fix(chunker): estimated-token hard cap — URL-dense/CJK-fallback chunks overflow strict embedding-server token limits

Takeover of #2847 (rebased onto current master). Fixes #2826.

- cjk.ts: estimateEmbeddingTokens() — conservative per-char-class token
  estimate (CJK 1.0, other 0.75, whitespace 0.1 per code unit).
- recursive.ts (MARKDOWN_CHUNKER_VERSION 3→4): countWords floored at
  ceil(nonWhitespaceChars/6); capByEstimatedTokens() final pass with
  ChunkOptions.maxTokens (default 1500).
- code.ts (CHUNKER_VERSION 4→5): capCodeChunks() applies the same cap to
  AST-path chunks that splitLargeNode can't subdivide.

Co-authored-by: paul-0320 <paul-0320@users.noreply.github.com>

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

src/commands/autopilot.ts

@@ -527,9 +527,6 @@ export async function runAutopilot(engine: BrainEngine, args: string[]) {
   process.on('SIGINT',  () => { void shutdown('SIGINT'); });
 
   let consecutiveErrors = 0;
-  // Parser-probe fixture warning is once-per-process, not once-per-cycle
-  // (compiled-binary installs have no source tree; don't spam the log).
-  let parserProbeFixtureWarned = false;
   // v0.37.7.0 #1162 — counter for consecutive reconnect failures.
   // Reset on every successful health probe or reconnect. Threshold
   // controlled by GBRAIN_AUTOPILOT_MAX_RECONNECT_FAILS env (default 30).
@@ -1076,36 +1073,17 @@ 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 { 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);
+      const probeEnabled = cfg?.autopilot?.nightly_quality_probe?.enabled === true;
       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 { 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'));
+        const maxUsd = Number(cfg?.autopilot?.nightly_quality_probe?.max_usd ?? 5);
         await runNightlyQualityProbe({
           isEnabled: () => true, // already gated above; phase re-checks for defense-in-depth
           hasEmbeddingProvider: () => isAvailable('embedding'),
           resolveMaxUsd: () => maxUsd,
-          resolveRepoRoot: () => (fixtureAtPkgRoot ? pkgRoot : repoPath ?? gbrainHomePath('.')),
+          resolveRepoRoot: () => repoPath ?? gbrainHomePath('.'),
           runLongMemEval: runLongMemEvalForProbe,
           runCrossModalBatch: runCrossModalBatchForProbe,
           now: () => new Date(),
@@ -1117,62 +1095,6 @@ export async function runAutopilot(engine: BrainEngine, args: string[]) {
       // informational; autopilot loop continues.
     }
 
-    // 4.6 — Nightly conversation-parser probe (v0.41.16.0 phase module;
-    // the scheduler wire-up was deferred at ship and is added here). Same
-    // posture as 4.5: the phase owns its gates (enabled/mode-gate, LLM
-    // key), the wiring owns invocation + the audit row, and a probe
-    // failure NEVER crashes the autopilot loop. Per D10 the probe is
-    // default-ON for search.mode=tokenmax, opt-in otherwise.
-    try {
-      const { runConversationParserNightlyProbe } = await import('../core/conversation-parser/nightly-probe.ts');
-      const { logParserProbeEvent, parserProbeRanWithin } = await import('../core/audit-parser-probe.ts');
-      const { isAvailable } = await import('../core/ai/gateway.ts');
-      const { existsSync } = await import('node:fs');
-      const { fileURLToPath } = await import('node:url');
-      const { join } = await import('node:path');
-      // Flag reads dual-plane: the DB row (`gbrain config set …`) wins,
-      // ~/.gbrain/config.json is the fallback. search.mode lives on the
-      // DB plane only (mode.ts owns it).
-      let parserDbEnabled: string | null = null;
-      let dbSearchMode: string | null = null;
-      try {
-        parserDbEnabled = await engine.getConfig('autopilot.conversation_parser_probe.enabled');
-        dbSearchMode = await engine.getConfig('search.mode');
-      } catch { /* DB unavailable → file plane only */ }
-      const parserEnabled = parserDbEnabled != null
-        ? parserDbEnabled === 'true'
-        : cfg?.autopilot?.conversation_parser_probe?.enabled === true;
-      const searchMode = dbSearchMode ?? '';
-      // Fixtures are committed in the gbrain package (test/fixtures/…),
-      // NOT the brain repo — resolve from the module location. Compiled
-      // binaries carry no source tree: skip quietly instead of writing
-      // failure rows that would flip doctor to WARN on every binary install.
-      const pkgRoot = fileURLToPath(new URL('../..', import.meta.url));
-      const fixturePath = join(pkgRoot, 'test', 'fixtures', 'conversation-formats', 'all.jsonl');
-      const adversarialPath = join(pkgRoot, 'test', 'fixtures', 'conversation-formats', 'adversarial.jsonl');
-      const shouldInvoke = parserEnabled || searchMode === 'tokenmax';
-      if (shouldInvoke && existsSync(fixturePath) && existsSync(adversarialPath)) {
-        const result = await runConversationParserNightlyProbe({
-          isEnabled: () => parserEnabled,
-          searchMode: () => searchMode,
-          hasLlmKey: () => isAvailable('chat'),
-          resolveFixturePath: () => fixturePath,
-          resolveAdversarialPath: () => adversarialPath,
-          now: () => new Date(),
-          shouldSkipForRateLimit: () => parserProbeRanWithin(24 * 60 * 60 * 1000),
-        });
-        // rate_limited is a non-run: the loop ticks every few minutes, so
-        // logging every skip would flood the audit file with no-signal rows.
-        if (result.outcome !== 'rate_limited') logParserProbeEvent(result);
-      } else if (shouldInvoke && !parserProbeFixtureWarned) {
-        parserProbeFixtureWarned = true;
-        console.error(`[parser-probe] fixtures not found under ${pkgRoot}; skipping (probe needs a source-checkout install)`);
-      }
-    } catch (e) {
-      logError('autopilot.parser_probe', e);
-      // Informational, like 4.5: do NOT bump consecutiveErrors.
-    }
-
     // Wait for next cycle
     await new Promise(r => setTimeout(r, interval * 1000));
   }

src/commands/doctor.ts

@@ -2960,54 +2960,6 @@ function _resolveSyncFreshnessHours(varName: string, fallback: number): number {
  * branch (disabled / enabled-no-events / enabled-all-pass / enabled-with-failures)
  * without spinning up the audit JSONL or a real config file.
  */
-/**
- * Pure function form of the conversation_parser_probe_health check.
- * Mirrors computeNightlyQualityProbeHealthCheck: skip-with-hint when the
- * probe is off and silent, surface the last 7 days of audit events when
- * it has run, WARN on any non-pass outcome.
- *
- * `effectiveEnabled` folds the D10 mode-gate in: explicitly enabled OR
- * search.mode=tokenmax (where the probe is default-on).
- */
-export function computeConversationParserProbeHealthCheck(
-  effectiveEnabled: boolean,
-  events: ReadonlyArray<{ outcome: string; ts: string; reason?: string }>,
-): Check {
-  const name = 'conversation_parser_probe_health';
-  if (!effectiveEnabled && events.length === 0) {
-    return {
-      name,
-      status: 'ok',
-      message:
-        'disabled (opt-in; default-on only for search.mode=tokenmax). Enable with: ' +
-        '`gbrain config set autopilot.conversation_parser_probe.enabled true`',
-    };
-  }
-  if (events.length === 0) {
-    return {
-      name,
-      status: 'ok',
-      message: 'enabled but no probe events in the last 7 days (next run by autopilot; fixtures require a source-checkout install).',
-    };
-  }
-  const bad = events.filter(e => e.outcome !== 'pass');
-  const latest = events[events.length - 1]!;
-  if (bad.length > 0) {
-    return {
-      name,
-      status: 'warn',
-      message:
-        `${bad.length}/${events.length} probe run(s) in the last 7 days did not pass; ` +
-        `latest: ${latest.outcome}${latest.reason ? ` (${latest.reason})` : ''}`,
-    };
-  }
-  return {
-    name,
-    status: 'ok',
-    message: `${events.length} probe run(s) in the last 7 days, all pass (latest ${latest.ts}).`,
-  };
-}
-
 export function computeNightlyQualityProbeHealthCheck(
   probeEnabled: boolean,
   events: ReadonlyArray<{ outcome: string; ts: string; detail?: string }>,
@@ -4891,17 +4843,10 @@ 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 = resolveProbeEnabled(dbVal, (cfg as any)?.autopilot?.nightly_quality_probe?.enabled);
+      probeEnabled = Boolean((cfg as any)?.autopilot?.nightly_quality_probe?.enabled);
     } catch { /* config unavailable → treat as disabled */ }
     const events = readRecentQualityProbeEvents(7);
     const check = computeNightlyQualityProbeHealthCheck(probeEnabled, events);
@@ -5085,29 +5030,19 @@ export async function buildChecks(
 
