Merge PR #2629: fix(autopilot,eval): make the nightly quality probe enable path work end-to-end

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

# Conflicts:
#	test/engine-find-trajectory.test.ts

src/commands/autopilot.ts

@@ -1022,17 +1022,36 @@ export async function runAutopilot(engine: BrainEngine, args: string[]) {
     // loop. Probe runs even when cycleOk=false (probe may surface signal
     // explaining why the cycle is failing).
     try {
-      const probeEnabled = cfg?.autopilot?.nightly_quality_probe?.enabled === true;
+      const { resolveProbeEnabled, resolveProbeMaxUsd, runNightlyQualityProbe } = await import('../core/cycle/nightly-quality-probe.ts');
+      // Dual-plane read: `gbrain config set` (what the doctor enable hint
+      // prints) writes the DB plane; ~/.gbrain/config.json is the fallback.
+      let dbEnabled: string | null = null;
+      let dbMaxUsd: string | null = null;
+      try {
+        dbEnabled = await engine.getConfig('autopilot.nightly_quality_probe.enabled');
+        dbMaxUsd = await engine.getConfig('autopilot.nightly_quality_probe.max_usd');
+      } catch { /* DB unavailable → file plane only */ }
+      const probeEnabled = resolveProbeEnabled(dbEnabled, cfg?.autopilot?.nightly_quality_probe?.enabled);
       if (probeEnabled) {
-        const { runNightlyQualityProbe } = await import('../core/cycle/nightly-quality-probe.ts');
         const { runLongMemEvalForProbe, runCrossModalBatchForProbe } = await import('../core/cycle/nightly-probe-adapters.ts');
         const { isAvailable } = await import('../core/ai/gateway.ts');
-        const maxUsd = Number(cfg?.autopilot?.nightly_quality_probe?.max_usd ?? 5);
+        const { existsSync } = await import('node:fs');
+        const { fileURLToPath } = await import('node:url');
+        const { join } = await import('node:path');
+        const maxUsd = resolveProbeMaxUsd(dbMaxUsd, cfg?.autopilot?.nightly_quality_probe?.max_usd);
+        // The committed fixture (test/fixtures/longmemeval-nightly.jsonl)
+        // lives in the gbrain PACKAGE, not the brain repo — repoPath is
+        // sync.repo_path (the user's brain), where the fixture never
+        // exists, so the probe error'd on every real install. Resolve the
+        // package root from the module location; keep repoPath as the
+        // fallback for setups that vendor the fixture into the brain repo.
+        const pkgRoot = fileURLToPath(new URL('../..', import.meta.url));
+        const fixtureAtPkgRoot = existsSync(join(pkgRoot, 'test', 'fixtures', 'longmemeval-nightly.jsonl'));
         await runNightlyQualityProbe({
           isEnabled: () => true, // already gated above; phase re-checks for defense-in-depth
           hasEmbeddingProvider: () => isAvailable('embedding'),
           resolveMaxUsd: () => maxUsd,
-          resolveRepoRoot: () => repoPath ?? gbrainHomePath('.'),
+          resolveRepoRoot: () => (fixtureAtPkgRoot ? pkgRoot : repoPath ?? gbrainHomePath('.')),
           runLongMemEval: runLongMemEvalForProbe,
           runCrossModalBatch: runCrossModalBatchForProbe,
           now: () => new Date(),

