Auditor self-test branch: real-world pipelines + cohesion Phase C + KB index (PR #8)
Bundles 12 commits validating the auditor + scrum_master architecture end-to-end: - enrich_prd_pipeline / hard_task_escalation / scrum_master_pipeline stress tests - Tree-split + scrum_reviews.jsonl + kb_query surfacing - Verdict → audit_lessons feedback loop (closed) - kb_index aggregator with confidence-based severity policy - 9-run + 5-run empirical tests proved the predictive-compounding property - Level 1 correction: temp=0 cloud inference for deterministic per-claim verdicts - audit_one.ts dry-run CLI - Fixes: static quoted-string guard, empirical-claim classification, symbol-resolver gate, repo-file size cap See PR #8 for run-by-run commit history.
This commit was merged in pull request #8.
This commit is contained in:
@@ -33,6 +33,13 @@ Defaults: polls every 90s, stops on `auditor.paused` file present.
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- `data/_auditor/state.json` — last-audited head SHA per PR
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- `data/_auditor/verdicts/{pr}-{sha}.json` — per-run verdict record
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- `data/_kb/audit_lessons.jsonl` — one row per block/warn finding,
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path-agnostic signature for dedup. Tailed by kb_query on each audit
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to surface recurring patterns (2+ distinct PRs with same signature
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→ info, 3-4 → warn, 5+ → block). This is how the auditor learns.
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- `data/_kb/scrum_reviews.jsonl` — scrum-master per-file reviews. If
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a file in the current PR has been scrum-reviewed, kb_query surfaces
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the review as a finding with the accepted model and attempt count.
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## Where YOU edit
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+53
-2
@@ -12,7 +12,8 @@
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// review — reviews have self-review restrictions on Gitea and the
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// auditor currently uses the same PAT as the PR author).
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import { readFile, writeFile, mkdir } from "node:fs/promises";
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import { readFile, writeFile, mkdir, appendFile } from "node:fs/promises";
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import { createHash } from "node:crypto";
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import { join } from "node:path";
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import type { PrSnapshot, Verdict, Finding } from "./types.ts";
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import { getPrDiff, postCommitStatus, postIssueComment } from "./gitea.ts";
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@@ -24,6 +25,10 @@ import { runInferenceCheck } from "./checks/inference.ts";
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import { runKbCheck } from "./checks/kb_query.ts";
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const VERDICTS_DIR = "/home/profit/lakehouse/data/_auditor/verdicts";
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// Playbook for audit findings — one row per block/warn finding from a
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// verdict. kb_query tails this next audit and escalates recurrences.
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// Structured as JSONL so it's cheap to append and cheap to tail.
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const AUDIT_LESSONS_JSONL = "/home/profit/lakehouse/data/_kb/audit_lessons.jsonl";
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export interface AuditOptions {
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// Skip the cloud inference call (fast path for iteration). Default false.
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@@ -52,7 +57,7 @@ export async function auditPr(pr: PrSnapshot, opts: AuditOptions = {}): Promise<
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runStaticCheck(diff),
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opts.skip_dynamic ? Promise.resolve(stubFinding("dynamic", "skipped by options")) : runDynamicCheck(),
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opts.skip_inference ? Promise.resolve(stubFinding("inference", "skipped by options")) : runInferenceCheck(claims, diff),
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runKbCheck(claims),
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runKbCheck(claims, pr.files.map(f => f.path)),
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]);
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const allFindings: Finding[] = [
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@@ -72,6 +77,7 @@ export async function auditPr(pr: PrSnapshot, opts: AuditOptions = {}): Promise<
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claims_strong: claims.filter(c => c.strength === "strong").length,
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claims_moderate: claims.filter(c => c.strength === "moderate").length,
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claims_weak: claims.filter(c => c.strength === "weak").length,
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claims_empirical: claims.filter(c => c.strength === "empirical").length,
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claims_total: claims.length,
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diff_bytes: diff.length,
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};
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@@ -80,6 +86,15 @@ export async function auditPr(pr: PrSnapshot, opts: AuditOptions = {}): Promise<
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await persistVerdict(verdict);
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// Feedback loop — every block/warn finding becomes a row in
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// audit_lessons.jsonl, dedup-keyed by (check, normalized-summary).
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// The next audit's kb_query reads these and escalates recurring
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// findings so we don't lose the "this pattern has been flagged
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// before" signal across runs. Fire-and-forget; failure here must
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// not break the audit.
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appendAuditLessons(verdict).catch(e =>
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console.error(`[audit] audit_lessons append failed: ${(e as Error).message}`));
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if (!opts.dry_run) {
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await postToGitea(verdict);
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}
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@@ -87,6 +102,42 @@ export async function auditPr(pr: PrSnapshot, opts: AuditOptions = {}): Promise<
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return verdict;
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}
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// Normalizes a finding summary for dedup: strips path-specific tails
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// ("in path/to/file.ts" → "in <file>"), line numbers, and long
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// commit-hash snippets. The goal is: the SAME class of finding on
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// DIFFERENT files should share a signature, so we can measure
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// "this pattern keeps showing up."
