+2800 tok, 6 task attempts, 6 continuation retries local stored summary + per-iter JSON for inspection What this proves that prior stress runs did NOT: - Error-recovery at task granularity is live, not aspirational - Compounding failure context flows between retries as text - Loop bound is enforced; runaway cases aren't possible - Two retry mechanisms compose without deadlock (continuation inside task-retry inside tree-split) Follow-ups worth doing (separate PRs): - Persist retry-history to observer :3800 so cross-run learning sees the failure patterns - Route retries through /vectors/hybrid to surface similar prior errors from the real KB (currently only in-memory across one iteration) - Fix citation regex in summary — iter 6 received 5 prior IDs but counter shows 0 (regex needs to tolerate hyphens in IDs)J asked (2026-04-22): construct a task the local model provably can't complete, then watch the escalation + retry + cloud pipeline actually solve it. The task: generate a Rust async function with 15 specific structural rules (exact signature, bounded concurrency, exponential backoff 250/500/1000ms, NO .unwrap(), rustdoc comments, etc.). Small enough to fit in one response but strict enough that one rule violation = not accepted. Fits Rust + async + concurrency + error-handling — across the hardest dimensions for 7B models. Escalation ladder (corrected per J — kimi-k2.x requires Ollama Cloud Pro subscription which J's key lacks; mistral-large-3:675b is the biggest provisioned model): 1. qwen3.5:latest (local 7B) 2. qwen3:latest (local 7B) 3. gpt-oss:20b (local 20B) 4. gpt-oss:120b (cloud 120B) 5. devstral-2:123b (cloud 123B coding specialist) 6. mistral-large-3:675b (cloud 675B — biggest available) Each attempt gets PRIOR failures' rubric violations injected as learning context. Loop caps at MAX_ATTEMPTS=6. Live run (runs/hard_task_moapd3g3/): attempt 1: qwen3.5:latest 11/15 — missed concurrency + some constraints attempt 2: qwen3:latest 11/15 — different misses after learning attempt 3: gpt-oss:20b 0/1 — empty response (local model dead-end) attempt 4: gpt-oss:120b 0/1 — empty (heavy learning context may confuse) attempt 5: devstral-2:123b 15/15 ✅ ACCEPTED after 10.4s attempt 6: (not reached) Total: 5 attempts, 145.6s, coding-specialist succeeded. Honest findings from the run: - Pipeline works: escalated through 4 distinct model tiers, injected learning, bounded at 6, graceful failure surfaces. - Learning injection doesn't always help general-purpose models — gpt-oss:120b returned empty when given heavy prior-failure context (attempt 4). The coding specialist (devstral) worked better because the task is domain-aligned. - Local 7B came within 4 rules of success first-try (11/15) — not bad for the scale, but specific constraints like "EXACT signature" and "bounded concurrency at 4" are where small models slip. - Kimi K2.5/K2.6 both require a paid subscription on our current Ollama Cloud key — verified via direct ollama.com curl. Swap to kimi once subscription lands. Also includes a rubric bug-fix caught in the run: the regex for "reaches 500/1000ms backoff" originally required literal constants, but devstral-2:123b wrote idiomatic `retry_delay *= 2;` which doubles 250 → 500 → 1000 correctly. Broadened rubric to recognize `*= 2`, bit-shift, `.pow()`, and literal forms. Without this the ladder would have false-failed on semantically-correct code. Files: tests/real-world/hard_task_escalation.ts (270 LOC) tests/real-world/runs/hard_task_moapd3g3/ attempt_{1..5}.txt — raw model outputs (last successful) attempt_{1..5}.json — per-attempt rubric verdict + error summary.json — ladder summary What this PROVES that no prior test did: - Task-level retry ESCALATES across distinct model capabilities (not just same model retried) - Bigger and more-specialized models ACTUALLY solve what smaller ones can't — the ladder works by design, not by luck - The subscription boundary (Kimi K2.x) is a real operational constraint, not a code issue - Rubric engineering is its own discipline — a strict-but-wrong validator can reject correct code; shipping the test harness required tuning against actual model outputs Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>The orchestrator J described: pulls git repo source + PRD + suggested-changes doc, chunks them, hands each code piece through the proven escalation ladder with learning context, collects per-file suggestions in a consolidated handoff report. Composes ONLY already-shipped primitives — no new core code: - chunker with 800-char / 120-overlap windows - sidecar /embed for real nomic-embed-text embeddings - in-memory cosine retrieval for top-5 PRD + top-5 proposal chunks per target file - escalation ladder (qwen3.5 → qwen3 → gpt-oss:20b → gpt-oss:120b → devstral-2:123b → mistral-large-3:675b) - per-attempt learning-context injection (prior failures as "do not repeat" block) - acceptance rubric (length ≥ 200 chars + structured form) Live-run (tests/real-world/runs/scrum_moatqkee/): targets: 3 files - crates/vectord/src/playbook_memory.rs (920 lines) - crates/vectord/src/doc_drift.rs (163 lines) - auditor/audit.ts (170 lines) resolved: 3/3 on attempt 1 by qwen3.5:latest local 7B total duration: 111.7s output: scrum_report.md + per-file JSON Sample from scrum_report.md (playbook_memory.rs review): - Alignment score: 9/10 vs PRD Phase 19 - 4 concrete change suggestions naming specific lines + PLAN/PRD chunk offsets - 3 gap analyses with PRD-reference citations Honest findings from this run: 1. Local 7B handled review-style tasks first-try. The escalation ladder infrastructure is live but didn't fire — review is an easier task shape than strict code-generation (see hard_task test which needed devstral-2 specialist). 2. 6KB file-truncation caused one false positive: model claimed playbook_memory.rs lacks a `doc_refs` field, but that field exists past the 6KB cutoff. Trade-off between context-size and review-depth needs tuning per file. 3. Chunk-offset citations are real: model output includes `[PRD @27880]` and `[PLAN @16320]` which map to the actual byte offsets of retrieved context chunks. Auditor pattern could adopt this for traceable claims. This is the scrum-master-handoff shape J asked for: repo + PRD + proposal → chunk → retrieve → escalate → consolidate → human-reviewable markdown report Not shipping: per-PR diff analysis, open-PR integration, Gitea posting of suggestions. Those compose the same primitives differently — this proves the core pattern. Env override: LH_SCRUM_FILES=path1,path2,... to target a different file set. Default 3 files keeps runtime ~2min. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>Phase 1 — definition-layer over append-only JSONL scratchpads. auditor/kb_index.ts is the single shared aggregator: aggregate<T>(jsonlPath, { keyFn, scopeFn, checkFn, tailLimit }) → Map<signature, {count, distinct_scopes, confidence, first_seen, last_seen, representative_summary, ...}> ratingSeverity(agg) — confidence × count severity policy shared across all KB readers. Kills the "same unfixed PR inflates its own recurrence score" failure mode by design: confidence = distinct_scopes/count, so same-scope noise stays below the 0.3 escalation threshold no matter how many times it repeats. checkAuditLessons now routes through aggregate + ratingSeverity. Net effect: the recurrence detector's bespoke Map/Set bookkeeping is gone; same behavior, shared discipline, reusable by scrum/observer. Also: symbolsExistInRepo now skips files >500KB so the audit can't get stuck slurping a fixture. Phase 2 — nine-consecutive audit runner. tests/real-world/nine_consecutive_audits.ts pushes 9 empty commits, waits for each verdict, captures the audit_lessons aggregate state after each run, reports: - sig_count trajectory (should stabilize, not grow linearly) - max_count trajectory (same-signature repeat rate) - max_confidence trajectory (must stay LOW on same-PR noise) - verdict_stable across runs (must NOT oscillate) This is the empirical proof that the KB compounds favorably: noise doesn't escalate itself, and signal stays distinguishable. Unit-tested both failure modes: same-PR × 9 repeats = conf=0.11 (info); cross-PR × 5 distinct = conf=1.00 (block). The rating function correctly discriminates.Auditor verdict: 🛑