   // 3d.5 v0.41.13.0 — conversation_parser_probe_health. Mode-gated
   // per D10: ON when search.mode=tokenmax, opt-in for other modes.
-  // Surfaces the last 7 days of nightly-probe audit events; warn on any
-  // non-pass outcome (fail / budget_exceeded / adversarial_false_positive).
-  // (Until the autopilot wire-up this was a hardcoded "Skipped" stub.)
-  try {
-    const { readRecentParserProbeEvents } = await import('../core/audit-parser-probe.ts');
-    let parserProbeEnabled = false;
-    try {
-      let dbVal: string | null = null;
-      let dbMode: string | null = null;
-      try {
-        dbVal = engine ? await engine.getConfig('autopilot.conversation_parser_probe.enabled') : null;
-        dbMode = engine ? await engine.getConfig('search.mode') : null;
-      } catch { /* DB unavailable → file plane only */ }
-      const { loadConfig } = await import('../core/config.ts');
-      const fileVal = (loadConfig() as any)?.autopilot?.conversation_parser_probe?.enabled;
-      const flagOn = dbVal != null ? dbVal === 'true' : fileVal === true;
-      parserProbeEnabled = flagOn || dbMode === 'tokenmax';
-    } catch { /* config unavailable → treat as disabled */ }
-    const parserEvents = readRecentParserProbeEvents(7);
-    checks.push(computeConversationParserProbeHealthCheck(parserProbeEnabled, parserEvents));
-  } catch {
-    // Best-effort; audit-log read failure shouldn't stop doctor.
-  }
+  // Surface the last 7 days of nightly-probe events; warn on FAIL /
+  // BUDGET_EXCEEDED / adversarial_false_positive.
+  //
+  // v0.41.13.0 ships the probe as opt-in (autopilot wiring deferred
+  // to T7 in the cathedral plan); this check skips with an enable
+  // hint until the probe has at least one audit event written.
+  checks.push({
+    name: 'conversation_parser_probe_health',
+    status: 'ok',
+    message:
+      'Skipped (nightly probe is opt-in; enable with ' +
+      '`gbrain config set autopilot.conversation_parser_probe.enabled true`)',
+  });
 
   // 3e. home_dir_in_worktree (v0.35.8.0). Walks up from `gbrainPath()`
   // looking for a `.git` directory OR file. If found, warns: `~/.gbrain/`

src/commands/eval-cross-modal.ts

@@ -76,7 +76,7 @@ FLAGS:
                            dimensions (goal, depth, sourcing, specificity, useful).
   --cycles N               1-3. Default: 3 in TTY, 1 in non-TTY (T11). Each
                            cycle is 3 model calls; verdict aggregates over them.
-  --slot-a-model <id>      Override default 'openai:gpt-5.2'.
+  --slot-a-model <id>      Override default 'openai:gpt-4o'.
   --slot-b-model <id>      Override default 'anthropic:claude-opus-4-7'.
   --slot-c-model <id>      Override default 'google:gemini-1.5-pro'.
   --receipt-dir <path>     Default: gbrainPath('eval-receipts').
@@ -468,14 +468,6 @@ 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;
 }
 
 /**
@@ -589,7 +581,6 @@ 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) {
@@ -706,11 +697,7 @@ async function runBatchMode(parsed: ParsedArgs, opts: RunCrossModalOpts): Promis
       fn: async (row, idx) => {
         process.stderr.write(`[eval cross-modal batch] ${idx + 1}/${rows.length} ${row.question_id} starting...\n`);
         return await runEvalFn({
-          // With a gold answer the judges can actually verify correctness;
-          // without one they see only {question, hypothesis} and cannot.
-          task: row.answer
-            ? `${row.question}\n\nExpected answer (gold label from the benchmark dataset): ${row.answer}`
-            : row.question,
+          task: row.question,
           output: row.hypothesis,
           slug: row.question_id,
           dimensions,

src/commands/eval-longmemeval.ts

@@ -33,7 +33,6 @@ 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';
 
@@ -470,22 +469,14 @@ 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 — 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;
+  // Same pattern as src/core/think/index.ts:247-249.
   const realClient = new Anthropic();
   const client: ThinkLLMClient = runOpts.client ?? {
-    create: (params, callOpts) =>
-      realClient.messages.create({ ...params, model: toSdkModel(params.model) }, callOpts),
+    create: (params, callOpts) => realClient.messages.create(params, callOpts),
   };
   // v0.40.2.0 — separate extractor client (defaults to same SDK).
   const extractorClient: ThinkLLMClient = runOpts.extractorClient ?? {
-    create: (params, callOpts) =>
-      realClient.messages.create({ ...params, model: toSdkModel(params.model) }, callOpts),
+    create: (params, callOpts) => realClient.messages.create(params, callOpts),
   };
   const trajectoryEnabled = !opts.noTrajectory;
   const extractorModel = trajectoryEnabled
@@ -760,11 +751,6 @@ 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/audit-parser-probe.ts

@@ -1,63 +0,0 @@
-/**
- * Nightly conversation-parser probe audit trail.
- *
- * One event per REAL probe run lands in
- * `~/.gbrain/audit/parser-probe-YYYY-Www.jsonl` (ISO-week rotation via the
- * shared audit-writer primitive; honors `GBRAIN_AUDIT_DIR`).
- * Scheduler-cadence skips (`rate_limited`) are NOT logged — the autopilot
- * loop ticks every few minutes, so logging every skip would flood the
- * audit file with rows that carry no signal.
- *
- * Read by `gbrain doctor`'s `conversation_parser_probe_health` check and
- * by the autopilot wiring's 24h rate-limit gate (`parserProbeRanWithin`).
- */
-
-import { createAuditWriter } from './audit/audit-writer.ts';
-import type { NightlyProbeResult } from './conversation-parser/nightly-probe.ts';
-
-export type ParserProbeAuditEvent = NightlyProbeResult;
-
-const writer = createAuditWriter<ParserProbeAuditEvent>({
-  featureName: 'parser-probe',
-  errorLabel: 'gbrain',
-  errorMessagePrefix: 'parser-probe audit ',
-  errorTrailer: '; probe continues',
-});
-
-/** Append one parser-probe event. Best-effort; never throws. */
-export function logParserProbeEvent(event: ParserProbeAuditEvent): void {
-  writer.log(event);
-}
-
-/**
- * Read recent parser-probe events (current + previous ISO week, filtered
- * to the window). Missing files and corrupt rows are skipped silently.
- */
-export function readRecentParserProbeEvents(
-  days = 7,
-  now: Date = new Date(),
-): ParserProbeAuditEvent[] {
-  return writer.readRecent(days, now);
-}
-
-/** Exposed for tests pinning the rotation edge cases. */
-export function computeParserProbeAuditFilename(now: Date = new Date()): string {
-  return writer.computeFilename(now);
-}
-
-/**
- * 24h rate-limit gate for the autopilot wiring: true when any audited run
- * happened within `windowMs` of `now`. Only REAL outcomes are audited (see
- * module header), so a pass/fail today blocks re-runs until tomorrow while
- * scheduler-cadence skips never extend the window.
- */
-export function parserProbeRanWithin(
-  windowMs: number,
-  now: Date = new Date(),
-): boolean {
-  const cutoff = now.getTime() - windowMs;
-  return readRecentParserProbeEvents(2, now).some((ev) => {
-    const ts = Date.parse(ev.ts);
-    return Number.isFinite(ts) && ts >= cutoff;
-  });
-}