src/commands/doctor.ts

@@ -4779,10 +4779,17 @@ export async function buildChecks(
   try {
     const { readRecentQualityProbeEvents } = await import('../core/audit-quality-probe.ts');
     const { loadConfig } = await import('../core/config.ts');
+    const { resolveProbeEnabled } = await import('../core/cycle/nightly-quality-probe.ts');
     let probeEnabled = false;
     try {
+      // Dual-plane read, matching the autopilot gate: the DB row (what the
+      // enable hint's `gbrain config set` writes) wins; file plane fallback.
+      let dbVal: string | null = null;
+      try {
+        dbVal = engine ? await engine.getConfig('autopilot.nightly_quality_probe.enabled') : null;
+      } catch { /* DB unavailable → file plane only */ }
       const cfg = loadConfig();
-      probeEnabled = Boolean((cfg as any)?.autopilot?.nightly_quality_probe?.enabled);
+      probeEnabled = resolveProbeEnabled(dbVal, (cfg as any)?.autopilot?.nightly_quality_probe?.enabled);
     } catch { /* config unavailable → treat as disabled */ }
     const events = readRecentQualityProbeEvents(7);
     const check = computeNightlyQualityProbeHealthCheck(probeEnabled, events);

src/commands/eval-cross-modal.ts

@@ -466,6 +466,14 @@ interface BatchRow {
   question_id: string;
   question: string;
   hypothesis: string;
+  /**
+   * Gold answer from the benchmark dataset, when the upstream eval emits
+   * it (eval-longmemeval does). Folded into the judge task so CORRECTNESS
+   * is verifiable — without it a judge panel that sees only
+   * {question, hypothesis} cannot validate a terse factual answer against
+   * a haystack it never saw.
+   */
+  answer?: string;
 }
 
 /**
@@ -579,6 +587,7 @@ function readBatchRows(path: string): BatchReadResult {
       question_id: typeof obj.question_id === 'string' ? obj.question_id : `line-${lineNo}`,
       question: obj.question,
       hypothesis: obj.hypothesis,
+      ...(typeof obj.answer === 'string' && obj.answer.length > 0 ? { answer: obj.answer } : {}),
     });
   }
   if (summarySkipped > 0) {
@@ -695,7 +704,11 @@ async function runBatchMode(parsed: ParsedArgs, opts: RunCrossModalOpts): Promis
       fn: async (row, idx) => {
         process.stderr.write(`[eval cross-modal batch] ${idx + 1}/${rows.length} ${row.question_id} starting...\n`);
         return await runEvalFn({
-          task: row.question,
+          // With a gold answer the judges can actually verify correctness;
+          // without one they see only {question, hypothesis} and cannot.
+          task: row.answer
+            ? `${row.question}\n\nExpected answer (gold label from the benchmark dataset): ${row.answer}`
+            : row.question,
           output: row.hypothesis,
           slug: row.question_id,
           dimensions,

src/commands/eval-longmemeval.ts

@@ -33,6 +33,7 @@ import {
   type AliasMap,
 } from '../eval/longmemeval/extract.ts';
 import { extractCandidateEntities } from '../core/think/entity-extract.ts';
+import { splitProviderModelId } from '../core/model-id.ts';
 import { resolveEntitySlugWithSource, type ResolutionSource } from '../core/entities/resolve.ts';
 import { formatTrajectoryBlock } from '../core/trajectory-format.ts';
 
@@ -469,14 +470,22 @@ export async function runEvalLongMemEval(args: string[], runOpts: RunOpts = {}):
   });
 