blockOne-liner: 4 blocking issues: cloud: claim not backed — "Primary reviewer (gpt-oss:120b) runs N=3 times in parallel, majority-vote per claim. Tie-breaker:
q" **Head SHA:**a264bcf3fcb4`Audited at: 2026-04-23T04:46:50.656Z
dynamic — 1 findings (0 block, 0 warn, 1 info)
ℹ️ info — dynamic check skipped — skipped by options
skipped by optionsinference — 13 findings (4 block, 8 warn, 1 info)
ℹ️ info — cloud review completed (model=gpt-oss:120b, consensus=3/3, tokens=5121) (curated: 150847 chars → 34 shards → scratchpad 0 chars)
claims voted: 12parsed runs: 3 / 3🛑 block — cloud: claim not backed — "Primary reviewer (gpt-oss:120b) runs N=3 times in parallel, majority-vote per claim. Tie-breaker: `q"
at pr_body:6consensus: 2/3 not-backed (resolution: majority_not_backed)cloud reason: No supporting code in diff⚠️ warn — cloud: claim not backed — "- Token-aware diff splitting (vs char-based). Current char-split works; tokenizer integration would "
at pr_body:23consensus: 2/3 not-backed (resolution: majority_not_backed)cloud reason: No supporting code in diff🛑 block — cloud: claim not backed — "8 findings (the "proven escalation ladder" block) was flipping across"
at commit:2afad0f8:4consensus: 2/3 not-backed (resolution: majority_not_backed)cloud reason: No supporting code in diff🛑 block — cloud: claim not backed — "Verified end-to-end on PR #8: 102KB diff → 23 shards → 1KB scratchpad"
at commit:77650c4b:36consensus: 2/3 not-backed (resolution: majority_not_backed)cloud reason: No supporting code in diff⚠️ warn — cloud: claim not backed — "Small-prompt tests passed because the model could respond without"
at commit:47f1ca73:10consensus: 2/3 not-backed (resolution: majority_not_backed)cloud reason: No supporting code in diff🛑 block — cloud: claim not backed — "the proven escalation ladder with learning context, collects"
at commit:a7aba319:5consensus: 2/3 not-backed (resolution: majority_not_backed)cloud reason: No supporting code in diff⚠️ warn — cloud: claim not backed — "Composes ONLY already-shipped primitives — no new core code:"
at commit:a7aba319:8consensus: 2/3 not-backed (resolution: majority_not_backed)cloud reason: No supporting code in diff⚠️ warn — cloud: claim not backed — "complete, then watch the escalation + retry + cloud pipeline actually"
at commit:540c493f:4consensus: 2/3 not-backed (resolution: majority_not_backed)cloud reason: No supporting code in diff⚠️ warn — cloud: claim not backed — "ones can't — the ladder works by design, not by luck"
at commit:540c493f:70consensus: 2/3 not-backed (resolution: majority_not_backed)cloud reason: No supporting code in diff⚠️ warn — cloud: claim not backed — "the first version passed IDs only and the model ignored them)"
at commit:4458c94f:19consensus: 2/3 not-backed (resolution: majority_not_backed)cloud reason: No supporting code in diff⚠️ warn — cloud: claim not backed — "- Rescue on primary failure is wired and produces answers from a"
at commit:4458c94f:33consensus: 2/3 not-backed (resolution: majority_not_backed)cloud reason: No supporting code in diff⚠️ warn — cloud: claim not backed — "- Compounding context injection works: iter 6's prompt had the 5"
at commit:4458c94f:35consensus: 2/3 not-backed (resolution: majority_not_backed)cloud reason: No supporting code in diffkb_query — 10 findings (0 block, 0 warn, 10 info)
ℹ️ info — KB: 71 recent scenario runs, 210/291 events ok (fail rate 27.8%)
most recent: ?recent failing sigs: 5745bcd5e4c68591, caeeeffc69d36009, pr6-7fe47babℹ️ info — scrum-master review for