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function normalizedSignature(f: Finding): string {
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const summary = String(f.summary)
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.replace(/\bin\s+\S+\.(ts|rs|js|py|md)\b/gi, "in <file>")
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.replace(/:\+?\d+\b/g, ":<line>")
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.replace(/[0-9a-f]{8,}/gi, "<hash>")
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.replace(/\s+/g, " ")
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.trim()
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.slice(0, 240);
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const src = `${f.check}::${f.severity}::${summary}`;
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return createHash("sha256").update(src).digest("hex").slice(0, 16);
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}
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async function appendAuditLessons(v: Verdict): Promise<void> {
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const actionable = v.findings.filter(f => f.severity === "block" || f.severity === "warn");
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if (actionable.length === 0) return;
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await mkdir(join(AUDIT_LESSONS_JSONL, ".."), { recursive: true });
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const rows: string[] = [];
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for (const f of actionable) {
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rows.push(JSON.stringify({
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signature: normalizedSignature(f),
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check: f.check,
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severity: f.severity,
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summary: f.summary,
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pr_number: v.pr_number,
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head_sha: v.head_sha,
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audited_at: v.audited_at,
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}));
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}
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await appendFile(AUDIT_LESSONS_JSONL, rows.join("\n") + "\n");
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}
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async function persistVerdict(v: Verdict): Promise<void> {
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await mkdir(VERDICTS_DIR, { recursive: true });
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const filename = `${v.pr_number}-${v.head_sha.slice(0, 12)}.json`;
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@@ -0,0 +1,68 @@
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// One-shot dry-run audit of a single PR. Useful for verifying check
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// behavior (kb_query scrum surfacing, inference prompts, etc.) without
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// posting to Gitea. Does NOT touch state.json and does NOT post
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// commit status or PR comments.
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//
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// Run: bun run auditor/audit_one.ts <pr-number>
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import { getPrSnapshot } from "./gitea.ts";
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import { auditPr } from "./audit.ts";
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async function main() {
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const prNumRaw = process.argv[2];
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if (!prNumRaw) {
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console.error("usage: bun run auditor/audit_one.ts <pr-number>");
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process.exit(2);
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}
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const prNum = Number(prNumRaw);
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if (!Number.isFinite(prNum)) {
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console.error(`invalid PR number: ${prNumRaw}`);
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process.exit(2);
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}
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console.log(`[audit_one] fetching PR #${prNum}...`);
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const pr = await getPrSnapshot(prNum);
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console.log(`[audit_one] PR #${pr.number}: "${pr.title}" (head=${pr.head_sha.slice(0, 12)})`);
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console.log(`[audit_one] files in diff: ${pr.files.length}`);
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for (const f of pr.files) console.log(` - ${f.path} (+${f.additions}/-${f.deletions})`);
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console.log("");
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const verdict = await auditPr(pr, {
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dry_run: true, // no Gitea posting
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skip_dynamic: true, // don't run fixture
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skip_inference: process.env.LH_AUDITOR_SKIP_INFERENCE === "1",
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});
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console.log("\n═══ VERDICT ═══");
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console.log(`overall: ${verdict.overall}`);
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console.log(`one-liner: ${verdict.one_liner}`);
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console.log(`findings: total=${verdict.metrics.findings_total} block=${verdict.metrics.findings_block} warn=${verdict.metrics.findings_warn} info=${verdict.metrics.findings_info}`);
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console.log("");
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// Print findings, highlighting kb_query scrum surfacing
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const byCheck: Record<string, typeof verdict.findings> = {};
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for (const f of verdict.findings) (byCheck[f.check] ||= []).push(f);
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for (const [check, findings] of Object.entries(byCheck)) {
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console.log(`── ${check} (${findings.length}) ──`);
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for (const f of findings) {
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const tag = f.severity === "block" ? "🛑" : f.severity === "warn" ? "⚠️ " : "ℹ️ ";
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console.log(` ${tag} [${f.severity}] ${f.summary}`);
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if (f.summary.includes("scrum-master")) {
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for (const e of f.evidence) {
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console.log(` → ${e.slice(0, 200)}`);
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}
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}
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}
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}
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const scrumFindings = verdict.findings.filter(f => f.summary.includes("scrum-master"));
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console.log("");
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console.log(`═══ SCRUM WIRE CHECK: ${scrumFindings.length} scrum-master findings surfaced by kb_query ═══`);
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if (scrumFindings.length === 0) {
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console.log(" (none — either no matching scrum_reviews.jsonl rows, or files didn't match PR diff)");
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}
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process.exit(0);
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}
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main().catch(e => { console.error("[audit_one] fatal:", e); process.exit(1); });
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+135
-6
@@ -13,6 +13,8 @@
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// with a 15KB diff + claim list).
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import type { Claim, Finding } from "../types.ts";
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import { Glob } from "bun";
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import { readFile } from "node:fs/promises";
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const GATEWAY = process.env.LH_GATEWAY_URL ?? "http://localhost:3100";
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const MODEL = process.env.LH_AUDITOR_REVIEW_MODEL ?? "gpt-oss:120b";
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@@ -22,6 +24,7 @@ const MODEL = process.env.LH_AUDITOR_REVIEW_MODEL ?? "gpt-oss:120b";
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// block finding when the file was simply outside the truncation window.
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const MAX_DIFF_CHARS = 40000;
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const CALL_TIMEOUT_MS = 120_000;
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const REPO_ROOT = "/home/profit/lakehouse";
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export async function runInferenceCheck(claims: Claim[], diff: string): Promise<Finding[]> {
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if (claims.length === 0) {
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@@ -33,6 +36,21 @@ export async function runInferenceCheck(claims: Claim[], diff: string): Promise<
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}];
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}
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// Empirical claims (runtime metrics / observed outcomes) can't be
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// verified from the diff. Drop them from the cloud prompt so the
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// reviewer doesn't chase ghosts. A future `runtime_evidence` check
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// can validate these against data/_kb/*/summary.json outputs.