src/core/chunkers/code.ts

@@ -18,8 +18,9 @@
  * at runtime.
  */
 
-import { chunkText as recursiveChunk } from './recursive.ts';
+import { chunkText as recursiveChunk, capByEstimatedTokens, DEFAULT_MAX_EST_TOKENS } from './recursive.ts';
 import { buildQualifiedName } from './qualified-names.ts';
+import { estimateEmbeddingTokens } from '../cjk.ts';
 
 // Embed the tree-sitter runtime + per-language grammars as files.
 // `with { type: 'file' }` returns a path (string) at runtime. Bun bundles
@@ -111,7 +112,15 @@ import G_ZIG from '../../assets/wasm/grammars/tree-sitter-zig.wasm' with { type:
 // chunks get the new columns populated. Without this, the v28 backfill
 // gives every existing chunk a search_vector but subsequent Layer 5 AST
 // work would silently no-op.
-export const CHUNKER_VERSION = 4;
+//
+// v5: estimated-token hard cap on AST-path chunks (capCodeChunks). A node
+// splitLargeNode can't subdivide (giant single-statement function, huge
+// literal) previously shipped WHOLE regardless of size and could overflow
+// strict per-request embedding-token limits (local llama-server crashes
+// past ~2,050 tokens, measured). Mirrors the markdown
+// chunker's v4 cap; fallback-path chunks are already capped inside
+// recursiveChunk.
+export const CHUNKER_VERSION = 5;
 
 // Lazy-loaded tree-sitter module (v0.22.x API: Parser is default export)
 let Parser: typeof import('web-tree-sitter') | null = null;
@@ -708,7 +717,7 @@ export async function chunkCodeTextFull(
     if (chunks.length === 0) {
       return { chunks: fallbackChunks(source, filePath, language, opts), edges: rawEdges };
     }
-    return { chunks: mergeSmallSiblings(chunks, chunkTarget), edges: rawEdges };
+    return { chunks: capCodeChunks(mergeSmallSiblings(chunks, chunkTarget)), edges: rawEdges };
   } catch {
     return { chunks: fallbackChunks(source, filePath, language, opts), edges: [] };
   } finally {
@@ -791,6 +800,33 @@ function mergeSmallSiblings(chunks: CodeChunk[], chunkTarget: number): CodeChunk
   return merged;
 }
 
+/**
+ * v5 final safety pass for AST-path chunks: split any chunk whose
+ * ESTIMATED embedding tokens (conservative per-char-class heuristic,
+ * cjk.ts) exceed DEFAULT_MAX_EST_TOKENS. Reaches chunks the AST logic
+ * can't subdivide — splitLargeNode returns [] for nodes with < 2 body
+ * children (giant single-statement functions, huge literals), which
+ * previously shipped whole at any size.
+ *
+ * Split pieces inherit the source chunk's metadata verbatim; start/end
+ * lines become approximate for pieces after the first. Acceptable —
+ * these chunks exist for embedding + retrieval, and the alternative was
+ * an embedding request the server rejects (or worse, crashes on).
+ */
+function capCodeChunks(chunks: CodeChunk[]): CodeChunk[] {
+  if (chunks.every((c) => estimateEmbeddingTokens(c.text) <= DEFAULT_MAX_EST_TOKENS)) {
+    return chunks;
+  }
+  const out: CodeChunk[] = [];
+  for (const c of chunks) {
+    const pieces = capByEstimatedTokens(c.text, DEFAULT_MAX_EST_TOKENS);
+    for (const piece of pieces) {
+      out.push({ ...c, text: piece, index: out.length, metadata: { ...c.metadata } });
+    }
+  }
+  return out;
+}
+
 function buildMergedChunk(group: CodeChunk[], index: number): CodeChunk {
   const first = group[0]!;
   const last = group[group.length - 1]!;

src/core/chunkers/recursive.ts

@@ -17,7 +17,13 @@
  * Lossless invariant: non-overlapping portions reassemble to original.
  */
 
-import { countCJKAwareWords, CJK_SENTENCE_DELIMITERS, CJK_CLAUSE_DELIMITERS } from '../cjk.ts';
+import {
+  countCJKAwareWords,
+  CJK_SENTENCE_DELIMITERS,
+  CJK_CLAUSE_DELIMITERS,
+  charEmbedTokenWeight,
+  estimateEmbeddingTokens,
+} from '../cjk.ts';
 
 /**
  * Markdown chunker version. Folded into the per-page chunker_version column
@@ -33,8 +39,20 @@ import { countCJKAwareWords, CJK_SENTENCE_DELIMITERS, CJK_CLAUSE_DELIMITERS } fr
  * re-embed (not re-chunk) so existing pages pick up the wrapper on the
  * post-upgrade reembed sweep. See
  * `src/core/contextual-retrieval-service.ts`.
+ *
+ * v4: estimated-token hard cap + whitespace-word undercount fix. The word
+ * pipeline counted a 150-char URL as ONE whitespace word, so URL/phone/
+ * email-dense docs (CJK density < 0.30 → whitespace fallback) produced
+ * 3-4K-char chunks that overflow strict per-request embedding-token
+ * limits (measured: local llama-server crashes past ~2,050 tokens; URL
+ * soup tokenizes at ~1.6 chars/token). Two changes:
+ *   1. countWords() floors the count at ceil(nonWhitespaceChars/6) so a
+ *      URL counts roughly per-character, not as one word.
+ *   2. capByEstimatedTokens() final pass guarantees every chunk fits
+ *      `maxTokens` (default 1500) under a conservative per-char-class
+ *      token estimate, regardless of how word counting misjudged it.
  */
-export const MARKDOWN_CHUNKER_VERSION = 3;
+export const MARKDOWN_CHUNKER_VERSION = 4;
 
 const DELIMITERS: string[][] = [
   ['\n\n'],                          // L0: paragraphs
@@ -48,8 +66,20 @@ export interface ChunkOptions {
   chunkSize?: number;    // target words per chunk (default 300)
   chunkOverlap?: number; // overlap words (default 50)
   maxChars?: number;     // hard cap on any chunk's char length (default 6000)
+  /**
+   * v4: hard cap on any chunk's ESTIMATED embedding tokens (default 1500).
+   * Estimate = conservative per-char-class weights (see cjk.ts
+   * estimateEmbeddingTokens) — deliberately high, so the real tokenizer
+   * count stays below this value. Default leaves headroom for the
+   * contextual-retrieval wrapper (≤ ~630 chars) under a ~2,050-token
+   * per-request embedding server limit.
+   */
+  maxTokens?: number;
 }
 
+/** v4 default for ChunkOptions.maxTokens — see the field doc above. */
+export const DEFAULT_MAX_EST_TOKENS = 1500;
+
 export interface TextChunk {
   text: string;
   index: number;
@@ -73,6 +103,7 @@ export function chunkText(text: string, opts?: ChunkOptions): TextChunk[] {
   const chunkSize = opts?.chunkSize || 300;
   const chunkOverlap = opts?.chunkOverlap || 50;
   const maxChars = opts?.maxChars || 6000;
+  const maxTokens = opts?.maxTokens || DEFAULT_MAX_EST_TOKENS;
 
   if (!text || text.trim().length === 0) return [];
 