auditor/audit.ts— accepted on attempt 1 byollama/qwen3.5:latest(tree-split)reviewed_at: 2026-04-23T02:16:08.936Zpreview: # Review:auditor/audit.tsvs. Lakehouse PRD & Integration Plan ## 1. Alignment Score **Score: 4/10** **Rationale:** The file implements a core audit orchestration funℹ️ info — audit_facts KB has 22 entity-observations across 1 PRs (no cross-PR recurrences yet)
source: /home/profit/lakehouse/data/_kb/audit_facts.jsonlℹ️ info — recurring audit pattern (1 distinct PRs, 13 flaggings, conf=0.08): cloud: claim not backed — "Composes ONLY already-shipped primitives — no new core code:"
signature=081018b68d52a4bfchecks: inferencescopes: pr-8ℹ️ info — recurring audit pattern (1 distinct PRs, 10 flaggings, conf=0.10): cloud: claim not backed — "ones can't — the ladder works by design, not by luck"
signature=3d98a2324b5c6414checks: inferencescopes: pr-8ℹ️ info — recurring audit pattern (1 distinct PRs, 13 flaggings, conf=0.08): cloud: claim not backed — "the first version passed IDs only and the model ignored them)"
signature=443ca7da70aeae2echecks: inferencescopes: pr-8ℹ️ info — recurring audit pattern (1 distinct PRs, 7 flaggings, conf=0.14): cloud: claim not backed — "the proven escalation ladder with learning context, collects"
signature=cf09820847e8d9e1checks: inferencescopes: pr-8ℹ️ info — recurring audit pattern (1 distinct PRs, 10 flaggings, conf=0.10): cloud: claim not backed — "- Rescue on primary failure is wired and produces answers from a"
signature=b67055d5567b441echecks: inferencescopes: pr-8ℹ️ info — recurring audit pattern (1 distinct PRs, 5 flaggings, conf=0.20): cloud: claim not backed — "complete, then watch the escalation + retry + cloud pipeline actually"
signature=58efac40f0ca42aechecks: inferencescopes: pr-8ℹ️ info — recurring audit pattern (1 distinct PRs, 5 flaggings, conf=0.20): cloud: claim not backed — "- Compounding context injection works: iter 6's prompt had the 5"
signature=781f0d5cb30d5d32checks: inferencescopes: pr-8Metrics
Lakehouse auditor · SHA
a264bcf3· re-audit on new commit flips the status automatically.Auditor verdict: 🛑
blockOne-liner: 1 blocking issue: cloud: claim not backed — "now classify as empirical; fresh claims like "Phase 45 shipped" stay"
Head SHA:
b25e36881c33Audited at: 2026-04-23T04:59:10.665Z
dynamic — 1 findings (0 block, 0 warn, 1 info)
ℹ️ info — dynamic check skipped — skipped by options
skipped by optionsinference — 7 findings (1 block, 5 warn, 1 info)
ℹ️ info — cloud review completed (model=gpt-oss:120b, consensus=3/3, tokens=6250) (curated: 152738 chars → 34 shards → scratchpad 706 chars)
claims voted: 6parsed runs: 3 / 3⚠️ warn — cloud: claim not backed — "- Token-aware diff splitting (vs char-based). Current char-split works; tokenizer integration would "
at pr_body:23consensus: 3/3 not-backed (resolution: majority_not_backed)cloud reason: Diff only adds regex patterns for diff-splitting; no token-aware or tokenizer integration shown.🛑 block — cloud: claim not backed — "now classify as empirical; fresh claims like "Phase 45 shipped" stay"
at commit:b25e3688:22consensus: 3/3 not-backed (resolution: majority_not_backed)cloud reason: No changes to classification logic are present in the diff.⚠️ warn — cloud: claim not backed — "Small-prompt tests passed because the model could respond without"
at commit:47f1ca73:10consensus: 3/3 not-backed (resolution: majority_not_backed)cloud reason: No test files or test functions were added in the diff.⚠️ warn — cloud: claim not backed — "Composes ONLY already-shipped primitives — no new core code:"
at commit:a7aba319:8consensus: 3/3 not-backed (resolution: majority_not_backed)cloud reason: New constants, regex patterns, and interface fields constitute new core code, contradicting the claim.⚠️ warn — cloud: claim not backed — "complete, then watch the escalation + retry + cloud pipeline actually"
at commit:540c493f:4consensus: 3/3 not-backed (resolution: majority_not_backed)cloud reason: No escalation/retry/cloud pipeline code or end‑to‑end verification is present.⚠️ warn — cloud: claim not backed — "ones can't — the ladder works by design, not by luck"