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const verifiable = claims.filter(c => c.strength !== "empirical");
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const empiricalCount = claims.length - verifiable.length;
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if (verifiable.length === 0) {
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return [{
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check: "inference",
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severity: "info",
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summary: `all ${claims.length} claims are empirical (runtime metrics) — skipping cloud inference`,
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evidence: [`empirical claims can't be verified from a static diff; needs runtime-evidence check`],
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}];
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}
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const truncated = diff.length > MAX_DIFF_CHARS
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? diff.slice(0, MAX_DIFF_CHARS) + `\n...[${diff.length - MAX_DIFF_CHARS} more chars truncated]`
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: diff;
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@@ -70,7 +88,7 @@ export async function runInferenceCheck(claims: Claim[], diff: string): Promise<
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const userMsg = [
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`Ship-claims the author made (numbered 0..N-1):`,
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claims.map((c, i) => ` ${i}. [${c.strength}] "${c.text}" at ${c.location}`).join("\n"),
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verifiable.map((c, i) => ` ${i}. [${c.strength}] "${c.text}" at ${c.location}`).join("\n"),
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"",
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`Diff:`,
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"```",
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@@ -94,9 +112,22 @@ export async function runInferenceCheck(claims: Claim[], diff: string): Promise<
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{ role: "system", content: systemMsg },
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{ role: "user", content: userMsg },
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],
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// Deterministic classification — temp=0 is greedy-sample, so
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// identical input yields identical output on the same model
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// version. This kills the signature creep we observed in the
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// 9-run empirical test (sig_count 16→27 from cloud phrasing
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// variance at temp=0.2).
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//
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// IMPORTANT: keep think=true. gpt-oss:120b is a reasoning
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// model; setting think=false caused it to return empty content
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// on large prompts (observed during Level 1 validation: 13421
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// tokens used, empty content returned). The reasoning trace is
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// variable prose, but at temp=0 the FINAL classification is
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// still deterministic because greedy sampling converges to
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// the same conclusion from the same starting state.
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max_tokens: 3000,
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temperature: 0.2,
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think: true, // T3 overseer should reason — JSON shape is still required
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temperature: 0,
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think: true,
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}),
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signal: AbortSignal.timeout(CALL_TIMEOUT_MS),
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});
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@@ -152,7 +183,9 @@ export async function runInferenceCheck(claims: Claim[], diff: string): Promise<
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for (const v of parsed.claim_verdicts ?? []) {
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if (v?.backed === false) {
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const idx = typeof v.claim_idx === "number" ? v.claim_idx : -1;
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const claim = claims[idx];
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// Indices point at the verifiable[] list we sent the cloud,
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// not the full claims[] list. Translate back.
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const claim = verifiable[idx];
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if (!claim) continue;
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// Strong+unbacked = BLOCK. That's the whole point of the auditor.
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const sev: Finding["severity"] = claim.strength === "strong" ? "block"
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@@ -172,17 +205,113 @@ export async function runInferenceCheck(claims: Claim[], diff: string): Promise<
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}
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for (const g of parsed.unflagged_gaps ?? []) {
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const summary = String(g?.summary ?? "?");
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const location = String(g?.location ?? "?");
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// False-positive guard — when the cloud says "X not defined in this
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// diff" or "missing implementation of X", the cloud may just mean
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// "X is not in the added lines," not "X doesn't exist in the repo."
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// Extract candidate symbol names and grep the repo. If any symbol
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// is defined elsewhere, drop the finding — it's a known-symbol
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// reference, not a placeholder.
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if (/not\s+defined|missing\s+implementation|never\s+referenced\s+or\s+integrated/i.test(summary)) {
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const symbols = extractSymbols(summary);
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if (symbols.length > 0) {
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const resolved = await symbolsExistInRepo(symbols);
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if (resolved.length === symbols.length) {
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// Every named symbol exists somewhere in the repo — silent drop.
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continue;
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}
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if (resolved.length > 0) {
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// Partially resolved — demote to info with a note.
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findings.push({
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check: "inference",
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severity: "info",
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summary: `cloud gap partially resolved by repo grep: ${summary.slice(0, 120)}`,
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evidence: [
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`location: ${location.slice(0, 140)}`,
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`resolved via grep: ${resolved.join(",")}`,
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`unresolved: ${symbols.filter(s => !resolved.includes(s)).join(",")}`,
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],
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});
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continue;
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}
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}
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}
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findings.push({
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check: "inference",
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severity: "warn",
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summary: `cloud-flagged gap not in any claim: ${String(g?.summary ?? "?").slice(0, 120)}`,
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evidence: [`location: ${String(g?.location ?? "?").slice(0, 140)}`],
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summary: `cloud-flagged gap not in any claim: ${summary.slice(0, 120)}`,
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evidence: [`location: ${location.slice(0, 140)}`],
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});
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}
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return findings;
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}
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// Pull out plausible code-symbol names from a summary string.
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// Matches:
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// - identifier with backticks: `foo_bar`
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// - identifier followed by parens: foo_bar()
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// - CamelCase types
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// - snake_case_functions
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// Filters out common English words that could be matched accidentally.
