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.

auditor/claim_parser.ts

@@ -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({