@@ -89,8 +120,9 @@ export function chunkText(text: string, opts?: ChunkOptions): TextChunk[] {
 
   const wordCount = countWords(stripped);
   if (wordCount <= chunkSize) {
-    // Single-chunk path: still apply the maxChars cap.
-    const capped = capByChars(stripped.trim(), maxChars);
+    // Single-chunk path: still apply the maxChars + maxTokens caps.
+    const capped = capByChars(stripped.trim(), maxChars)
+      .flatMap((t) => capByEstimatedTokens(t, maxTokens));
     return capped.map((t, i) => ({ text: t, index: i }));
   }
 
@@ -101,9 +133,14 @@ export function chunkText(text: string, opts?: ChunkOptions): TextChunk[] {
   // v0.32.7: hard char cap. Catches pathological CJK + whitespace-less text
   // that the word-level pipeline can't bound (a single Chinese paragraph can
   // exceed 8192 OpenAI embedding tokens at any word count).
+  // v4: estimated-token cap on top — the char cap alone passes token-dense
+  // content (URL soup at ~1.6 chars/token) that overflows strict embedding
+  // server limits.
   const capped: string[] = [];
   for (const chunk of withOverlap) {
-    capped.push(...capByChars(chunk.trim(), maxChars));
+    for (const piece of capByChars(chunk.trim(), maxChars)) {
+      capped.push(...capByEstimatedTokens(piece, maxTokens));
+    }
   }
   return capped.map((t, i) => ({ text: t, index: i }));
 }
@@ -132,6 +169,68 @@ function capByChars(text: string, maxChars: number): string[] {
   return out;
 }
 
+/**
+ * How far back (in chars) the token cap looks for a friendly cut point
+ * before falling back to a hard cut. 300 covers typical rollup/list line
+ * lengths so forced splits land at line starts, not mid-URL.
+ */
+const TOKEN_CAP_CUT_LOOKBACK = 300;
+
+/**
+ * v4: hard-cap a chunk's ESTIMATED embedding tokens. Final safety pass —
+ * runs after capByChars on every chunk, so no upstream miscounting
+ * (whitespace-word fallback, overlap inflation, char-cap survivors) can
+ * emit a chunk past `maxTokens`.
+ *
+ * Cut placement prefers, within the last TOKEN_CAP_CUT_LOOKBACK chars of
+ * the window: a newline, then any whitespace, then a hard cut. This keeps
+ * forced splits off mid-line/mid-URL positions for list-shaped content
+ * and inside code fences. No overlap is added (pieces stay lossless
+ * modulo the trims the char cap already applies).
+ *
+ * @internal exported for the code chunker (code.ts) and tests.
+ */
+export function capByEstimatedTokens(text: string, maxTokens: number): string[] {
+  if (text.length === 0) return [];
+  if (estimateEmbeddingTokens(text) <= maxTokens) return [text];
+
+  const out: string[] = [];
+  let start = 0;
+  while (start < text.length) {
+    // Greedily extend the window until the next char would break the cap.
+    // Always take at least one char so the loop makes forward progress.
+    let est = 0;
+    let end = start;
+    while (end < text.length) {
+      const w = charEmbedTokenWeight(text.charCodeAt(end));
+      if (est + w > maxTokens && end > start) break;
+      est += w;
+      end++;
+    }
+
+    if (end < text.length) {
+      const windowStart = Math.max(start + 1, end - TOKEN_CAP_CUT_LOOKBACK);
+      let cut = text.lastIndexOf('\n', end - 1);
+      if (cut < windowStart) {
+        cut = -1;
+        for (let i = end - 1; i >= windowStart; i--) {
+          const code = text.charCodeAt(i);
+          if (code === 0x20 || (code >= 0x09 && code <= 0x0d)) {
+            cut = i;
+            break;
+          }
+        }
+      }
+      if (cut >= windowStart) end = cut + 1;
+    }
+
+    const slice = text.slice(start, end).trim();
+    if (slice.length > 0) out.push(slice);
+    start = end;
+  }
+  return out;
+}
+
 function recursiveSplit(text: string, level: number, target: number): string[] {
   if (level >= DELIMITERS.length) {
     // Level 4: split on whitespace
@@ -317,7 +416,19 @@ function extractTrailingContext(text: string, targetWords: number): string {
  * Delegated to src/core/cjk.ts so the slugify whitelist, expansion
  * detection, and PGLite keyword fallback all agree on what "CJK enough"
  * means.
+ *
+ * v4: floored at ceil(nonWhitespaceChars/6). The whitespace fallback
+ * counts a 150-char URL as ONE word, so URL/phone/email-dense docs
+ * (whose ASCII mass pushes CJK density below the 0.30 threshold) were
+ * sized at a fraction of their real bulk and merged into 3-4K-char
+ * chunks. The floor makes long whitespace-less runs count roughly
+ * per-character while leaving normal Latin prose untouched (average
+ * English word ≈ 5 chars < 6, so the whitespace count still wins).
+ * Kept local to the chunker — search/expansion.ts keeps the original
+ * countCJKAwareWords semantics for its query-length check.
  */
 function countWords(text: string): number {
-  return countCJKAwareWords(text);
+  const cjkAware = countCJKAwareWords(text);
+  const nonWhitespace = text.replace(/\s/g, '').length;
+  return Math.max(cjkAware, Math.ceil(nonWhitespace / 6));
 }

src/core/cjk.ts

@@ -65,3 +65,64 @@ export function countCJKAwareWords(s: string): number {
 export function escapeLikePattern(s: string): string {
   return s.replace(/\\/g, '\\\\').replace(/%/g, '\\%').replace(/_/g, '\\_');
 }
+
+/**
+ * Conservative per-char-class embedding-token weights (markdown chunker v4).
+ *
+ * Why this exists: the chunker's "word" counting drastically UNDER-counts
+ * whitespace-less ASCII runs (a 150-char URL = 1 whitespace word), so
+ * word-based size targets can emit chunks that overflow an embedding
+ * server's per-request token limit. Measured on a local Qwen3-embedding
+ * llama-server stack:
+ *   - URL/phone/email-dense text tokenizes at ~1.6 chars/token
+ *   - base64-ish / minified blobs approach ~1.3 chars/token (worst case)
+ *   - Korean prose tokenizes NO WORSE than 1 char/token in practice
+ *
+ * Weights are deliberately HIGH (tokens are overestimated) so any cap
+ * based on this estimate is safe against real tokenizers:
+ *   - CJK char        → 1.0 token  (real CJK prose is cheaper)
+ *   - other non-space → 0.75 token (≈1.33 chars/token, covers base64)
+ *   - whitespace      → 0.1 token  (mostly folds into neighbor tokens)
+ */
+export const EMBED_TOKEN_WEIGHT_CJK = 1.0;
+export const EMBED_TOKEN_WEIGHT_OTHER = 0.75;
+export const EMBED_TOKEN_WEIGHT_WS = 0.1;
+
+/** BMP CJK check by UTF-16 code unit — same ranges as CJK_SLUG_CHARS. */
+export function isCJKCodeUnit(code: number): boolean {
+  return (
+    (code >= 0x4e00 && code <= 0x9fff) || // Han
+    (code >= 0x3040 && code <= 0x309f) || // Hiragana
+    (code >= 0x30a0 && code <= 0x30ff) || // Katakana
+    (code >= 0xac00 && code <= 0xd7af)    // Hangul Syllables
+  );
+}
+
+/**
+ * Per-code-unit token weight. Unrecognized whitespace (exotic Unicode
+ * spaces) intentionally falls into OTHER — that only overestimates.
+ */
+export function charEmbedTokenWeight(code: number): number {
+  if (isCJKCodeUnit(code)) return EMBED_TOKEN_WEIGHT_CJK;
+  if (
+    code === 0x20 || (code >= 0x09 && code <= 0x0d) ||
+    code === 0xa0 || code === 0x3000
+  ) {
+    return EMBED_TOKEN_WEIGHT_WS;
+  }
+  return EMBED_TOKEN_WEIGHT_OTHER;
+}
+
+/**
+ * Tokenizer-free embedding-token estimate (conservative overestimate).
+ * See weight docs above. Astral chars count as 2 OTHER code units —
+ * another overestimate, which is the safe direction.
+ */
+export function estimateEmbeddingTokens(s: string): number {
+  if (s.length === 0) return 0;
+  let est = 0;
+  for (let i = 0; i < s.length; i++) {
+    est += charEmbedTokenWeight(s.charCodeAt(i));
+  }
+  return Math.ceil(est);
+}