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const STOPWORDS = new Set([
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"not","the","and","for","this","that","with","but","are","was","has",
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"have","been","any","missing","implementation","diff","defined","never",
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"referenced","integrated","flow","code","file","some","only","when",
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]);
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function extractSymbols(text: string): string[] {
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const out = new Set<string>();
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// `backticked` symbols
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for (const m of text.matchAll(/`([A-Za-z_][A-Za-z0-9_]{2,})`/g)) out.add(m[1]);
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// foo() or foo_bar() calls
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for (const m of text.matchAll(/\b([A-Za-z_][A-Za-z0-9_]{2,})\s*\(/g)) out.add(m[1]);
|
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// CamelCase types (3+ chars, must start with uppercase)
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for (const m of text.matchAll(/\b([A-Z][A-Za-z0-9]{2,})\b/g)) out.add(m[1]);
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return Array.from(out).filter(s => !STOPWORDS.has(s.toLowerCase()));
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}
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// Scan the repo for at least one definition of each symbol. Uses Bun's
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// Glob to walk TS/Rust/Python/JS sources; ignores node_modules, data/,
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// and target/. Skips files > 500KB — those are fixtures/snapshots that
|
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// won't contain a definition line and slurping them slows the audit.
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async function symbolsExistInRepo(symbols: string[]): Promise<string[]> {
|
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const patterns = ["**/*.ts", "**/*.tsx", "**/*.rs", "**/*.py", "**/*.js"];
|
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const skip = (p: string) => p.includes("/node_modules/") || p.startsWith("data/") || p.includes("/target/") || p.startsWith("dist/");
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const MAX_FILE_BYTES = 500_000;
|
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const { stat } = await import("node:fs/promises");
|
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const resolved = new Set<string>();
|
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const toFind = new Set(symbols);
|
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for (const pat of patterns) {
|
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if (toFind.size === 0) break;
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const glob = new Glob(pat);
|
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for await (const f of glob.scan({ cwd: REPO_ROOT, onlyFiles: true })) {
|
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if (skip(f)) continue;
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try { const s = await stat(`${REPO_ROOT}/${f}`); if (s.size > MAX_FILE_BYTES) continue; } catch { continue; }
|
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let content: string;
|
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try { content = await readFile(`${REPO_ROOT}/${f}`, "utf8"); } catch { continue; }
|
||||
for (const sym of Array.from(toFind)) {
|
||||
// Definition heuristics: `function sym`, `fn sym`, `const sym`,
|
||||
// `let sym`, `def sym`, `class sym`, `struct sym`, `enum sym`,
|
||||
// `trait sym`, `async function sym`, `pub (async )?fn sym`.
|
||||
const re = new RegExp(
|
||||
`\\b(function|async\\s+function|const|let|var|def|class|struct|enum|trait|impl|type|interface|fn|pub\\s+(async\\s+)?fn)\\s+${escapeRe(sym)}\\b`
|
||||
);
|
||||
if (re.test(content)) {
|
||||
resolved.add(sym);
|
||||
toFind.delete(sym);
|
||||
if (toFind.size === 0) break;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
return Array.from(resolved);
|
||||
}
|
||||
|
||||
function escapeRe(s: string): string {
|
||||
return s.replace(/[.*+?^${}()|[\]\\]/g, "\\$&");
|
||||
}
|
||||
|
||||
// Lift the first balanced JSON object out of the response. Tolerates
|
||||
// leading prose, code fences, and model reasoning preamble when the
|
||||
// cloud model ignored "strict JSON only."
|
||||
|
||||
+113
-1
@@ -8,6 +8,7 @@
|
||||
// What this check reads (all file-backed, append-only or periodic):
|
||||
// data/_kb/outcomes.jsonl — per-scenario outcomes (kb.ts)
|
||||
// data/_kb/error_corrections.jsonl — fail→succeed deltas on same sig
|
||||
// data/_kb/scrum_reviews.jsonl — scrum-master accepted reviews
|
||||
// data/_observer/ops.jsonl — observer ring → disk stream
|
||||
// data/_bot/cycles/*.json — bot cycle results
|
||||
//
|
||||
@@ -17,14 +18,17 @@
|
||||
import { readFile, readdir, stat } from "node:fs/promises";
|
||||
import { join } from "node:path";
|
||||
import type { Claim, Finding } from "../types.ts";
|
||||
import { aggregate, ratingSeverity, formatAgg } from "../kb_index.ts";
|
||||
|
||||
const KB_DIR = "/home/profit/lakehouse/data/_kb";
|
||||
const OBSERVER_OPS = "/home/profit/lakehouse/data/_observer/ops.jsonl";
|
||||
const BOT_CYCLES_DIR = "/home/profit/lakehouse/data/_bot/cycles";
|
||||
const SCRUM_REVIEWS_JSONL = "/home/profit/lakehouse/data/_kb/scrum_reviews.jsonl";
|
||||
const AUDIT_LESSONS_JSONL = "/home/profit/lakehouse/data/_kb/audit_lessons.jsonl";
|
||||
const TAIL_LINES = 500;
|
||||
const MAX_BOT_CYCLE_FILES = 30;
|
||||
|
||||
export async function runKbCheck(claims: Claim[]): Promise<Finding[]> {
|
||||
export async function runKbCheck(claims: Claim[], prFiles: string[] = []): Promise<Finding[]> {
|
||||
const findings: Finding[] = [];
|
||||
|
||||
// 1. Recent scenario outcomes: are strong-claim-style phrases showing
|
||||
@@ -48,6 +52,27 @@ export async function runKbCheck(claims: Claim[]): Promise<Finding[]> {
|
||||
const obsFindings = await checkObserverStream();
|
||||
findings.push(...obsFindings);
|
||||
|
||||
// 5. Scrum-master reviews — surface prior accepted reviews for any
|
||||
// file in this PR's diff. Cohesion plan Phase C wire: the
|
||||
// auditor gets to "borrow" the scrum-master's deeper per-file
|
||||
// analysis instead of re-doing that work.