   // Wrap Anthropic SDK so its `.messages.create` shape matches ThinkLLMClient.
-  // Same pattern as src/core/think/index.ts:247-249.
+  // Same pattern as src/core/think/index.ts:247-249 — EXCEPT think's default
+  // client routes through the gateway, which parses `provider:model` recipe
+  // ids. This eval's client is a raw SDK by design (hermetic, no gateway
+  // dependency), and resolveModel returns RECIPE ids (`anthropic:claude-…`);
+  // passing one through unstripped 404s every answer/extractor call, which
+  // surfaces downstream as all-upstream_error batches in the nightly probe.
+  const toSdkModel = (m: string): string => splitProviderModelId(m).model || m;
   const realClient = new Anthropic();
   const client: ThinkLLMClient = runOpts.client ?? {
-    create: (params, callOpts) => realClient.messages.create(params, callOpts),
+    create: (params, callOpts) =>
+      realClient.messages.create({ ...params, model: toSdkModel(params.model) }, callOpts),
   };
   // v0.40.2.0 — separate extractor client (defaults to same SDK).
   const extractorClient: ThinkLLMClient = runOpts.extractorClient ?? {
-    create: (params, callOpts) => realClient.messages.create(params, callOpts),
+    create: (params, callOpts) =>
+      realClient.messages.create({ ...params, model: toSdkModel(params.model) }, callOpts),
   };
   const trajectoryEnabled = !opts.noTrajectory;
   const extractorModel = trajectoryEnabled
@@ -751,6 +760,11 @@ async function runOneQuestion(
     // v0.40.1.0 (Track D / T2) — copy question_type into the row so the
     // by_type_summary can be rebuilt from the file on resume runs.
     question_type: q.question_type,
+    // Gold answer for downstream consumers that verify correctness (the
+    // cross-modal --batch judge folds it into the task; evaluate_qa.py
+    // ignores unknown fields). Without it a judge can't validate a terse
+    // factual hypothesis against a haystack it never saw.
+    ...(q.answer !== undefined ? { answer: q.answer } : {}),
     hypothesis,
     retrieved_session_ids: retrievedSessionIds,
     ...(recallHit !== undefined ? { recall_hit: recallHit } : {}),

src/core/cross-modal-eval/runner.ts

@@ -44,7 +44,12 @@ export const DEFAULT_DIMENSIONS: string[] = [
  * `--slot-a-model`, `--slot-b-model`, `--slot-c-model` on the CLI.
  */
 export const DEFAULT_SLOTS: SlotConfig[] = [
-  { id: 'A', model: 'openai:gpt-4o' },
+  // Every default MUST be listed in its recipe's chat touchpoint (pinned by
+  // test/cross-modal-default-slots.test.ts) — `openai:gpt-4o` sat here after
+  // the OpenAI recipe dropped it, so slot A errored "not listed for OpenAI
+  // chat" on every install and the 3-slot panel could never reach its
+  // 2-model quorum without a Google key (verdict: permanently inconclusive).
+  { id: 'A', model: 'openai:gpt-5.2' },
   { id: 'B', model: 'anthropic:claude-opus-4-7' },
   { id: 'C', model: 'google:gemini-1.5-pro' },
 ];

src/core/cycle/nightly-probe-adapters.ts

@@ -70,6 +70,28 @@ export async function runLongMemEvalForProbe(args: LongMemEvalProbeArgs): Promis
  * the batch input) or unparseable (cross-modal wrote garbage). Both
  * cases are paste-ready in the error message.
  */
+/**
+ * QA-shaped judge dimensions for the nightly probe. The batch judge's
+ * DEFAULT_DIMENSIONS rubric (DEPTH / SOURCING / SPECIFICITY / …) is built
+ * for rich agent responses; LongMemEval hypotheses are deliberately terse
+ * factual answers ("in widget-co") that can never score ≥7 on DEPTH or
+ * SOURCING — so with the default rubric the probe FAILs every night even
+ * when retrieval + answering are perfectly healthy. The probe owns its
+ * invocation of the eval tool and passes dimensions matching the
+ * fixture's QA shape instead.
+ *
+ * NOTE: the `--dimensions` CLI flag splits on commas, so these dimension
+ * descriptions must stay comma-free.
+ */
+export const PROBE_QA_DIMENSIONS: string[] = [
+  // No faithfulness/grounding dimension on purpose: the judge never sees
+  // the haystack, so any accurate detail beyond the terse gold label reads
+  // as "invented" and correct answers fail (verified empirically — a
+  // correct "before + dates" answer scored 4/10 on such a dimension).
+  'CORRECTNESS — Does the hypothesis state the same fact as the expected answer? A terse direct answer is ideal.',
+  'DIRECTNESS — Does it answer THIS question without hedging or padding or answering something else?',
+];
+
 export async function runCrossModalBatchForProbe(
   args: CrossModalProbeArgs,
 ): Promise<{ exitCode: number; summary: CrossModalBatchSummary }> {
@@ -81,6 +103,8 @@ export async function runCrossModalBatchForProbe(
     args.summaryPath,
     '--max-usd',
     String(args.maxUsd),
+    '--dimensions',
+    PROBE_QA_DIMENSIONS.join(','),
     '--yes',
     '--json',
   ]);