at commit:540c493f:70consensus: 3/3 not-backed (resolution: majority_not_backed)cloud reason: The claim refers to a 'ladder' design; the diff contains no related implementation.kb_query — 11 findings (0 block, 2 warn, 9 info)
ℹ️ info — KB: 71 recent scenario runs, 210/291 events ok (fail rate 27.8%)
most recent: ?recent failing sigs: 5745bcd5e4c68591, caeeeffc69d36009, pr6-7fe47babℹ️ info — scrum-master review for
auditor/audit.ts— accepted on attempt 1 byollama/qwen3.5:latest(tree-split)reviewed_at: 2026-04-23T02:16:08.936Zpreview: # Review:auditor/audit.tsvs. Lakehouse PRD & Integration Plan ## 1. Alignment Score **Score: 4/10** **Rationale:** The file implements a core audit orchestration funℹ️ info — audit_facts KB has 22 entity-observations across 1 PRs (no cross-PR recurrences yet)
source: /home/profit/lakehouse/data/_kb/audit_facts.jsonlℹ️ info — recurring audit pattern (2 distinct PRs, 14 flaggings, conf=0.14): cloud: claim not backed — "Composes ONLY already-shipped primitives — no new core code:"
signature=081018b68d52a4bfchecks: inferencescopes: pr-8,pr-9ℹ️ info — recurring audit pattern (2 distinct PRs, 11 flaggings, conf=0.18): cloud: claim not backed — "ones can't — the ladder works by design, not by luck"
signature=3d98a2324b5c6414checks: inferencescopes: pr-8,pr-9ℹ️ info — recurring audit pattern (2 distinct PRs, 14 flaggings, conf=0.14): cloud: claim not backed — "the first version passed IDs only and the model ignored them)"
signature=443ca7da70aeae2echecks: inferencescopes: pr-8,pr-9ℹ️ info — recurring audit pattern (2 distinct PRs, 8 flaggings, conf=0.25): cloud: claim not backed — "the proven escalation ladder with learning context, collects"
signature=cf09820847e8d9e1checks: inferencescopes: pr-8,pr-9ℹ️ info — recurring audit pattern (2 distinct PRs, 11 flaggings, conf=0.18): cloud: claim not backed — "- Rescue on primary failure is wired and produces answers from a"
signature=b67055d5567b441echecks: inferencescopes: pr-8,pr-9⚠️ warn — recurring audit pattern (2 distinct PRs, 6 flaggings, conf=0.33): cloud: claim not backed — "complete, then watch the escalation + retry + cloud pipeline actually"
signature=58efac40f0ca42aechecks: inferencescopes: pr-8,pr-9⚠️ warn — recurring audit pattern (2 distinct PRs, 6 flaggings, conf=0.33): cloud: claim not backed — "- Compounding context injection works: iter 6's prompt had the 5"
signature=781f0d5cb30d5d32checks: inferencescopes: pr-8,pr-9ℹ️ info — recurring audit pattern (2 distinct PRs, 2 flaggings, conf=1.00): cloud: claim not backed — "Small-prompt tests passed because the model could respond without"
signature=e0d31c00efd1a86dchecks: inferencescopes: pr-8,pr-9Metrics
Lakehouse auditor · SHA
b25e3688· re-audit on new commit flips the status automatically.Two fixes observed in test sweep on b25e368: 1. The "Phase 45 shipped" quoted test example in a commit message body was triggering STRONG_PATTERNS despite being inside quotes — produced a block finding that flipped 1/0/1 across 3 back-to-back audits. Same bug class as auditor/checks/static.ts (fixed earlier): rubric files quote pattern examples, parser can't distinguish. Fix: firstUnquotedMatch() wraps firstMatch(); uses isInsideQuotedString() to check whether the regex's match position falls inside double / single / backtick quotes on the line. Mirrors static.ts exactly. 2. A regex misfire: `(?:PR|commit|prior|...)` in history/proof patterns was matching "verified ... in production" because `PR` (2 chars) matched the first 2 chars of "production" before the `\s*#?\w*` tail absorbed the rest. Tightened to require a digit after PR (`PR\s*#?\d+`) and commit to require a hex hash. Verified: 3 back-to-back audit_one runs before this fix showed the Phase 45 block flipping 1/0/1; after these fixes, unit tests confirm quoted examples skip correctly AND real claims ("Phase 45 shipped", "verified end-to-end against production", "Verified end-to-end on PR #8") still classify correctly.Auditor verdict: ⚠️
request_changesOne-liner: 7 warnings — see review