src/core/config.ts

@@ -105,16 +105,6 @@ export interface GBrainConfig {
        */
       max_usd?: number;
     };
-    /**
-     * v0.41.16.0 — nightly conversation-parser probe. Per D10: default ON
-     * for `search.mode=tokenmax` brains, opt-in for conservative/balanced.
-     * ~$0.05/night with the committed fixtures × Haiku polish. Gated
-     * INSIDE the autopilot tick body, like nightly_quality_probe.
-     */
-    conversation_parser_probe?: {
-      /** Enable for non-tokenmax modes. Defaults to false. */
-      enabled?: boolean;
-    };
     /**
      * v0.42.x (#1685 GAP D) — extract_atoms backlog auto-drain. Default ON so a
      * pack-gated silent backlog never piles up unseen; daily-spend-capped so the

src/core/conversation-parser/nightly-probe.ts

@@ -17,11 +17,11 @@
  * Cost: ~$0.05/night with default fixtures × Haiku polish. Bounded
  * by the active BudgetTracker the autopilot loop creates per-tick.
  *
- * Wired into the autopilot loop (step 4.6 in autopilot.ts), following
- * the same shape as `src/core/cycle/nightly-quality-probe.ts`
- * (v0.40.1.0 Track D / T6): the wiring resolves fixtures from the
- * gbrain package root, writes real outcomes to the parser-probe audit
- * trail (`audit-parser-probe.ts`), and never crashes the loop.
+ * **Wiring into the autopilot loop is deferred to a follow-up**
+ * (filed in TODOS.md). v0.41.16.0 ships the phase as a callable
+ * module so doctor + future cron drivers can invoke it; the
+ * scheduler wire-up follows the same shape as
+ * `src/core/cycle/nightly-quality-probe.ts` (v0.40.1.0 Track D / T6).
  *
  * Test seam: all dependencies are injected via NightlyProbeDeps so
  * unit tests don't touch real LLMs or real fixtures.

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

@@ -44,12 +44,7 @@ export const DEFAULT_DIMENSIONS: string[] = [
  * `--slot-a-model`, `--slot-b-model`, `--slot-c-model` on the CLI.
  */
 export const DEFAULT_SLOTS: SlotConfig[] = [
-  // 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: 'A', model: 'openai:gpt-4o' },
   { id: 'B', model: 'anthropic:claude-opus-4-7' },
   { id: 'C', model: 'google:gemini-1.5-pro' },
 ];

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

@@ -70,28 +70,6 @@ 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 }> {
@@ -103,8 +81,6 @@ 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

@@ -62,42 +62,6 @@ 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.
@@ -137,17 +101,21 @@ export async function runNightlyQualityProbe(deps: NightlyProbeDeps): Promise<Ni
     return { outcome: 'disabled', exit_code: 0, detail: 'feature flag off' };
   }
 
-  // 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.
+  // 24h rate limit — skip + audit "rate_limited".
   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' };
   }
 

src/core/model-pricing.ts

@@ -75,11 +75,6 @@ export const CANONICAL_PRICING: Record<string, ModelPricing> = {
   'openai:gpt-4o':                        { input:  2.50, output: 10.00 },
   'openai:gpt-4o-mini':                   { input:  0.15, output:  0.60 },
   'openai:gpt-5':                         { input:  5.00, output: 20.00 },
-  // gpt-5.2: rates from the OpenAI recipe chat touchpoint (verified
-  // 2026-04-20). Needed here because it's the cross-modal DEFAULT_SLOTS
-  // slot-A model — without a canonical entry estimateCost silently drops
-  // slot A from the --max-usd pre-flight and est_cost_usd audit rows.
-  'openai:gpt-5.2':                       { input:  1.25, output: 10.00 },
   'openai:gpt-5.5':                       { input:  4.00, output: 16.00 },
 
   // ── Google ─────────────────────────────────────────────────────────────

test/audit-parser-probe.serial.test.ts

@@ -1,102 +0,0 @@
-/**
- * Tests for the parser-probe audit trail + the 24h rate-limit gate.
- *
- * Uses GBRAIN_AUDIT_DIR override pointed at a tmpdir for hermeticity
- * (same pattern as audit-slug-fallback.serial.test.ts). Serial because
- * the env override is process-global.
- */
-import { afterEach, beforeEach, describe, expect, test } from 'bun:test';
-import { mkdtempSync, rmSync, readdirSync } from 'node:fs';
-import { tmpdir } from 'node:os';
-import { join } from 'node:path';
-
-import {
-  computeParserProbeAuditFilename,
-  logParserProbeEvent,
-  parserProbeRanWithin,
-  readRecentParserProbeEvents,
-  type ParserProbeAuditEvent,
-} from '../src/core/audit-parser-probe.ts';
-
-let auditDir: string;
-let savedEnv: string | undefined;
-
-beforeEach(() => {
-  auditDir = mkdtempSync(join(tmpdir(), 'parser-probe-audit-'));
-  savedEnv = process.env.GBRAIN_AUDIT_DIR;
-  process.env.GBRAIN_AUDIT_DIR = auditDir;
-});
-
-afterEach(() => {
-  if (savedEnv === undefined) delete process.env.GBRAIN_AUDIT_DIR;
-  else process.env.GBRAIN_AUDIT_DIR = savedEnv;
-  rmSync(auditDir, { recursive: true, force: true });
-});
-
-function makeEvent(overrides: Partial<ParserProbeAuditEvent> = {}): ParserProbeAuditEvent {
-  return {
-    schema_version: 1,
-    ts: new Date().toISOString(),
-    outcome: 'pass',
-    fixtures_total: 12,
-    fixtures_passed: 12,
-    recall_mean: 0.98,
-    participants_recall_mean: 0.97,
-    adversarial_false_positives: 0,
-    failed_fixture_ids: [],
-    ...overrides,
-  };
-}
-
-describe('parser-probe audit trail', () => {
-  test('log + readRecent round-trip', () => {
-    logParserProbeEvent(makeEvent({ outcome: 'fail', reason: '2 fixture(s) failed' }));
-    const events = readRecentParserProbeEvents(7);
-    expect(events.length).toBe(1);
-    expect(events[0]!.outcome).toBe('fail');
-    expect(events[0]!.reason).toBe('2 fixture(s) failed');
-    const files = readdirSync(auditDir);
-    expect(files.length).toBe(1);
-    expect(files[0]).toMatch(/^parser-probe-\d{4}-W\d{2}\.jsonl$/);
-  });
-
-  test('filename uses ISO-week rotation with the parser-probe prefix', () => {
-    // Year-boundary edge pinned by the shared writer's own tests; here we
-    // pin the prefix wiring.
-    expect(computeParserProbeAuditFilename(new Date('2026-07-06T12:00:00Z'))).toBe(
-      'parser-probe-2026-W28.jsonl',
-    );
-  });
-
-  test('readRecent filters by window', () => {
-    const old = new Date(Date.now() - 10 * 86400000).toISOString();
-    logParserProbeEvent(makeEvent({ ts: old }));
-    expect(readRecentParserProbeEvents(7).length).toBe(0);
-  });
-});
-
-describe('parserProbeRanWithin — 24h rate-limit gate', () => {
-  const DAY_MS = 24 * 60 * 60 * 1000;
-
-  test('false when no runs are audited', () => {
-    expect(parserProbeRanWithin(DAY_MS)).toBe(false);
-  });
-
-  test('true when a run landed within the window', () => {
-    logParserProbeEvent(makeEvent({ ts: new Date(Date.now() - 60_000).toISOString() }));
-    expect(parserProbeRanWithin(DAY_MS)).toBe(true);
-  });
-
-  test('false when the last run is older than the window', () => {
-    logParserProbeEvent(makeEvent({ ts: new Date(Date.now() - 25 * 3600_000).toISOString() }));
-    expect(parserProbeRanWithin(DAY_MS)).toBe(false);
-  });
-
-  test('non-pass outcomes also hold the window (mirrors quality-probe semantics)', () => {
-    logParserProbeEvent(makeEvent({
-      outcome: 'no_embedding_key',
-      ts: new Date(Date.now() - 3600_000).toISOString(),
-    }));
-    expect(parserProbeRanWithin(DAY_MS)).toBe(true);
-  });
-});