src/core/cycle/nightly-quality-probe.ts

@@ -62,6 +62,42 @@ export interface NightlyProbeDeps {
   now: () => Date;
 }
 
+/**
+ * Dual-plane flag resolution (same precedent as `mcp.publish_skills` in
+ * serve-http.ts): the DB config row — what `gbrain config set` writes —
+ * wins when present; the file plane (~/.gbrain/config.json) is the
+ * fallback. Doctor's paste-ready enable hint says `gbrain config set
+ * autopilot.nightly_quality_probe.enabled true`, so the gate MUST read
+ * the DB plane — a file-only read turns that hint into a silent no-op.
+ */
+export function resolveProbeEnabled(
+  dbVal: string | null | undefined,
+  fileVal: unknown,
+): boolean {
+  if (dbVal != null) return dbVal === 'true';
+  return fileVal === true;
+}
+
+/**
+ * Same dual-plane rule for the per-run cost cap. Malformed or negative
+ * values on either plane fall through to the next plane / the default.
+ */
+export function resolveProbeMaxUsd(
+  dbVal: string | null | undefined,
+  fileVal: unknown,
+  fallback: number = DEFAULT_MAX_USD,
+): number {
+  if (dbVal != null) {
+    const n = Number(dbVal);
+    if (Number.isFinite(n) && n >= 0) return n;
+  }
+  if (fileVal != null) {
+    const n = Number(fileVal);
+    if (Number.isFinite(n) && n >= 0) return n;
+  }
+  return fallback;
+}
+
 /**
  * Pure function: decide whether the probe should run given the audit
  * history. Returns reason when skipping.
@@ -101,21 +137,17 @@ export async function runNightlyQualityProbe(deps: NightlyProbeDeps): Promise<Ni
     return { outcome: 'disabled', exit_code: 0, detail: 'feature flag off' };
   }
 
-  // 24h rate limit — skip + audit "rate_limited".
+  // 24h rate limit — skip WITHOUT an audit row. The autopilot loop invokes
+  // the probe every cycle (~5-10 min), so all but one invocation per day
+  // lands here; logging each skip floods the audit file (~hundreds of
+  // rows/day) and — because doctor treats any non-pass outcome as bad
+  // signal — flips nightly_quality_probe_health to a permanent WARN the
+  // moment the probe is enabled. A skip is a non-event: the real runs are
+  // the signal, and their rows are what gates the next 24h window.
   const now = deps.now();
   const recent = readRecentQualityProbeEvents(2, now); // 2-day window is enough for 24h check
   const decision = shouldRunNightly(now, recent);
   if (!decision.run) {
-    logQualityProbeEvent({
-      outcome: 'rate_limited',
-      exit_code: 0,
-      pass_count: 0,
-      fail_count: 0,
-      inconclusive_count: 0,
-      error_count: 0,
-      est_cost_usd: 0,
-      detail: 'already ran within 24h window',
-    });
     return { outcome: 'rate_limited', exit_code: 0, detail: 'already ran within 24h' };
   }
 

test/autopilot-nightly-probe-wiring.test.ts

@@ -31,10 +31,15 @@ describe('autopilot wiring: nightly quality probe', () => {
     expect(SOURCE).toContain(`runCrossModalBatchForProbe`);
   });
 