Head SHA:
2a97fd72370bAudited at: 2026-04-23T05:24:40.161Z
dynamic — 1 findings (0 block, 0 warn, 1 info)
ℹ️ info — dynamic check skipped — skipped by options
skipped by optionsinference — 6 findings (0 block, 5 warn, 1 info)
ℹ️ info — cloud review completed (model=gpt-oss:120b, consensus=3/3, tokens=4376) (curated: 155464 chars → 35 shards → scratchpad 114 chars)
claims voted: 5parsed runs: 3 / 3⚠️ warn — cloud: claim not backed — "- Token-aware diff splitting (vs char-based). Current char-split works; tokenizer integration would "
at pr_body:23consensus: 3/3 not-backed (resolution: majority_not_backed)cloud reason: Diff only adds imports; no token-aware diff splitting implementation.⚠️ warn — cloud: claim not backed — "audits. Same bug class as auditor/checks/static.ts (fixed earlier):"
at commit:2a97fd72:8consensus: 3/3 not-backed (resolution: majority_not_backed)cloud reason: No audit-related code or changes present in diff.⚠️ warn — cloud: claim not backed — "Small-prompt tests passed because the model could respond without"
at commit:47f1ca73:10consensus: 3/3 not-backed (resolution: majority_not_backed)cloud reason: No test code added; diff only shows imports.⚠️ warn — cloud: claim not backed — "Composes ONLY already-shipped primitives — no new core code:"
at commit:a7aba319:8consensus: 3/3 not-backed (resolution: majority_not_backed)cloud reason: Diff shows only import statements, no composition logic or usage of existing primitives.⚠️ warn — cloud: claim not backed — "complete, then watch the escalation + retry + cloud pipeline actually"
at commit:540c493f:4consensus: 3/3 not-backed (resolution: majority_not_backed)cloud reason: No escalation, retry, or cloud pipeline code present.kb_query — 13 findings (0 block, 2 warn, 11 info)
ℹ️ info — KB: 71 recent scenario runs, 210/291 events ok (fail rate 27.8%)
most recent: ?recent failing sigs: 5745bcd5e4c68591, caeeeffc69d36009, pr6-7fe47babℹ️ info — scrum-master review for
auditor/audit.ts— accepted on attempt 1 byollama/qwen3.5:latest(tree-split)reviewed_at: 2026-04-23T02:16:08.936Zpreview: # Review:auditor/audit.tsvs. Lakehouse PRD & Integration Plan ## 1. Alignment Score **Score: 4/10** **Rationale:** The file implements a core audit orchestration funℹ️ info — core entity
mkdirrecurs in 2 PRs (types: Function)count=3 distinct_PRs=2description: A function imported from 'node:fs/promises' for creating directoriesPRs: 8,9ℹ️ info — core entity
writeFilerecurs in 2 PRs (types: Function)count=2 distinct_PRs=2description: A function imported from 'node:fs/promises' for writing filesPRs: 8,9ℹ️ info — recurring audit pattern (2 distinct PRs, 15 flaggings, conf=0.13): cloud: claim not backed — "Composes ONLY already-shipped primitives — no new core code:"
signature=081018b68d52a4bfchecks: inferencescopes: pr-8,pr-9ℹ️ info — recurring audit pattern (2 distinct PRs, 12 flaggings, conf=0.17): cloud: claim not backed — "ones can't — the ladder works by design, not by luck"
signature=3d98a2324b5c6414checks: inferencescopes: pr-8,pr-9ℹ️ info — recurring audit pattern (2 distinct PRs, 14 flaggings, conf=0.14): cloud: claim not backed — "the first version passed IDs only and the model ignored them)"
signature=443ca7da70aeae2echecks: inferencescopes: pr-8,pr-9ℹ️ info — recurring audit pattern (2 distinct PRs, 8 flaggings, conf=0.25): cloud: claim not backed — "the proven escalation ladder with learning context, collects"
signature=cf09820847e8d9e1checks: inferencescopes: pr-8,pr-9ℹ️ info — recurring audit pattern (2 distinct PRs, 11 flaggings, conf=0.18): cloud: claim not backed — "- Rescue on primary failure is wired and produces answers from a"
signature=b67055d5567b441echecks: inferencescopes: pr-8,pr-9ℹ️ info — recurring audit pattern (2 distinct PRs, 7 flaggings, conf=0.29): cloud: claim not backed — "complete, then watch the escalation + retry + cloud pipeline actually"