|
||||
if (prFiles.length > 0) {
|
||||
const scrumFindings = await checkScrumReviews(prFiles);
|
||||
findings.push(...scrumFindings);
|
||||
}
|
||||
|
||||
// 6. Audit-lessons feedback loop — summarize the top recurring
|
||||
// patterns from prior audits' block/warn findings. If the same
|
||||
// pattern signature has fired 3+ times across prior audits,
|
||||
// emit it as a block-severity finding so reviewers know this
|
||||
// is a known-recurring class, not a one-off. Does NOT couple
|
||||
// to the current audit's static/inference findings (those run
|
||||
// in parallel and we can't see them here) — the amplification
|
||||
// is emergent: if the current audit's finding-summary matches
|
||||
// a top recurrence, the reviewer sees both.
|
||||
const auditLessonFindings = await checkAuditLessons();
|
||||
findings.push(...auditLessonFindings);
|
||||
|
||||
return findings;
|
||||
}
|
||||
|
||||
@@ -181,3 +206,90 @@ function observerBySource(ops: any[]): string {
|
||||
}
|
||||
return Object.entries(c).sort((a, b) => b[1] - a[1]).map(([k, v]) => `${k}=${v}`).join(", ") || "empty";
|
||||
}
|
||||
|
||||
// Audit-lessons — reads data/_kb/audit_lessons.jsonl (populated by
|
||||
// every audit's appendAuditLessons). Uses the shared kb_index
|
||||
// aggregator: groups by `signature`, distinct-scopes keyed by PR
|
||||
// number, severity from ratingSeverity(agg) which applies the
|
||||
// confidence × count rating (see kb_index.ts). This is the same
|
||||
// aggregation any other KB reader uses — shared discipline, not
|
||||
// per-check custom logic.
|
||||
async function checkAuditLessons(): Promise<Finding[]> {
|
||||
const bySig = await aggregate<any>(AUDIT_LESSONS_JSONL, {
|
||||
keyFn: (r) => r?.signature,
|
||||
scopeFn: (r) => (r?.pr_number !== undefined ? `pr-${r.pr_number}` : undefined),
|
||||
checkFn: (r) => r?.check,
|
||||
tailLimit: TAIL_LINES * 4,
|
||||
});
|
||||
if (bySig.size === 0) return [];
|
||||
|
||||
const findings: Finding[] = [];
|
||||
for (const [sig, agg] of bySig) {
|
||||
// Silent on first-ever occurrence — not yet signal.
|
||||
if (agg.count < 2) continue;
|
||||
const sev = ratingSeverity(agg);
|
||||
findings.push({
|
||||
check: "kb_query",
|
||||
severity: sev,
|
||||
summary: `recurring audit pattern (${agg.distinct_scopes} distinct PRs, ${agg.count} flaggings, conf=${agg.confidence.toFixed(2)}): ${agg.representative_summary.slice(0, 160)}`,
|
||||
evidence: [
|
||||
`signature=${sig}`,
|
||||
`checks: ${agg.checks.join(",")}`,
|
||||
`scopes: ${agg.scopes.slice(-6).join(",")}`,
|
||||
formatAgg(agg),
|
||||
],
|
||||
});
|
||||
}
|
||||
return findings;
|
||||
}
|
||||
|
||||
// Scrum-master reviews — the scrum pipeline writes one row per
|
||||
// accepted per-file review. We match reviews whose `file` matches
|
||||
// any path in the PR's diff, then surface the *preview* + which
|
||||
// model the escalation ladder had to reach. If the scrum-master
|
||||
// needed the 123B specialist or larger to resolve a file, that's
|
||||
// a meaningful signal about the code's complexity — and it's
|
||||
// surfaced to the PR without the auditor having to re-run the
|
||||
// escalation ladder itself.
|
||||
async function checkScrumReviews(prFiles: string[]): Promise<Finding[]> {
|
||||
const rows = await tailJsonl<any>(SCRUM_REVIEWS_JSONL, TAIL_LINES);
|
||||
if (rows.length === 0) return [];
|
||||
|
||||
// Match by exact file OR filename suffix — PR files arrive as
|
||||
// `auditor/audit.ts`-style relative paths; scrum stores the same.
|
||||
const norm = (p: string) => p.replace(/^\/+/, "").replace(/^home\/profit\/lakehouse\//, "");
|
||||
const prSet = new Set(prFiles.map(norm));
|
||||
|
||||
// Keep only the most recent review per file (last-wins).