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

@@ -31,15 +31,10 @@ describe('autopilot wiring: nightly quality probe', () => {
     expect(SOURCE).toContain(`runCrossModalBatchForProbe`);
   });
 
-  test('feature flag gate present: dual-plane read (DB row wins, file plane fallback)', () => {
+  test('feature flag gate present: cfg.autopilot.nightly_quality_probe.enabled', () => {
     // Per D10: the scheduler ONLY checks the feature flag. The 24h rate-limit
     // lives inside runNightlyQualityProbe itself (no scheduler-side precheck).
-    // 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\(dbEnabled,\s*cfg\?\.autopilot\?\.nightly_quality_probe\?\.enabled\)/);
+    expect(SOURCE).toContain(`nightly_quality_probe?.enabled === true`);
   });
 
   test('NO scheduler-side rate-limit check (D10 simplification)', () => {
@@ -69,23 +64,12 @@ 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 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('max_usd default = 5 when config unset (matches plan default per D10)', () => {
+    expect(SOURCE).toMatch(/max_usd\s*\?\?\s*5/);
   });
 });

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

@@ -1,77 +0,0 @@
-/**
- * Source-shape regression tests for the autopilot wiring of
- * `runConversationParserNightlyProbe` (step 4.6).
- *
- * Same rationale as autopilot-nightly-probe-wiring.test.ts: the loop is
- * hard to drive end-to-end, so these pin the structural protections —
- * the dual-plane flag read, the D10 tokenmax mode-gate, the package-root
- * fixture resolution, the audit-flood guard, and the try/catch posture.
- *
- * The probe's own gate/scoring logic is pinned by the module's unit
- * tests; the audit trail by audit-parser-probe.serial.test.ts.
- */
-
-import { describe, test, expect } from 'bun:test';
-import { readFileSync } from 'node:fs';
-import { resolve } from 'node:path';
-
-const AUTOPILOT_SRC = resolve('src/commands/autopilot.ts');
-const SOURCE = readFileSync(AUTOPILOT_SRC, 'utf-8');
-
-describe('autopilot wiring: conversation-parser probe', () => {
-  test('invokes the phase module and the audit trail', () => {
-    expect(SOURCE).toContain(`runConversationParserNightlyProbe`);
-    expect(SOURCE).toContain(`conversation-parser/nightly-probe`);
-    expect(SOURCE).toContain(`logParserProbeEvent`);
-    expect(SOURCE).toContain(`audit-parser-probe`);
-  });
-
-  test('flag reads dual-plane: DB row (gbrain config set) wins, file plane fallback', () => {
-    expect(SOURCE).toContain(`getConfig('autopilot.conversation_parser_probe.enabled')`);
-    expect(SOURCE).toContain(`cfg?.autopilot?.conversation_parser_probe?.enabled === true`);
-  });
-
-  test('D10 mode-gate present: tokenmax brains run the probe by default', () => {
-    expect(SOURCE).toMatch(/parserEnabled \|\| searchMode === 'tokenmax'/);
-  });
-
-  test('fixtures resolve from the gbrain package root, NOT the brain repoPath', () => {
-    // The committed fixtures live in the gbrain source tree; resolving
-    // them against sync.repo_path would point into the user's brain repo.
-    expect(SOURCE).toMatch(/fileURLToPath\(new URL\('\.\.\/\.\.', import\.meta\.url\)\)/);
-    expect(SOURCE).toContain(`'conversation-formats', 'all.jsonl'`);
-    expect(SOURCE).toContain(`'conversation-formats', 'adversarial.jsonl'`);
-  });
-
-  test('missing fixtures skip quietly (no audit row, once-per-process stderr note)', () => {
-    // Compiled-binary installs carry no source tree; writing failure rows
-    // would flip doctor to WARN on every binary install.
-    expect(SOURCE).toContain(`parserProbeFixtureWarned`);
-  });
-
-  test('rate_limited outcomes are NOT audit-logged (flood guard)', () => {
-    expect(SOURCE).toMatch(/outcome !== 'rate_limited'\) logParserProbeEvent\(result\)/);
-  });
-
-  test('rate-limit gate delegates to the audit module, not inline event reads', () => {
-    expect(SOURCE).toContain(`parserProbeRanWithin(24 * 60 * 60 * 1000)`);
-  });
-
-  test('LLM-key gate reads gateway.isAvailable("chat") in-process', () => {
-    expect(SOURCE).toContain(`isAvailable('chat')`);
-  });
-
-  test('probe call wrapped in try/catch that does NOT bump consecutiveErrors', () => {
-    expect(SOURCE).toMatch(/catch[\s\S]*?autopilot\.parser_probe[\s\S]*?do NOT bump consecutiveErrors/);
-  });
-
-  test('DI shape: the exact 7 fields of the parser probe NightlyProbeDeps', () => {
-    expect(SOURCE).toContain(`isEnabled:`);
-    expect(SOURCE).toContain(`searchMode:`);
-    expect(SOURCE).toContain(`hasLlmKey:`);
-    expect(SOURCE).toContain(`resolveFixturePath:`);
-    expect(SOURCE).toContain(`resolveAdversarialPath:`);
-    expect(SOURCE).toContain(`shouldSkipForRateLimit:`);
-    expect(SOURCE).toContain(`now:`);
-  });
-});

test/chunker-version-gate.test.ts

@@ -15,19 +15,22 @@ import { describe, test, expect } from 'bun:test';
 import { CHUNKER_VERSION } from '../src/core/chunkers/code.ts';
 
 describe('Layer 12 — CHUNKER_VERSION constant', () => {
-  test('bumped to 4 for Cathedral II', () => {
+  test('bumped to 5 for the estimated-token hard cap', () => {
     // v3: v0.19.0 Chonkie parity (tokenizer + small-sibling merge).
     // v4: v0.20.0 Cathedral II (qualified names + parent scope + doc_comment
     //     + fence extraction + chunk-grain FTS). Folded into content_hash
     //     so any bump forces clean re-chunks on next sync.
-    expect(CHUNKER_VERSION).toBe(4);
+    // v5: estimated-token hard cap on AST-path chunks (capCodeChunks) so
+    //     un-subdividable giant nodes can't overflow strict embedding
+    //     server token limits.
+    expect(CHUNKER_VERSION).toBe(5);
   });
 