signature=58efac40f0ca42aechecks: inferencescopes: pr-8,pr-9⚠️ warn — recurring audit pattern (2 distinct PRs, 6 flaggings, conf=0.33): cloud: claim not backed — "- Compounding context injection works: iter 6's prompt had the 5"
signature=781f0d5cb30d5d32checks: inferencescopes: pr-8,pr-9⚠️ warn — recurring audit pattern (2 distinct PRs, 3 flaggings, conf=0.67): cloud: claim not backed — "Small-prompt tests passed because the model could respond without"
signature=e0d31c00efd1a86dchecks: inferencescopes: pr-8,pr-9ℹ️ info — recurring audit pattern (1 distinct PRs, 2 flaggings, conf=0.50): cloud: claim not backed — "- Token-aware diff splitting (vs char-based). Current char-split works; tokenizer integration would "
signature=7511bfe51c2b9859checks: inferencescopes: pr-9Metrics
Lakehouse auditor · SHA
2a97fd72· re-audit on new commit flips the status automatically.Two bundled changes. Both came out of J's observation that the verifier was defaulting to UNVERIFIABLE on domain-specific facts because it had no idea what Lakehouse was, which project's code it was reading, or what framework the types belonged to. 1. Project context preamble. Added docs/AUDITOR_CONTEXT.md — a <400- word concise description of the project (crates, services, architecture phases, the auditor's role itself). fact_extractor reads it once, caches it, prepends it to the extract prompt as a "PROJECT CONTEXT (for grounding; do NOT extract from this)" section. Both extractor and verifier now see this context, so statements like "aggregate<T> returns Map<string, AggregateRow>" get grounded as "this is a TypeScript function in the Lakehouse auditor subsystem" and the verifier can reason about plausibility instead of guessing. 2. Verifier-verdict parser fix. Gemma2's output format varies between "**Verdict:** CORRECT" and just "* **CORRECT**" inline (observed variance across runs). The old regex required "Verdict:" as a label and missed the second format — causing all verdicts to stay UNCHECKED. Replaced with a two-pass approach: find each fact section start ("**N.**" or "N."), slice to the next section, scan the slice for the first CORRECT|INCORRECT|UNVERIFIABLE token. Handles both formats plus unfenced fallback. Verified: 4-fact test extraction went from 0/4 verdicts scored (pre-fix) to 2/4 CORRECT + 2/4 UNVERIFIABLE (post-fix). The 2 UNVERIFIABLE cases are domain-specific code behavior the verifier legitimately can't confirm without reading source — correct stance, not a parser miss. No new consensus modes yet. J suggested adding codereview or validator as a second pass; holding until we see whether context injection alone gives sufficient signal lift.Auditor verdict: ⚠️
request_changesOne-liner: 8 warnings — see review
Head SHA:
56dbfb7d0314Audited at: 2026-04-23T05:33:22.924Z
dynamic — 1 findings (0 block, 0 warn, 1 info)
ℹ️ info — dynamic check skipped — skipped by options
skipped by optionsinference — 6 findings (0 block, 5 warn, 1 info)
ℹ️ info — cloud review completed (model=gpt-oss:120b, consensus=3/3, tokens=5386) (curated: 161083 chars → 36 shards → scratchpad 887 chars)
claims voted: 5parsed runs: 3 / 3⚠️ warn — cloud: claim not backed — "- Token-aware diff splitting (vs char-based). Current char-split works; tokenizer integration would "
at pr_body:23consensus: 3/3 not-backed (resolution: majority_not_backed)cloud reason: Diff only adds constants and imports; no token-aware diff splitting implementation or tokenizer integration is present.⚠️ warn — cloud: claim not backed — "fact_extractor: project context + fixed verifier-verdict parser"
at commit:56dbfb7d:1consensus: 3/3 not-backed (resolution: majority_not_backed)cloud reason: Only an import ofextractFactsis shown; no new fact_extractor logic or verifier‑verdict parser fixes are evident.⚠️ warn — cloud: claim not backed — "audits. Same bug class as auditor/checks/static.ts (fixed earlier):"
at commit:2a97fd72:8consensus: 3/3 not-backed (resolution: majority_not_backed)cloud reason: No modifications to audit‑related code appear in the diff.⚠️ warn — cloud: claim not backed — "Small-prompt tests passed because the model could respond without"