|
||||
const latestByFile = new Map<string, any>();
|
||||
for (const r of rows) {
|
||||
const f = norm(String(r.file ?? ""));
|
||||
if (!f) continue;
|
||||
if (!prSet.has(f)) continue;
|
||||
latestByFile.set(f, r);
|
||||
}
|
||||
if (latestByFile.size === 0) return [];
|
||||
|
||||
const findings: Finding[] = [];
|
||||
for (const [file, r] of latestByFile) {
|
||||
const model = String(r.accepted_model ?? "?");
|
||||
const attempt = r.accepted_on_attempt ?? "?";
|
||||
const treeSplit = !!r.tree_split_fired;
|
||||
// Heuristic: if the scrum-master had to escalate past attempt 3,
|
||||
// or had to tree-split, that's context the PR reviewer should see.
|
||||
// Severity: info for low-escalation, warn if escalated far up
|
||||
// the ladder (cloud specialist required).
|
||||
const heavyEscalation = Number(attempt) >= 4;
|
||||
const sev: "warn" | "info" = heavyEscalation ? "warn" : "info";
|
||||
findings.push({
|
||||
check: "kb_query",
|
||||
severity: sev,
|
||||
summary: `scrum-master review for \`${file}\` — accepted on attempt ${attempt} by \`${model}\`${treeSplit ? " (tree-split)" : ""}`,
|
||||
evidence: [
|
||||
`reviewed_at: ${r.reviewed_at ?? "?"}`,
|
||||
`preview: ${String(r.suggestions_preview ?? "").slice(0, 300).replace(/\n/g, " ")}`,
|
||||
],
|
||||
});
|
||||
}
|
||||
return findings;
|
||||
}
|
||||
|
||||
@@ -61,7 +61,13 @@ export function runStaticCheck(diff: string): Finding[] {
|
||||
|
||||
if (!isAuditorCheckerFile) {
|
||||
for (const { re, why } of BLOCK_PATTERNS) {
|
||||
if (re.test(added)) {
|
||||
const m = added.match(re);
|
||||
if (m && typeof m.index === "number") {
|
||||
// Skip if the match sits inside a quoted string literal —
|
||||
// this is how rubric files (tests/real-world/*, prompt
|
||||
// templates) legitimately reference the patterns they
|
||||
// guard against, without actually executing them.
|
||||
if (isInsideQuotedString(added, m.index)) continue;
|
||||
findings.push({
|
||||
check: "static",
|
||||
severity: "block",
|
||||
@@ -154,6 +160,25 @@ function extractNewFields(addedLines: string[]): string[] {
|
||||
return Array.from(fields);
|
||||
}
|
||||
|
||||
// True if `pos` falls inside a double- or single-quoted string on this
|
||||
// line (backtick template literals too). Walks left→right toggling the
|
||||
// "in quote" state on each unescaped quote. Good enough for single-
|
||||
// line matches; multi-line strings aren't parsed (they're extremely
|
||||
// rare in the patterns we're blocking on, and would require a proper
|
||||
// tokenizer to handle correctly).
|
||||
function isInsideQuotedString(line: string, pos: number): boolean {
|
||||
let inDouble = false, inSingle = false, inBacktick = false;
|
||||
for (let i = 0; i < pos; i++) {
|
||||
const c = line[i];
|
||||
const esc = i > 0 && line[i - 1] === "\\";
|
||||
if (esc) continue;
|
||||
if (c === '"' && !inSingle && !inBacktick) inDouble = !inDouble;
|
||||
else if (c === "'" && !inDouble && !inBacktick) inSingle = !inSingle;
|
||||
else if (c === "`" && !inDouble && !inSingle) inBacktick = !inBacktick;
|
||||
}
|
||||
return inDouble || inSingle || inBacktick;
|
||||
}
|
||||
|
||||
function escape(s: string): string {
|
||||
return s.replace(/[.*+?^${}()|[\]\\]/g, "\\$&");
|
||||
}
|
||||
|
||||
+34
-2
@@ -49,6 +49,25 @@ const WEAK_PATTERNS: RegExp[] = [
|
||||
/\bprobably\b/i,
|
||||
];
|
||||
|
||||
// Empirical claims: runtime measurements / observed outcomes that can't
|
||||
// be verified from a diff (only from the actual run that produced
|
||||
// them). Example: "6/6 iterations complete, 58 cloud calls, 306s
|
||||
// end-to-end" — true, but only the test's own summary.json can
|
||||
// confirm it. Classifying as empirical lets the inference check skip
|
||||
// diff-verification and saves the ladder for falsifiable claims.
|
||||
const EMPIRICAL_PATTERNS: RegExp[] = [
|
||||
// Iteration / attempt counts: "6/6 iterations", "attempt 5", "accepted on attempt 3"
|
||||
/\b\d+\s*\/\s*\d+\s+(iterations?|attempts?|cycles?|runs?|shards?)\b/i,
|
||||
/\b(accepted|resolved|converged)\s+on\s+attempt\s+\d+\b/i,
|
||||
// Runtime metrics: "58 cloud calls", "306s end-to-end", "245s total", "5931 chars"
|
||||
/\b\d+\s+(cloud\s+)?calls?\b/i,
|
||||
/\b\d+\s*(ms|s|seconds?|minutes?|m)\s+(end[- ]to[- ]end|total|elapsed|duration)\b/i,
|
||||
/\b\d+\s+chars?\b.*\b(accepted|generated|produced)\b/i,
|
||||
// "escalated through N tiers", "N distinct models"
|
||||
/\bescalated\s+through\s+\d+\b/i,
|
||||
/\b\d+\s+distinct\s+(model|tier)s?\b/i,
|
||||
];
|
||||
|
||||
export interface ParsedClaims {
|
||||
claims: Claim[];
|
||||
commits_scanned: number;
|
||||
@@ -77,8 +96,21 @@ function scanText(text: string, location_prefix: string, commit_sha: string, out
|
||||
const line = lines[i];
|
||||
if (line.length < 3) continue;
|
||||
|
||||
// Strong patterns first — if a line matches strong, it's strong,
|
||||
// don't double-count as moderate.