-  test('feature flag gate present: cfg.autopilot.nightly_quality_probe.enabled', () => {
+  test('feature flag gate present: dual-plane read (DB row wins, file plane fallback)', () => {
     // Per D10: the scheduler ONLY checks the feature flag. The 24h rate-limit
     // lives inside runNightlyQualityProbe itself (no scheduler-side precheck).
-    expect(SOURCE).toContain(`nightly_quality_probe?.enabled === true`);
+    // The flag resolves through resolveProbeEnabled so `gbrain config set
+    // autopilot.nightly_quality_probe.enabled true` (the doctor hint, DB
+    // plane) and ~/.gbrain/config.json (file plane) BOTH work — a file-only
+    // read made the printed hint a silent no-op.
+    expect(SOURCE).toContain(`getConfig('autopilot.nightly_quality_probe.enabled')`);
+    expect(SOURCE).toMatch(/resolveProbeEnabled\(dbEnabled,\s*cfg\?\.autopilot\?\.nightly_quality_probe\?\.enabled\)/);
   });
 
   test('NO scheduler-side rate-limit check (D10 simplification)', () => {
@@ -64,12 +69,23 @@ describe('autopilot wiring: nightly quality probe', () => {
     expect(SOURCE).toContain(`now:`);
   });
 
+  test('resolveRepoRoot prefers the gbrain package root (committed fixture home), not the brain repoPath', () => {
+    // The DI harness in nightly-quality-probe.test.ts passes process.cwd()
+    // (= the gbrain repo in CI), which papered over the wiring passing
+    // repoPath (= sync.repo_path, the user's BRAIN repo, where the fixture
+    // never exists). Pin the package-root resolution + existence check.
+    expect(SOURCE).toMatch(/fileURLToPath\(new URL\('\.\.\/\.\.', import\.meta\.url\)\)/);
+    expect(SOURCE).toContain(`'longmemeval-nightly.jsonl'`);
+    expect(SOURCE).toMatch(/fixtureAtPkgRoot \? pkgRoot : repoPath/);
+  });
+
   test('hasEmbeddingProvider reads from gateway.isAvailable("embedding") (codex round-2 #12 — in-process, not subprocess)', () => {
     expect(SOURCE).toContain(`isAvailable('embedding')`);
     expect(SOURCE).toContain(`gateway`);
   });
 
-  test('max_usd default = 5 when config unset (matches plan default per D10)', () => {
-    expect(SOURCE).toMatch(/max_usd\s*\?\?\s*5/);
+  test('max_usd resolves dual-plane (default = 5 pinned by resolveProbeMaxUsd unit tests)', () => {
+    expect(SOURCE).toContain(`getConfig('autopilot.nightly_quality_probe.max_usd')`);
+    expect(SOURCE).toMatch(/resolveProbeMaxUsd\(dbMaxUsd,\s*cfg\?\.autopilot\?\.nightly_quality_probe\?\.max_usd\)/);
   });
 });

test/cross-modal-default-slots.test.ts

@@ -0,0 +1,35 @@
+/**
+ * Consistency guard: every cross-modal DEFAULT_SLOTS model must be listed
+ * in its recipe's chat touchpoint. `openai:gpt-4o` drifted out of the
+ * OpenAI recipe while remaining the slot-A default — the gateway then
+ * rejected slot A ("not listed for OpenAI chat") on every install, and the
+ * 3-slot judge panel could never reach its 2-model quorum without a Google
+ * key, pinning every batch verdict at inconclusive (which the nightly
+ * quality probe surfaces as a doctor WARN).
+ */
+import { describe, expect, test } from 'bun:test';
+
+import { DEFAULT_SLOTS } from '../src/core/cross-modal-eval/runner.ts';
+import { getRecipe } from '../src/core/ai/recipes/index.ts';
+import { splitProviderModelId } from '../src/core/model-id.ts';
+
+describe('cross-modal DEFAULT_SLOTS ↔ recipe consistency', () => {
+  test('every default slot model is listed in its recipe chat touchpoint', () => {
+    for (const slot of DEFAULT_SLOTS) {
+      const { provider, model } = splitProviderModelId(slot.model);
+      expect(provider).not.toBeNull();
+      const recipe = getRecipe(provider!);
+      expect(recipe, `slot ${slot.id}: unknown recipe "${provider}"`).toBeDefined();
+      const chatModels = recipe!.touchpoints.chat?.models ?? [];
+      expect(
+        chatModels,
+        `slot ${slot.id}: "${model}" not listed for ${provider} chat — the judge slot can never run`,
+      ).toContain(model);
+    }
+  });
+
+  test('slots span three distinct providers (uncorrelated blind spots)', () => {
+    const providers = new Set(DEFAULT_SLOTS.map(s => splitProviderModelId(s.model).provider));
+    expect(providers.size).toBe(3);
+  });
+});

