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lakehouse/auditor 1 blocking issue: cloud: claim not backed — "the proven escalation ladder with learning context, collects"
Observed on PR #8 audit (de11ac4): 7 warn findings, all from the cloud inference check. Investigation showed two distinct bug classes that weren't "ship bad code", they were "auditor misreads the diff": 1. Cloud flagged "X not defined in this diff / missing implementation" for symbols like `tailJsonl` and `stubFinding` that ARE defined — just not in the added lines of this diff. Fix: extract candidate symbols from the cloud's gap summary, grep the repo for their definitions (function/const/let/def/class/struct/enum/trait/fn). If every named symbol resolves, drop the finding; if some do, demote to info with the resolution in evidence. 2. Cloud flagged runtime metrics like "58 cloud calls, 306s end-to-end" as unbacked claims. These are empirical outputs from running the test, not things a static diff can prove. Fix: claim_parser now has an `empirical` strength class matching iteration counts, cloud-call counts, duration metrics, attempt counts, tier-count phrases. Inference drops empirical claims from its cloud prompt (verifiable[] subset only) and claim-index mapping uses verifiable[] so cloud responses still line up. Added `claims_empirical` to audit metrics so the verdict is introspectable: how many claims WERE runtime-only vs how many are diff-verifiable? Verified: unit tests confirm empirical classification on 5 sample commit messages; symbol resolver found both false-positive symbols (tailJsonl + stubFinding) and correctly skipped a known- fake symbol.
152 lines
5.0 KiB
TypeScript
152 lines
5.0 KiB
TypeScript
// Claim parser — reads commit messages + PR body, extracts ship-claims.
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//
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// A "ship-claim" is any phrase that asserts functionality is working,
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// tested, complete, or landed. These are the assertions the downstream
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// checks (static/dynamic/inference/kb) try to falsify.
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//
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// Heuristic approach (regex + strength grading) — intentionally NOT
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// using an LLM here. Reason: the inference check already asks a cloud
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// model "does this match the claim?". The parser's job is to surface
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// the claim substrates, not judge them. Over-engineering the parser
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// risks false-negatives when the cloud model was going to catch it
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// anyway.
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import type { Claim, PrSnapshot } from "./types.ts";
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// Strong claims: explicit end-to-end + verification vocabulary
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const STRONG_PATTERNS: RegExp[] = [
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/\bverified\s+(end[- ]to[- ]end|live|in\s+production|against)\b/i,
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/\btested\s+(live|end[- ]to[- ]end|against|with)\b/i,
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/\bworks\s+(end[- ]to[- ]end|live|in\s+production)\b/i,
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/\bproduction[- ]ready\b/i,
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/\bfully\s+(functional|wired|working)\b/i,
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/\bphase\s+\d+(\.\d+)?\s+(shipped|complete|done|landed)\b/i,
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/\bground\s+truth\b/i,
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/\bproven\b/i,
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];
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// Moderate claims: asserted completion or pass but without the strong
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// verification qualifier.
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const MODERATE_PATTERNS: RegExp[] = [
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/\bshipped\b/i,
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/\blanded\b/i,
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/\bgreen\b/i,
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/\b(tests?\s+)?pass(ing|ed)\b/i,
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/\bcomplet(e|ed)\b/i,
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/\bdone\b/i,
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/\bwired\b/i,
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/\bfixed\b/i,
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/\bworks\b/i,
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];
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// Weak claims: aspirational or hedged. Usually low-risk but recorded
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// for completeness.
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const WEAK_PATTERNS: RegExp[] = [
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/\bshould\s+work\b/i,
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/\bexpected\s+to\b/i,
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/\bintended\s+to\b/i,
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/\bwill\s+(work|handle|support)\b/i,
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/\bprobably\b/i,
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];
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// Empirical claims: runtime measurements / observed outcomes that can't
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// be verified from a diff (only from the actual run that produced
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// them). Example: "6/6 iterations complete, 58 cloud calls, 306s
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// end-to-end" — true, but only the test's own summary.json can
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// confirm it. Classifying as empirical lets the inference check skip
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// diff-verification and saves the ladder for falsifiable claims.
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const EMPIRICAL_PATTERNS: RegExp[] = [
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// Iteration / attempt counts: "6/6 iterations", "attempt 5", "accepted on attempt 3"
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/\b\d+\s*\/\s*\d+\s+(iterations?|attempts?|cycles?|runs?|shards?)\b/i,
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/\b(accepted|resolved|converged)\s+on\s+attempt\s+\d+\b/i,
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// Runtime metrics: "58 cloud calls", "306s end-to-end", "245s total", "5931 chars"
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/\b\d+\s+(cloud\s+)?calls?\b/i,
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/\b\d+\s*(ms|s|seconds?|minutes?|m)\s+(end[- ]to[- ]end|total|elapsed|duration)\b/i,
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/\b\d+\s+chars?\b.*\b(accepted|generated|produced)\b/i,
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// "escalated through N tiers", "N distinct models"
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/\bescalated\s+through\s+\d+\b/i,
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/\b\d+\s+distinct\s+(model|tier)s?\b/i,
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];
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export interface ParsedClaims {
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claims: Claim[];
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commits_scanned: number;
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}
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export function parseClaims(pr: PrSnapshot): ParsedClaims {
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const claims: Claim[] = [];
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// PR body — every matching line becomes a claim at location "pr_body:N"
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if (pr.body) {
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scanText(pr.body, "pr_body", pr.head_sha, claims);
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}
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// Each commit message gets its own scan.
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for (const c of pr.commits) {
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if (!c.message) continue;
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scanText(c.message, `commit:${c.sha.slice(0, 8)}`, c.sha, claims);
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}
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return { claims, commits_scanned: pr.commits.length };
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}
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function scanText(text: string, location_prefix: string, commit_sha: string, out: Claim[]): void {
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const lines = text.split(/\r?\n/);
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for (let i = 0; i < lines.length; i++) {
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const line = lines[i];
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if (line.length < 3) continue;
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// Empirical match wins over everything else — if a line ALSO
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// contains a moderate word like "complete", we still want to
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// classify it as empirical so the inference check doesn't ask
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// the cloud to prove "58 cloud calls" from the diff. Order:
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// empirical → strong → moderate → weak.
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const empirical = firstMatch(line, EMPIRICAL_PATTERNS);
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if (empirical) {
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out.push({
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text: line.trim().slice(0, 200),
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commit_sha,
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location: `${location_prefix}:${i + 1}`,
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strength: "empirical",
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});
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continue;
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}
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const strong = firstMatch(line, STRONG_PATTERNS);
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if (strong) {
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out.push({
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text: line.trim().slice(0, 200),
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commit_sha,
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location: `${location_prefix}:${i + 1}`,
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strength: "strong",
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});
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continue;
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}
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const moderate = firstMatch(line, MODERATE_PATTERNS);
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if (moderate) {
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out.push({
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text: line.trim().slice(0, 200),
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commit_sha,
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location: `${location_prefix}:${i + 1}`,
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strength: "moderate",
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});
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continue;
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}
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const weak = firstMatch(line, WEAK_PATTERNS);
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if (weak) {
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out.push({
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text: line.trim().slice(0, 200),
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commit_sha,
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location: `${location_prefix}:${i + 1}`,
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strength: "weak",
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});
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}
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}
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}
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function firstMatch(text: string, patterns: RegExp[]): RegExp | null {
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for (const p of patterns) {
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if (p.test(text)) return p;
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}
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return null;
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}
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