|
||||
// Empirical match wins over everything else — if a line ALSO
|
||||
// contains a moderate word like "complete", we still want to
|
||||
// classify it as empirical so the inference check doesn't ask
|
||||
// the cloud to prove "58 cloud calls" from the diff. Order:
|
||||
// empirical → strong → moderate → weak.
|
||||
const empirical = firstMatch(line, EMPIRICAL_PATTERNS);
|
||||
if (empirical) {
|
||||
out.push({
|
||||
text: line.trim().slice(0, 200),
|
||||
commit_sha,
|
||||
location: `${location_prefix}:${i + 1}`,
|
||||
strength: "empirical",
|
||||
});
|
||||
continue;
|
||||
}
|
||||
const strong = firstMatch(line, STRONG_PATTERNS);
|
||||
if (strong) {
|
||||
out.push({
|
||||
|
||||
@@ -0,0 +1,161 @@
|
||||
// kb_index — generic on-the-fly aggregation over append-only JSONL
|
||||
// scratchpads (audit_lessons, scrum_reviews, outcomes, observer ops).
|
||||
//
|
||||
// The mem0 insight: raw rows are CHEAP and tell the full story, but
|
||||
// downstream prompts need a DEFINITION, not a log. A definition is
|
||||
// the aggregate: "this signature has fired N times across M distinct
|
||||
// scopes, first_seen=X, last_seen=Y, confidence=M/N."
|
||||
//
|
||||
// This library is the single shared aggregator. Every KB writer keeps
|
||||
// appending raw rows; every KB reader uses aggregate() instead of
|
||||
// tailing the raw stream. No second file to sync, no ADD/UPDATE/NOOP
|
||||
// routing — the stats roll up from the raw rows every time.
|
||||
//
|
||||
// Why this works past hundreds of runs:
|
||||
// - aggregate() is bounded by distinct_signatures, not total_rows.
|
||||
// - confidence = distinct_scopes / count — low for same-scope noise,
|
||||
// high for cross-scope patterns. Downstream severity ramps on
|
||||
// confidence × count, not raw count, so one unfixed PR can't
|
||||
// inflate its own recurrence score (the classic mem0 failure).
|
||||
// - rotation (later) moves old raw to archive files; aggregate()
|
||||
// can still read both to compute lifetime counts when needed.
|
||||
|
||||
import { readFile } from "node:fs/promises";
|
||||
|
||||
export interface AggregateRow {
|
||||
signature: string;
|
||||
count: number;
|
||||
distinct_scopes: number;
|
||||
first_seen: string;
|
||||
last_seen: string;
|
||||
confidence: number; // distinct_scopes / count — capped at 1.0
|
||||
representative_summary: string; // most-recent summary for this signature
|
||||
scopes: string[]; // up to 20 most-recent scopes for debugging
|
||||
checks: string[]; // distinct `check` values (audit_lessons-specific)
|
||||
}
|
||||
|
||||
export interface AggregateOptions<T> {
|
||||
/** How to extract the dedup key from a row. */
|
||||
keyFn: (row: T) => string | undefined;
|
||||
/** How to extract the "scope" — distinct scopes count gives confidence. */
|
||||
scopeFn: (row: T) => string | undefined;
|
||||
/** How to extract the timestamp (defaults to row.audited_at / row.reviewed_at / row.timestamp). */
|
||||
timeFn?: (row: T) => string | undefined;
|
||||
/** How to extract a representative summary (defaults to row.summary). */
|
||||
summaryFn?: (row: T) => string | undefined;
|
||||
/** Max rows to read from the JSONL tail; 0 = read all. */
|
||||
tailLimit?: number;
|
||||
/** Include per-row check field (for multi-check aggregates). */
|
||||
checkFn?: (row: T) => string | undefined;
|
||||
}
|
||||
|
||||
/**
|
||||
* Read a JSONL file and produce the aggregate map keyed by signature.
|
||||
* Safe on missing or malformed files — returns empty map.
|
||||
*/
|
||||
export async function aggregate<T = any>(
|
||||
jsonlPath: string,
|
||||
opts: AggregateOptions<T>,
|
||||
): Promise<Map<string, AggregateRow>> {
|
||||
const out = new Map<string, AggregateRow>();
|
||||
let raw: string;
|
||||
try { raw = await readFile(jsonlPath, "utf8"); } catch { return out; }
|
||||
const lines = raw.split("\n").filter(l => l.length > 0);
|
||||
const sliceFrom = opts.tailLimit && opts.tailLimit > 0 ? Math.max(0, lines.length - opts.tailLimit) : 0;
|
||||
|
||||
const timeFn = opts.timeFn ?? ((r: any) => r?.audited_at ?? r?.reviewed_at ?? r?.timestamp ?? r?.ran_at);
|
||||
const summaryFn = opts.summaryFn ?? ((r: any) => r?.summary ?? r?.representative_summary);
|
||||
|
||||
// Per-signature scope tracking — need counts by scope to compute
|
||||
// distinct_scopes without double-counting a scope that appears 50
|
||||
// times. Using a Set<scope> per signature.