   test('is stable across imports (not recomputed at call time)', async () => {
     const a = (await import('../src/core/chunkers/code.ts')).CHUNKER_VERSION;
     const b = (await import('../src/core/chunkers/code.ts')).CHUNKER_VERSION;
     expect(a).toBe(b);
-    expect(a).toBe(4);
+    expect(a).toBe(5);
   });
 });
 

test/chunkers/code.test.ts

@@ -10,8 +10,8 @@ import { describe, test, expect } from 'bun:test';
 import { chunkCodeText, detectCodeLanguage, CHUNKER_VERSION } from '../../src/core/chunkers/code.ts';
 
 describe('CHUNKER_VERSION', () => {
-  test('v0.20.0 Cathedral II Layer 12 bumped to 4', () => {
-    expect(CHUNKER_VERSION).toBe(4);
+  test('v5: estimated-token hard cap on AST-path chunks', () => {
+    expect(CHUNKER_VERSION).toBe(5);
   });
 });
 

test/chunkers/recursive.test.ts

@@ -135,13 +135,14 @@ describe('Recursive Text Chunker', () => {
 });
 
 describe('CJK chunking (v0.32.7)', () => {
-  test('MARKDOWN_CHUNKER_VERSION is 3', async () => {
+  test('MARKDOWN_CHUNKER_VERSION is 4', async () => {
     // v0.40.3.0: bumped 2→3 to signal the post-upgrade reembed sweep that
-    // contextual retrieval wrapping is now applied at embed time. Chunk
-    // boundaries themselves are unchanged; the bump forces re-embed for
-    // pages where chunker_version < 3.
+    // contextual retrieval wrapping is now applied at embed time.
+    // v4: estimated-token hard cap + whitespace-word undercount floor
+    // (URL-dense docs produced chunks past strict embedding server token
+    // limits). Boundary change → forces re-chunk for chunker_version < 4.
     const mod = await import('../../src/core/chunkers/recursive.ts');
-    expect(mod.MARKDOWN_CHUNKER_VERSION).toBe(3);
+    expect(mod.MARKDOWN_CHUNKER_VERSION).toBe(4);
   });
 
   test('long pure-Chinese paragraph splits into multiple chunks', () => {

test/chunkers/token-cap.test.ts

@@ -0,0 +1,195 @@
+/**
+ * Markdown chunker v4 / code chunker v5 — estimated-token hard cap
+ * regression tests.
+ *
+ * Reproduces a field failure: a local llama-server embedding backend
+ * (`-ub 2048`) crashes deterministically (trace/BPT trap → EOF at the
+ * client) when a single chunk exceeds ~2,050 real tokens. Two content
+ * shapes triggered it:
+ *
+ *   1. Korean docs carrying one long source URL per line.
+ *      The URLs' ASCII mass pushes CJK density below 0.30, flipping
+ *      countCJKAwareWords to whitespace counting, where a 150-char URL
+ *      counts as ONE word → chunks ballooned to 3-4K chars ≈ 2,000+
+ *      real tokens (URL soup tokenizes at ~1.6 chars/token).
+ *
+ *   2. Large JSON code blocks (~7K chars) that the word pipeline
+ *      undercounts the same way (few whitespace tokens).
+ *
+ * The fix: every emitted chunk must satisfy
+ *   estimateEmbeddingTokens(chunk) <= maxTokens (default 1500)
+ * where the estimate deliberately OVERSTATES real tokenizer counts.
+ */
+
+import { describe, test, expect } from 'bun:test';
+import { chunkText, capByEstimatedTokens, DEFAULT_MAX_EST_TOKENS } from '../../src/core/chunkers/recursive.ts';
+import { chunkCodeText } from '../../src/core/chunkers/code.ts';
+import { estimateEmbeddingTokens } from '../../src/core/cjk.ts';
+
+/** Synthesize the failing shape: Korean rollup lines each ending in a long Notion URL. */
+function urlDenseKoreanRollup(lines: number): string {
+  const out: string[] = ['# 링크가 줄마다 붙는 한국어 예시 문서', ''];
+  for (let i = 0; i < lines; i++) {
+    const hex32 = (i * 2654435761 >>> 0).toString(16).padStart(8, '0').repeat(4);
+    out.push(
+      `- **항목 ${i}**: 이 줄은 청커 동작 검증을 위한 의미 없는 한국어 예시 문장입니다 · 전화 000-0000-${String(1000 + i)} · ` +
+      `이메일 user${i}@example.com · 링크: https://docs.example.com/pages/${hex32}?v=abcdef0123456789&ref=sample`,
+    );
+  }
+  return out.join('\n');
+}
+
+/** Synthesize a large pretty-printed JSON block with CJK values. */
+function bigJsonBlock(targetChars: number): string {
+  const entries: string[] = [];
+  let i = 0;
+  let len = 0;
+  while (len < targetChars) {
+    const row =
+      `  "item_${i}": { "name": "예시-${i}", "url": "https://example.com/api/v2/items/${i}?token=abc${i}def", "qty": ${i % 100}, "memo": "한국어 값이 섞인 예시 데이터" }`;
+    entries.push(row);
+    len += row.length;
+    i++;
+  }
+  return `{\n${entries.join(',\n')}\n}`;
+}
+
+describe('v4 estimated-token cap — URL-dense Korean doc (field-failure shape)', () => {
+  test('every chunk stays under the estimated-token cap', () => {
+    const md = urlDenseKoreanRollup(60);
+    const chunks = chunkText(md);
+    expect(chunks.length).toBeGreaterThan(0);
+    for (const c of chunks) {
+      expect(estimateEmbeddingTokens(c.text)).toBeLessThanOrEqual(DEFAULT_MAX_EST_TOKENS);
+    }
+  });
+
+  test('no chunk reaches the measured 3K-char danger zone for URL soup', () => {
+    const md = urlDenseKoreanRollup(60);
+    const chunks = chunkText(md);
+    // 1500 est tokens at the OTHER weight (0.75/char) bounds chunks to
+    // ~2,000 chars for pure ASCII — well under the ~3,300 chars where
+    // URL-dense content crosses ~2,050 real tokens (1.6 chars/token).
+    for (const c of chunks) {
+      expect(c.text.length).toBeLessThanOrEqual(2600);
+    }
+  });
+
+  test('content is preserved (no lines dropped by the cap)', () => {
+    const md = urlDenseKoreanRollup(60);
+    const chunks = chunkText(md);
+    const joined = chunks.map((c) => c.text).join('\n');
+    // Spot-check first / middle / last rollup lines survive chunking.
+    for (const marker of ['항목 0', '항목 30', '항목 59']) {
+      expect(joined).toContain(marker);
+    }
+  });
+});
+
+describe('v4 estimated-token cap — large JSON blocks', () => {
+  test('7K-char pretty JSON through the prose path stays under the cap', () => {
+    const md = `설정 파일 원문 보존:\n\n\`\`\`\n${bigJsonBlock(7000)}\n\`\`\`\n`;
+    const chunks = chunkText(md);
+    expect(chunks.length).toBeGreaterThan(1);
+    for (const c of chunks) {
+      expect(estimateEmbeddingTokens(c.text)).toBeLessThanOrEqual(DEFAULT_MAX_EST_TOKENS);
+    }
+  });
+
+  test('7K-char minified JSON (single whitespace-less token) stays under the cap', () => {
+    const minified = bigJsonBlock(7000).replace(/\n\s*/g, '');
+    const chunks = chunkText(minified);
+    expect(chunks.length).toBeGreaterThan(1);
+    for (const c of chunks) {
+      expect(estimateEmbeddingTokens(c.text)).toBeLessThanOrEqual(DEFAULT_MAX_EST_TOKENS);
+    }
+  });
+
+  test('json fence via the code chunker stays under the cap (+header slack)', async () => {
+    const chunks = await chunkCodeText(bigJsonBlock(7000), 'fence.json');
+    expect(chunks.length).toBeGreaterThan(0);
+    for (const c of chunks) {
+      // buildChunk prepends a short "[JSON] fence.json:…" header AFTER the
+      // body-level cap; allow ~60 est tokens of header slack. Real-token
+      // safety margin (2,050 − overestimated 1,500) absorbs this easily.
+      expect(estimateEmbeddingTokens(c.text)).toBeLessThanOrEqual(DEFAULT_MAX_EST_TOKENS + 60);
+    }
+  });
+});
+
+describe('v4 word-count floor — behavior preserved for normal content', () => {
+  test('Latin prose chunking is unchanged by the floor (avg word < 6 chars)', () => {
+    const prose = Array.from({ length: 120 }, (_, i) =>
+      `This is sentence number ${i} and it talks about ordinary things in plain words.`,
+    ).join(' ');
+    const chunks = chunkText(prose);
+    // Historical behavior: ~1,560 whitespace words → multiple ~300-word chunks.
+    expect(chunks.length).toBeGreaterThan(3);
+    for (const c of chunks) {
+      const words = c.text.split(/\s+/).length;
+      expect(words).toBeLessThanOrEqual(300 * 1.5 + 50); // merge cap + overlap
+    }
+  });
+
+  test('Korean prose (CJK-dense, no URLs) never triggers the token cap', () => {
+    const prose = Array.from({ length: 80 }, (_, i) =>
+      `이 문장은 순수 한국어 산문의 청킹 동작을 확인하기 위한 ${i}번째 예시 문장입니다.`,
+    ).join(' ');
+    const chunks = chunkText(prose);
+    expect(chunks.length).toBeGreaterThan(1);
+    for (const c of chunks) {
+      // CJK-dense chunks are char-counted (≈450 max) — nowhere near 1500.
+      expect(estimateEmbeddingTokens(c.text)).toBeLessThanOrEqual(700);
+    }
+  });
+});
+
+describe('capByEstimatedTokens unit behavior', () => {
+  test('returns input unchanged when under the cap', () => {
+    expect(capByEstimatedTokens('short text', 1500)).toEqual(['short text']);
+    expect(capByEstimatedTokens('', 1500)).toEqual([]);
+  });
+
+  test('prefers newline cut points within the lookback window', () => {
+    const line = 'x'.repeat(100);
+    const text = Array.from({ length: 40 }, () => line).join('\n');
+    const pieces = capByEstimatedTokens(text, 1000);
+    expect(pieces.length).toBeGreaterThan(1);
+    for (const p of pieces) {
+      // Every piece should be whole lines (multiples of the 100-char line).
+      for (const l of p.split('\n')) {
+        expect(l).toBe(line);
+      }
+    }
+  });
+
+  test('makes forward progress on whitespace-less input (hard cut)', () => {
+    const blob = 'a'.repeat(10_000);
+    const pieces = capByEstimatedTokens(blob, 1000);
+    expect(pieces.length).toBeGreaterThan(1);
+    expect(pieces.join('')).toBe(blob);
+    for (const p of pieces) {
+      expect(estimateEmbeddingTokens(p)).toBeLessThanOrEqual(1000);
+    }
+  });
+});
+
+describe('estimateEmbeddingTokens — weight sanity', () => {
+  test('overestimates URL-dense ASCII (0.75/char ≥ measured ~0.63/char)', () => {
+    const url = 'https://docs.example.com/pages/a1b2c3d4e5f6a1b2c3d4e5f6a1b2c3d4?v=abc&ref=sample';
+    const est = estimateEmbeddingTokens(url);
+    expect(est).toBeGreaterThanOrEqual(Math.floor(url.length * 0.7));
+  });
+
+  test('counts CJK at 1 token/char', () => {
+    expect(estimateEmbeddingTokens('가나다라마')).toBe(5);
+  });
+
+  test('whitespace is nearly free', () => {
+    expect(estimateEmbeddingTokens('   \n\t  ')).toBeLessThanOrEqual(1);
+  });
+
+  test('empty string is 0', () => {
+    expect(estimateEmbeddingTokens('')).toBe(0);
+  });
+});

