fix(schema): block scalars keep '#' as literal content

Inside a YAML block scalar '#' is content, not a comment; parseBlockScalar
was routing lines through stripComment/isBlank, truncating descriptions
like 'see issue #2029' and blanking comment-looking lines. Use the raw
line inside the scalar. Adds a pinning test.

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

src/core/ai/anthropic-key.ts

@@ -18,12 +18,22 @@
 import { loadConfig } from '../config.ts';
 
 export function hasAnthropicKey(): boolean {
-  if (process.env.ANTHROPIC_API_KEY) return true;
+  return resolveAnthropicKey() !== undefined;
+}
+
+/**
+ * Resolve the actual key value: env first, then the gbrain config file.
+ * Callers constructing an Anthropic client directly (e.g. the legacy
+ * subagent path) must pass this as `apiKey` — a bare `new Anthropic()`
+ * only sees env, so launchd/MCP workers with config-stored keys fail.
+ */
+export function resolveAnthropicKey(): string | undefined {
+  if (process.env.ANTHROPIC_API_KEY) return process.env.ANTHROPIC_API_KEY;
   try {
     const cfg = loadConfig();
-    if (cfg?.anthropic_api_key) return true;
+    if (cfg?.anthropic_api_key) return cfg.anthropic_api_key;
   } catch {
     // loadConfig may throw on first-run installs; treat as no key available.
   }
-  return false;
+  return undefined;
 }

src/core/chunkers/code.ts

@@ -18,9 +18,8 @@
  * at runtime.
  */
 
-import { chunkText as recursiveChunk, capByEstimatedTokens, DEFAULT_MAX_EST_TOKENS } from './recursive.ts';
+import { chunkText as recursiveChunk } 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
@@ -112,15 +111,7 @@ 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.
-//
-// 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;
+export const CHUNKER_VERSION = 4;
 
 // Lazy-loaded tree-sitter module (v0.22.x API: Parser is default export)
 let Parser: typeof import('web-tree-sitter') | null = null;
@@ -717,7 +708,7 @@ export async function chunkCodeTextFull(
     if (chunks.length === 0) {
       return { chunks: fallbackChunks(source, filePath, language, opts), edges: rawEdges };
     }
-    return { chunks: capCodeChunks(mergeSmallSiblings(chunks, chunkTarget)), edges: rawEdges };
+    return { chunks: mergeSmallSiblings(chunks, chunkTarget), edges: rawEdges };
   } catch {
     return { chunks: fallbackChunks(source, filePath, language, opts), edges: [] };
   } finally {
@@ -800,33 +791,6 @@ 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

@@ -17,13 +17,7 @@
  * Lossless invariant: non-overlapping portions reassemble to original.
  */
 
-import {
-  countCJKAwareWords,
-  CJK_SENTENCE_DELIMITERS,
-  CJK_CLAUSE_DELIMITERS,
-  charEmbedTokenWeight,
-  estimateEmbeddingTokens,
-} from '../cjk.ts';
+import { countCJKAwareWords, CJK_SENTENCE_DELIMITERS, CJK_CLAUSE_DELIMITERS } from '../cjk.ts';
 
 /**
  * Markdown chunker version. Folded into the per-page chunker_version column
@@ -39,20 +33,8 @@ import {
  * 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 = 4;
+export const MARKDOWN_CHUNKER_VERSION = 3;
 
 const DELIMITERS: string[][] = [
   ['\n\n'],                          // L0: paragraphs
@@ -66,20 +48,8 @@ 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;
@@ -103,7 +73,6 @@ 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 [];
 
@@ -120,9 +89,8 @@ export function chunkText(text: string, opts?: ChunkOptions): TextChunk[] {
 
   const wordCount = countWords(stripped);
   if (wordCount <= chunkSize) {
-    // Single-chunk path: still apply the maxChars + maxTokens caps.
-    const capped = capByChars(stripped.trim(), maxChars)
-      .flatMap((t) => capByEstimatedTokens(t, maxTokens));
+    // Single-chunk path: still apply the maxChars cap.
+    const capped = capByChars(stripped.trim(), maxChars);
     return capped.map((t, i) => ({ text: t, index: i }));
   }
 