at commit:47f1ca73:10consensus: 3/3 not-backed (resolution: majority_not_backed)cloud reason: No test files or test functions are added in the shown diff.⚠️ warn — cloud: claim not backed — "Composes ONLY already-shipped primitives — no new core code:"
at commit:a7aba319:8consensus: 3/3 not-backed (resolution: majority_not_backed)cloud reason: New interface and constants are introduced, which constitute new core code rather than pure composition of existing primitives.kb_query — 15 findings (0 block, 3 warn, 12 info)
ℹ️ info — KB: 71 recent scenario runs, 210/291 events ok (fail rate 27.8%)
most recent: ?recent failing sigs: 5745bcd5e4c68591, caeeeffc69d36009, pr6-7fe47babℹ️ info — scrum-master review for
auditor/audit.ts— accepted on attempt 1 byollama/qwen3.5:latest(tree-split)reviewed_at: 2026-04-23T02:16:08.936Zpreview: # Review:auditor/audit.tsvs. Lakehouse PRD & Integration Plan ## 1. Alignment Score **Score: 4/10** **Rationale:** The file implements a core audit orchestration funℹ️ info — core entity
mkdirrecurs in 2 PRs (types: Function)count=3 distinct_PRs=2description: A function imported from 'node:fs/promises' for creating directoriesPRs: 8,9ℹ️ info — core entity
writeFilerecurs in 2 PRs (types: Function)count=2 distinct_PRs=2description: A function imported from 'node:fs/promises' for writing filesPRs: 8,9ℹ️ info — core entity
aggregaterecurs in 2 PRs (types: Function)count=2 distinct_PRs=2description: A function imported from the file./kb_index.ts.PRs: 8,9ℹ️ info — recurring audit pattern (2 distinct PRs, 16 flaggings, conf=0.13): cloud: claim not backed — "Composes ONLY already-shipped primitives — no new core code:"
signature=081018b68d52a4bfchecks: inferencescopes: pr-8,pr-9ℹ️ info — recurring audit pattern (2 distinct PRs, 12 flaggings, conf=0.17): cloud: claim not backed — "ones can't — the ladder works by design, not by luck"
signature=3d98a2324b5c6414checks: inferencescopes: pr-8,pr-9ℹ️ info — recurring audit pattern (2 distinct PRs, 14 flaggings, conf=0.14): cloud: claim not backed — "the first version passed IDs only and the model ignored them)"
signature=443ca7da70aeae2echecks: inferencescopes: pr-8,pr-9ℹ️ info — recurring audit pattern (2 distinct PRs, 8 flaggings, conf=0.25): cloud: claim not backed — "the proven escalation ladder with learning context, collects"
signature=cf09820847e8d9e1checks: inferencescopes: pr-8,pr-9ℹ️ info — recurring audit pattern (2 distinct PRs, 11 flaggings, conf=0.18): cloud: claim not backed — "- Rescue on primary failure is wired and produces answers from a"
signature=b67055d5567b441echecks: inferencescopes: pr-8,pr-9ℹ️ info — recurring audit pattern (2 distinct PRs, 8 flaggings, conf=0.25): cloud: claim not backed — "complete, then watch the escalation + retry + cloud pipeline actually"
signature=58efac40f0ca42aechecks: inferencescopes: pr-8,pr-9⚠️ warn — recurring audit pattern (2 distinct PRs, 6 flaggings, conf=0.33): cloud: claim not backed — "- Compounding context injection works: iter 6's prompt had the 5"
signature=781f0d5cb30d5d32checks: inferencescopes: pr-8,pr-9⚠️ warn — recurring audit pattern (2 distinct PRs, 4 flaggings, conf=0.50): cloud: claim not backed — "Small-prompt tests passed because the model could respond without"
signature=e0d31c00efd1a86dchecks: inferencescopes: pr-8,pr-9⚠️ warn — recurring audit pattern (1 distinct PRs, 3 flaggings, conf=0.33): cloud: claim not backed — "- Token-aware diff splitting (vs char-based). Current char-split works; tokenizer integration would "
signature=7511bfe51c2b9859checks: inferencescopes: pr-9ℹ️ info — recurring audit pattern (1 distinct PRs, 2 flaggings, conf=0.50): recurring audit pattern (2 distinct PRs, 6 flaggings, conf=0.33): cloud: claim not backed — "- Compounding context injection works: iter 6's prompt had the 5"
signature=b2723ac9ec67784dchecks: kb_queryscopes: pr-9Metrics
Lakehouse auditor · SHA
56dbfb7d· re-audit on new commit flips the status automatically.