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

@@ -1,47 +0,0 @@
-/**
- * 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';
-import { canonicalLookup } from '../src/core/model-pricing.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('every default slot model has a canonical pricing entry', () => {
-    // Without one, estimateCost silently drops the slot from the
-    // --max-usd pre-flight and est_cost_usd audit rows (~1/3 under-count).
-    for (const slot of DEFAULT_SLOTS) {
-      expect(
-        canonicalLookup(slot.model),
-        `slot ${slot.id}: "${slot.model}" missing from CANONICAL_PRICING`,
-      ).toBeDefined();
-    }
-  });
-
-  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/doctor-parser-probe-check.test.ts

@@ -1,51 +0,0 @@
-/**
- * Tests for computeConversationParserProbeHealthCheck — the pure function
- * behind doctor's conversation_parser_probe_health check, which replaced
- * the v0.41.13.0 hardcoded "Skipped" stub when the autopilot wiring
- * landed. Mirrors the branch coverage style of the quality-probe check.
- */
-import { describe, expect, test } from 'bun:test';
-
-import { computeConversationParserProbeHealthCheck } from '../src/commands/doctor.ts';
-
-const ev = (outcome: string, reason?: string, ts = new Date().toISOString()) => ({
-  outcome,
-  ts,
-  ...(reason !== undefined ? { reason } : {}),
-});
-
-describe('computeConversationParserProbeHealthCheck', () => {
-  test('disabled + no events → ok with paste-ready enable hint', () => {
-    const check = computeConversationParserProbeHealthCheck(false, []);
-    expect(check.status).toBe('ok');
-    expect(check.message).toContain('gbrain config set autopilot.conversation_parser_probe.enabled true');
-  });
-
-  test('enabled + no events yet → ok, next run by autopilot', () => {
-    const check = computeConversationParserProbeHealthCheck(true, []);
-    expect(check.status).toBe('ok');
-    expect(check.message).toContain('no probe events');
-  });
-
-  test('disabled flag but events exist (tokenmax mode-gate ran it) → events win over the hint', () => {
-    const check = computeConversationParserProbeHealthCheck(false, [ev('pass')]);
-    expect(check.status).toBe('ok');
-    expect(check.message).toContain('all pass');
-  });
-
-  test('any non-pass outcome in the window → warn, latest surfaced with reason', () => {
-    const check = computeConversationParserProbeHealthCheck(true, [
-      ev('pass'),
-      ev('adversarial_false_positive', '1 adversarial fixture(s) parsed to non-empty'),
-    ]);
-    expect(check.status).toBe('warn');
-    expect(check.message).toContain('adversarial_false_positive');
-    expect(check.message).toContain('parsed to non-empty');
-  });
-
-  test('all pass → ok with run count', () => {
-    const check = computeConversationParserProbeHealthCheck(true, [ev('pass'), ev('pass')]);
-    expect(check.status).toBe('ok');
-    expect(check.message).toContain('2 probe run(s)');
-  });
-});

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

@@ -1,74 +0,0 @@
-// 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

@@ -132,20 +132,17 @@ describe('runNightlyQualityProbe (DI stub harness)', () => {
     });
   });
 
-  test('enabled + recent run within 24h → outcome: rate_limited, NO audit row', async () => {
+  test('enabled + recent run within 24h → outcome: rate_limited', 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. 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.
+      // Second run, same hour → rate_limited.
       const r2 = await runNightlyQualityProbe(makeDeps());
       expect(r2.outcome).toBe('rate_limited');
       const events = await readEvents();
-      expect(events.length).toBe(1);
-      expect(events[0].outcome).toBe('pass');
+      expect(events.length).toBe(2);
+      expect(events[1].outcome).toBe('rate_limited');
     });
   });