@@ -133,14 +101,9 @@ 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) {
-    for (const piece of capByChars(chunk.trim(), maxChars)) {
-      capped.push(...capByEstimatedTokens(piece, maxTokens));
-    }
+    capped.push(...capByChars(chunk.trim(), maxChars));
   }
   return capped.map((t, i) => ({ text: t, index: i }));
 }
@@ -169,68 +132,6 @@ 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
@@ -416,19 +317,7 @@ 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 {
-  const cjkAware = countCJKAwareWords(text);
-  const nonWhitespace = text.replace(/\s/g, '').length;
-  return Math.max(cjkAware, Math.ceil(nonWhitespace / 6));
+  return countCJKAwareWords(text);
 }

src/core/cjk.ts

@@ -65,64 +65,3 @@ 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/minions/handlers/subagent.ts

@@ -48,6 +48,7 @@ import {
   logSubagentHeartbeat,
 } from './subagent-audit.ts';
 import { resolveModel, isAnthropicProvider, TIER_DEFAULTS } from '../../model-config.ts';
+import { resolveAnthropicKey } from '../../ai/anthropic-key.ts';
 import { buildSystemPrompt, DEFAULT_SUBAGENT_SYSTEM } from '../system-prompt.ts';
 import { toolLoop as gatewayToolLoop } from '../../ai/gateway.ts';
 import type { ChatToolDef, ChatMessage, ChatBlock, ChatResult, ToolHandler } from '../../ai/gateway.ts';
@@ -186,7 +187,10 @@ export function makeSubagentHandler(deps: SubagentDeps) {
   // lives at sdk.messages.create. Assigning sdk.messages directly gets the
   // right object; JS method-call semantics preserve `this` at the call
   // site (subagent.ts invokes client.create(...) with client === sdk.messages).
-  const makeAnthropic = deps.makeAnthropic ?? (() => new Anthropic());
+  // Resolve the key env-first, then config (anthropic_api_key) — a bare
+  // new Anthropic() only reads env, so launchd/MCP workers whose key lives
+  // in the gbrain config file would fail auth (#2048).
+  const makeAnthropic = deps.makeAnthropic ?? (() => new Anthropic({ apiKey: resolveAnthropicKey() }));
   const client: MessagesClient = deps.client ?? makeAnthropic().messages;
   const config = deps.config ?? loadConfig() ?? ({ engine: 'postgres' } as GBrainConfig);
   const rateLeaseKey = deps.rateLeaseKey ?? DEFAULT_RATE_KEY;

src/core/operations.ts

@@ -4562,7 +4562,8 @@ const list_schema_packs: Operation = {
     const { existsSync, readdirSync } = await import('node:fs');
     const { join } = await import('node:path');
     const { gbrainPath } = await import('./config.ts');
-    const bundled = ['gbrain-base', 'gbrain-recommended'];
+    const { BUNDLED_PACK_NAMES } = await import('./schema-pack/bundled.ts');
+    const bundled = [...BUNDLED_PACK_NAMES];
     const installedDir = gbrainPath('schema-packs');
     const installed: string[] = [];
     if (existsSync(installedDir)) {

src/core/schema-pack/bundled.ts

@@ -0,0 +1,24 @@
+// Bundled schema-pack registry — single source of truth for the packs that
+// ship in src/core/schema-pack/base/. Keep every bundled-pack consumer
+// (CLI/MCP inspection, active-pack loading, mutation guards, upgrade
+// discovery) on this one list so they cannot drift.
+//
+// v0.39 T8 — gbrain-base + gbrain-recommended.
+// v0.41 T4 — lens packs: creator, investor, engineer, everything (meta-pack).
+// v0.42 type-unification — gbrain-base-v2, the 15-type canonical successor.
+
+export const BUNDLED_PACK_NAMES = [
+  'gbrain-base',
+  'gbrain-recommended',
+  'gbrain-creator',
+  'gbrain-investor',
+  'gbrain-engineer',
+  'gbrain-everything',
+  'gbrain-base-v2',
+] as const;
+
+export type BundledPackName = typeof BUNDLED_PACK_NAMES[number];
+
+export function isBundledPackName(name: string): name is BundledPackName {
+  return (BUNDLED_PACK_NAMES as readonly string[]).includes(name);
+}

src/core/schema-pack/load-active.ts

@@ -37,6 +37,7 @@ import {
   type ResolutionInput,
   type ResolutionResult,
 } from './registry.ts';
+import { isBundledPackName } from './bundled.ts';
 