test/engine-find-trajectory.test.ts

@@ -15,7 +15,7 @@
 
 import { describe, test, expect, beforeAll, afterAll, beforeEach } from 'bun:test';
 import { PGLiteEngine } from '../src/core/pglite-engine.ts';
-import { configureGateway } from '../src/core/ai/gateway.ts';
+import { configureGateway, resetGateway } from '../src/core/ai/gateway.ts';
 import {
   detectRegressions,
   computeDriftScore,
@@ -27,16 +27,19 @@ import type { TrajectoryPoint } from '../src/core/engine.ts';
 let engine: PGLiteEngine;
 
 beforeAll(async () => {
-  // This file hardcodes 1536-d vectors (vecForMetric). initSchema sizes the
-  // facts halfvec column from the AMBIENT gateway state, and a beforeAll runs
-  // before the legacy-embedding-preload's per-test restore — so a preceding
-  // file in the shard that left the gateway reset or non-1536 would seed a
-  // 1280-d schema and every insert here would fail with a width mismatch.
-  // Pin the schema shape explicitly (the pattern bunfig's preload documents).
+  // Pin the embedding dim to 1536 BEFORE initSchema. This file hardcodes
+  // Float32Array(1536) vectors, but initSchema sizes vector columns from
+  // process-global gateway state (getEmbeddingDimensions(), default 1280 =
+  // zeroentropyai). Whether this file passes therefore depended on which
+  // test files happened to run before it in the shard: a predecessor that
+  // leaves the gateway configured without dims (or a bare CI env) yields
+  // vector(1280) and every insert here dies with "expected 1280 dimensions,
+  // not 1536". Same fix + rationale as cosine-rescore-column.test.ts, which
+  // documents this exact class.
   configureGateway({
     embedding_model: 'openai:text-embedding-3-large',
     embedding_dimensions: 1536,
-    env: { ...process.env },
+    env: { OPENAI_API_KEY: 'sk-test-find-trajectory' },
   });
   engine = new PGLiteEngine();
   await engine.connect({});
@@ -45,6 +48,7 @@ beforeAll(async () => {
 
 afterAll(async () => {
   await engine.disconnect();
+  resetGateway();
 });
 