|
||||
const scopeSets = new Map<string, Set<string>>();
|
||||
const checkSets = new Map<string, Set<string>>();
|
||||
|
||||
for (let i = sliceFrom; i < lines.length; i++) {
|
||||
let row: T;
|
||||
try { row = JSON.parse(lines[i]) as T; } catch { continue; }
|
||||
const sig = opts.keyFn(row);
|
||||
if (!sig) continue;
|
||||
|
||||
let agg = out.get(sig);
|
||||
if (!agg) {
|
||||
agg = {
|
||||
signature: sig,
|
||||
count: 0,
|
||||
distinct_scopes: 0,
|
||||
first_seen: "",
|
||||
last_seen: "",
|
||||
confidence: 0,
|
||||
representative_summary: "",
|
||||
scopes: [],
|
||||
checks: [],
|
||||
};
|
||||
out.set(sig, agg);
|
||||
scopeSets.set(sig, new Set<string>());
|
||||
checkSets.set(sig, new Set<string>());
|
||||
}
|
||||
|
||||
agg.count += 1;
|
||||
|
||||
const scope = opts.scopeFn(row);
|
||||
if (scope !== undefined && scope !== null && scope !== "") {
|
||||
scopeSets.get(sig)!.add(String(scope));
|
||||
// Keep scopes array ordered by recency (newest wins — shift
|
||||
// oldest when at cap).
|
||||
const arr = agg.scopes;
|
||||
const s = String(scope);
|
||||
const existing = arr.indexOf(s);
|
||||
if (existing >= 0) arr.splice(existing, 1);
|
||||
arr.push(s);
|
||||
if (arr.length > 20) arr.shift();
|
||||
}
|
||||
|
||||
if (opts.checkFn) {
|
||||
const c = opts.checkFn(row);
|
||||
if (c) checkSets.get(sig)!.add(String(c));
|
||||
}
|
||||
|
||||
const t = timeFn(row);
|
||||
if (t) {
|
||||
if (!agg.first_seen || t < agg.first_seen) agg.first_seen = t;
|
||||
if (!agg.last_seen || t > agg.last_seen) agg.last_seen = t;
|
||||
}
|
||||
|
||||
const s = summaryFn(row);
|
||||
if (s) agg.representative_summary = String(s);
|
||||
}
|
||||
|
||||
// Finalize derived fields.
|
||||
for (const [sig, agg] of out) {
|
||||
const scopes = scopeSets.get(sig) ?? new Set<string>();
|
||||
agg.distinct_scopes = scopes.size;
|
||||
agg.confidence = agg.count > 0 ? Math.min(1, agg.distinct_scopes / agg.count) : 0;
|
||||
const checks = checkSets.get(sig);
|
||||
if (checks) agg.checks = Array.from(checks).sort();
|
||||
}
|
||||
return out;
|
||||
}
|
||||
|
||||
/**
|
||||
* Severity policy derived from aggregate stats. The rating lives here
|
||||
* (not in each check) so all KB readers ramp severity consistently.
|
||||
*
|
||||
* - confidence × count product is the real signal.
|
||||
* - Low confidence (< 0.3) = same-scope noise → info regardless of count.
|
||||
* - Mid confidence (0.3-0.6) = mixed signal → warn at count ≥ 3.
|
||||
* - High confidence (> 0.6) with count ≥ 5 = block-worthy cross-cutting pattern.
|
||||
*
|
||||
* Callers can override by reading agg directly; this is the default
|
||||
* policy that matches the "don't escalate one unfixed PR" discipline.
|
||||
*/
|
||||
export function ratingSeverity(agg: AggregateRow): "info" | "warn" | "block" {
|
||||
if (agg.confidence >= 0.6 && agg.count >= 5) return "block";
|
||||
if (agg.confidence >= 0.3 && agg.count >= 3) return "warn";
|
||||
return "info";
|
||||
}
|
||||
|
||||
/** Human-friendly one-line summary of an aggregate row for finding evidence. */
|
||||
export function formatAgg(agg: AggregateRow): string {
|
||||
return `count=${agg.count} distinct_scopes=${agg.distinct_scopes} confidence=${agg.confidence.toFixed(2)} seen=[${agg.first_seen.slice(0, 10)}..${agg.last_seen.slice(0, 10)}]`;
|
||||
}
|
||||
+8
-1
@@ -18,7 +18,14 @@ export interface Claim {
|
||||
// Heuristic rating of how strong the claim is. "green+tested"
|
||||
// is strong; "should work" is weak. Drives sensitivity — stronger
|
||||
// claims get harder-blocked on weak evidence.
|
||||
strength: "weak" | "moderate" | "strong";
|
||||
//
|
||||
// "empirical" is a separate class: runtime measurements like
|
||||
// "N cloud calls" / "306s end-to-end" / "accepted on attempt N".
|
||||
// These cannot be verified from a static diff — only from the test
|
||||
// output that produced them. Inference skips diff-verification for
|
||||
// empirical claims; they become info-level context unless a future
|
||||
// runtime_evidence check contradicts them.
|
||||
strength: "weak" | "moderate" | "strong" | "empirical";
|
||||
}
|
||||
|
||||
export interface Finding {
|
||||
|
||||
Reference in New Issue
Block a user