 /**
  * Inputs the caller (operations.ts handler / engine query path) provides.
@@ -92,28 +93,7 @@ export function _resetPackLocatorForTests(): void {
  * throwing UnknownPackError with a paste-ready install hint.
  */
 function defaultPackLocator(name: string): string | null {
-  // v0.39 T8 — bundled packs registry. gbrain-base + gbrain-recommended
-  // ship in src/core/schema-pack/base/. Add a new entry here to bundle
-  // additional canonical packs.
-  //
-  // v0.41 T4 — lens packs join the bundle: creator (atoms + concepts +
-  // extract_atoms/synthesize_concepts phases), investor (theses + bet
-  // resolution + 3 calibration domains), engineer (gstack-learnings bridge
-  // + 3 calibration domains), everything (meta-pack stacking all three
-  // via extends + borrow_from). Each ships as a real YAML at base/<name>.yaml.
-  const BUNDLED: ReadonlyArray<string> = [
-    'gbrain-base',
-    'gbrain-recommended',
-    'gbrain-creator',
-    'gbrain-investor',
-    'gbrain-engineer',
-    'gbrain-everything',
-    // v0.42 type-unification: 15-type canonical successor to gbrain-base.
-    // Ships as install default (Lane E T17) + via gbrain onboard pack
-    // upgrade flow (the unify-types Minion handler).
-    'gbrain-base-v2',
-  ];
-  if (BUNDLED.includes(name)) {
+  if (isBundledPackName(name)) {
     // Resolve bundled YAML relative to this source file. Works in both
     // direct-bun execution and bun --compile binaries.
     const here = dirname(fileURLToPath(import.meta.url));

src/core/schema-pack/loader.ts

@@ -159,6 +159,29 @@ export function parseYamlMini(content: string): unknown {
     return parseMapping(baseIndent);
   }
 
+  function parseBlockScalar(parentIndent: number, folded: boolean): string {
+    const contentIndent = parentIndent + 2;
+    const out: string[] = [];
+    while (i < lines.length) {
+      const raw = lines[i];
+      // Inside a block scalar everything is literal content — '#' is NOT a
+      // comment here, so use the raw line (no stripComment / isBlank).
+      if (raw.trim() === '') {
+        out.push('');
+        i++;
+        continue;
+      }
+      const indent = indentOf(raw);
+      if (indent <= parentIndent) break;
+      out.push(raw.slice(Math.min(contentIndent, indent)));
+      i++;
+    }
+    if (folded) {
+      return out.join(' ').replace(/\s+$/u, '');
+    }
+    return out.join('\n').replace(/\n+$/u, '');
+  }
+
   function parseSequence(baseIndent: number): unknown[] {
     const result: unknown[] = [];
     while (i < lines.length) {
@@ -227,6 +250,10 @@ export function parseYamlMini(content: string): unknown {
           i++;
           if (rest2 === '') {
             map[key2] = parseBlock(nextIndent + 2);
+          } else if (rest2 === '|' || rest2 === '|-' || rest2 === '|+') {
+            map[key2] = parseBlockScalar(nextIndent, false);
+          } else if (rest2 === '>' || rest2 === '>-' || rest2 === '>+') {
+            map[key2] = parseBlockScalar(nextIndent, true);
           } else {
             map[key2] = parseScalar(rest2);
           }
@@ -257,6 +284,10 @@ export function parseYamlMini(content: string): unknown {
       i++;
       if (rest === '') {
         result[key] = parseBlock(indent + 2);
+      } else if (rest === '|' || rest === '|-' || rest === '|+') {
+        result[key] = parseBlockScalar(indent, false);
+      } else if (rest === '>' || rest === '>-' || rest === '>+') {
+        result[key] = parseBlockScalar(indent, true);
       } else {
         result[key] = parseScalar(rest);
       }