 beforeEach(async () => {

test/nightly-probe-config-plane.test.ts

@@ -0,0 +1,74 @@
+// Regression test for the nightly-quality-probe config-plane split-brain.
+//
+// The doctor check prints a paste-ready enable hint — `gbrain config set
+// autopilot.nightly_quality_probe.enabled true` — which writes the DB config
+// plane. But both the autopilot gate and the doctor check used to read ONLY
+// the file plane (~/.gbrain/config.json via loadConfig), so following the
+// hint was a silent no-op: the probe never ran and doctor kept reporting
+// "disabled (opt-in)".
+//
+// resolveProbeEnabled / resolveProbeMaxUsd pin the dual-plane rule (same
+// precedent as `mcp.publish_skills` in serve-http.ts): DB row wins when
+// present, file plane is the fallback.
+import { describe, expect, test } from 'bun:test';
+
+import {
+  resolveProbeEnabled,
+  resolveProbeMaxUsd,
+} from '../src/core/cycle/nightly-quality-probe.ts';
+
+describe('resolveProbeEnabled — dual-plane flag resolution', () => {
+  test('DB plane "true" enables regardless of file plane (the doctor hint path)', () => {
+    expect(resolveProbeEnabled('true', undefined)).toBe(true);
+    expect(resolveProbeEnabled('true', false)).toBe(true);
+  });
+
+  test('explicit DB "false" wins over file-plane true (config set off sticks)', () => {
+    expect(resolveProbeEnabled('false', true)).toBe(false);
+  });
+
+  test('file plane is the fallback when no DB row exists', () => {
+    expect(resolveProbeEnabled(null, true)).toBe(true);
+    expect(resolveProbeEnabled(undefined, true)).toBe(true);
+    expect(resolveProbeEnabled(null, undefined)).toBe(false);
+    expect(resolveProbeEnabled(null, false)).toBe(false);
+  });
+
+  test('file plane stays strict boolean — string "true" in config.json does not enable', () => {
+    // Matches the pre-fix autopilot gate (`=== true`); the doctor check used
+    // Boolean(...) and could disagree with autopilot on a string value.
+    // Both call sites now share this helper, so they can no longer diverge.
+    expect(resolveProbeEnabled(null, 'true')).toBe(false);
+    expect(resolveProbeEnabled(null, 1)).toBe(false);
+  });
+
+  test('non-"true" DB strings are off (mcp.publish_skills semantics)', () => {
+    expect(resolveProbeEnabled('1', true)).toBe(false);
+    expect(resolveProbeEnabled('yes', true)).toBe(false);
+    expect(resolveProbeEnabled('', true)).toBe(false);
+  });
+});
+
+describe('resolveProbeMaxUsd — dual-plane cost cap resolution', () => {
+  test('DB plane wins when parseable', () => {
+    expect(resolveProbeMaxUsd('2.5', 10)).toBe(2.5);
+    expect(resolveProbeMaxUsd('0', 10)).toBe(0);
+  });
+
+  test('malformed or negative DB value falls through to file plane', () => {
+    expect(resolveProbeMaxUsd('banana', 3)).toBe(3);
+    expect(resolveProbeMaxUsd('-1', 3)).toBe(3);
+  });
+
+  test('file plane used when no DB row; default when both absent/invalid', () => {
+    expect(resolveProbeMaxUsd(null, 7)).toBe(7);
+    expect(resolveProbeMaxUsd(null, '4')).toBe(4);
+    expect(resolveProbeMaxUsd(null, undefined)).toBe(5);
+    expect(resolveProbeMaxUsd(null, 'banana')).toBe(5);
+    expect(resolveProbeMaxUsd(undefined, -2)).toBe(5);
+  });
+
+  test('explicit fallback override is honored', () => {
+    expect(resolveProbeMaxUsd(null, undefined, 12)).toBe(12);
+  });
+});

test/nightly-quality-probe.test.ts

@@ -132,17 +132,20 @@ describe('runNightlyQualityProbe (DI stub harness)', () => {
     });
   });
 
-  test('enabled + recent run within 24h → outcome: rate_limited', async () => {
+  test('enabled + recent run within 24h → outcome: rate_limited, NO audit row', async () => {
     // Pre-seed a recent audit event by running the probe once first.
     await withEnv({ GBRAIN_AUDIT_DIR: auditTmp }, async () => {
       // First run succeeds.
       await runNightlyQualityProbe(makeDeps());
-      // Second run, same hour → rate_limited.
+      // Second run, same hour → rate_limited. A skip is a non-event: the
+      // autopilot loop invokes the probe every cycle (~5-10 min), so
+      // logging each skip would flood the audit file and flip doctor's
+      // any-non-pass-is-bad filter to a permanent WARN.
       const r2 = await runNightlyQualityProbe(makeDeps());
       expect(r2.outcome).toBe('rate_limited');
       const events = await readEvents();
-      expect(events.length).toBe(2);
-      expect(events[1].outcome).toBe('rate_limited');
+      expect(events.length).toBe(1);
+      expect(events[0].outcome).toBe('pass');
     });
   });