src/core/schema-pack/mutate.ts

@@ -65,6 +65,7 @@ import { invalidateQueryCache } from './query-cache-invalidator.ts';
 import { logMutationFailure, logMutationSuccess, type MutationActor, type MutationOp } from './mutate-audit.ts';
 import { runFilePlaneLintRules } from './lint-rules.ts';
 import { withPackLock, type PackLockOpts } from './pack-lock.ts';
+import { BUNDLED_PACK_NAMES as BUNDLED_PACK_NAME_LIST } from './bundled.ts';
 import type { BrainEngine } from '../engine.ts';
 
 export type PackFileFormat = 'json' | 'yaml';
@@ -93,7 +94,7 @@ export class SchemaPackMutationError extends Error {
   }
 }
 
-export const BUNDLED_PACK_NAMES = new Set(['gbrain-base', 'gbrain-recommended', 'gbrain-base-v2']);
+export const BUNDLED_PACK_NAMES = new Set<string>(BUNDLED_PACK_NAME_LIST);
 
 export interface MutateResult {
   /** Pack name that was mutated. */

test/ai/anthropic-key.test.ts

@@ -10,7 +10,7 @@ import { mkdtempSync, mkdirSync, writeFileSync, rmSync } from 'node:fs';
 import { tmpdir } from 'node:os';
 import { join } from 'node:path';
 import { withEnv } from '../helpers/with-env.ts';
-import { hasAnthropicKey } from '../../src/core/ai/anthropic-key.ts';
+import { hasAnthropicKey, resolveAnthropicKey } from '../../src/core/ai/anthropic-key.ts';
 
 const tmpDirs: string[] = [];
 function freshHome(withConfig?: Record<string, unknown>): string {
@@ -62,3 +62,35 @@ describe('hasAnthropicKey', () => {
     );
   });
 });
+
+describe('resolveAnthropicKey (#2048 — subagent config-key auth)', () => {
+  test('env wins over config', async () => {
+    const home = freshHome({ anthropic_api_key: 'sk-from-config' });
+    await withEnv(
+      { ANTHROPIC_API_KEY: 'sk-from-env', GBRAIN_HOME: home, DATABASE_URL: undefined, GBRAIN_DATABASE_URL: undefined },
+      async () => {
+        expect(resolveAnthropicKey()).toBe('sk-from-env');
+      },
+    );
+  });
+
+  test('config key returned when env unset', async () => {
+    const home = freshHome({ anthropic_api_key: 'sk-from-config' });
+    await withEnv(
+      { ANTHROPIC_API_KEY: undefined, GBRAIN_HOME: home, DATABASE_URL: undefined, GBRAIN_DATABASE_URL: undefined },
+      async () => {
+        expect(resolveAnthropicKey()).toBe('sk-from-config');
+      },
+    );
+  });
+
+  test('neither → undefined', async () => {
+    const home = freshHome();
+    await withEnv(
+      { ANTHROPIC_API_KEY: undefined, GBRAIN_HOME: home, DATABASE_URL: undefined, GBRAIN_DATABASE_URL: undefined },
+      async () => {
+        expect(resolveAnthropicKey()).toBeUndefined();
+      },
+    );
+  });
+});

test/chunker-version-gate.test.ts

@@ -15,22 +15,19 @@ 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 5 for the estimated-token hard cap', () => {
+  test('bumped to 4 for Cathedral II', () => {
     // 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.
-    // 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);
+    expect(CHUNKER_VERSION).toBe(4);
   });
 
   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(5);
+    expect(a).toBe(4);
   });
 });
 

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('v5: estimated-token hard cap on AST-path chunks', () => {
-    expect(CHUNKER_VERSION).toBe(5);
+  test('v0.20.0 Cathedral II Layer 12 bumped to 4', () => {
+    expect(CHUNKER_VERSION).toBe(4);
   });
 });
 

test/chunkers/recursive.test.ts

@@ -135,14 +135,13 @@ describe('Recursive Text Chunker', () => {
 });
 
 describe('CJK chunking (v0.32.7)', () => {
-  test('MARKDOWN_CHUNKER_VERSION is 4', async () => {
+  test('MARKDOWN_CHUNKER_VERSION is 3', 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.
-    // 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.
+    // 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.
     const mod = await import('../../src/core/chunkers/recursive.ts');
-    expect(mod.MARKDOWN_CHUNKER_VERSION).toBe(4);
+    expect(mod.MARKDOWN_CHUNKER_VERSION).toBe(3);
   });
 
   test('long pure-Chinese paragraph splits into multiple chunks', () => {

test/chunkers/token-cap.test.ts

@@ -1,195 +0,0 @@
-/**
- * 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/lens-pack-manifests.test.ts

@@ -55,13 +55,13 @@ describe('v0.41 T4: all 4 bundled lens packs parse cleanly', () => {
 });
 
 describe('v0.41 T4: bundled registry includes lens packs', () => {
-  test('load-active.ts BUNDLED array source includes the 4 lens pack names', () => {
-    const loadActiveSrc = readFileSync(
-      join(here, '..', 'src', 'core', 'schema-pack', 'load-active.ts'),
-      'utf-8',
-    );
+  test('BUNDLED_PACK_NAMES includes the 4 lens pack names', async () => {
+    // The bundled list moved from load-active.ts to bundled.ts (the
+    // single source of truth); assert the array directly instead of
+    // grepping source text.
+    const { BUNDLED_PACK_NAMES } = await import('../src/core/schema-pack/bundled.ts');
     for (const name of PACK_NAMES) {
-      expect(loadActiveSrc).toContain(`'${name}'`);
+      expect(BUNDLED_PACK_NAMES).toContain(name);
     }
   });
 });

test/operations-schema-pack.test.ts

@@ -149,6 +149,9 @@ describe('list_schema_packs', () => {
       seedPack('mine');
       const result = await operationsByName.list_schema_packs!.handler(ctxOf(), {}) as { bundled: string[]; installed: string[] };
       expect(result.bundled).toContain('gbrain-base');
+      expect(result.bundled).toContain('gbrain-recommended');
+      expect(result.bundled).toContain('gbrain-base-v2');
+      expect(result.bundled).toContain('gbrain-investor');
       expect(result.installed).toContain('mine');
     });
   });

test/schema-cli.test.ts

@@ -64,11 +64,14 @@ describe('gbrain schema CLI (Phase C)', () => {
     expect(r.stdout + r.stderr).toMatch(/schema|active|list|show|validate|use/i);
   });
 
-  test('schema list shows gbrain-base bundled', () => {
+  test('schema list shows all bundled packs', () => {
     const r = gbrain(['schema', 'list']);
     expect(r.code).toBe(0);
     expect(r.stdout).toContain('Bundled packs:');
     expect(r.stdout).toContain('gbrain-base');
+    expect(r.stdout).toContain('gbrain-recommended');
+    expect(r.stdout).toContain('gbrain-base-v2');
+    expect(r.stdout).toContain('gbrain-investor');
   });
 
   test('schema show gbrain-base prints manifest details', () => {
@@ -97,6 +100,40 @@ describe('gbrain schema CLI (Phase C)', () => {
     expect(r.stdout).toContain('valid manifest');
   });
 
+  test('schema show/validate exposes bundled gbrain-recommended', () => {
+    const show = gbrain(['schema', 'show', 'gbrain-recommended']);
+    expect(show.code).toBe(0);
+    expect(show.stdout).toContain('gbrain-recommended v1.0.0');
+    expect(show.stdout).toContain('Page types (');
+    expect(show.stdout).toContain('meeting :: temporal');
+
+    const validate = gbrain(['schema', 'validate', 'gbrain-recommended']);
+    expect(validate.code).toBe(0);
+    expect(validate.stdout).toContain('valid manifest');
+  });
+
+  test('schema show exposes bundled gbrain-base-v2 successor pack', () => {
+    const r = gbrain(['schema', 'show', 'gbrain-base-v2']);
+    expect(r.code).toBe(0);
+    expect(r.stdout).toContain('gbrain-base-v2 v1.0.0');
+    expect(r.stdout).toContain('Page types (');
+    expect(r.stdout).toContain('Link verbs (14)');
+  });
+
+  test('schema active loads configured gbrain-recommended with real types', () => {
+    const home = mkdtempSync(join(tmpdir(), 'gbrain-schema-active-recommended-'));
+    try {
+      mkdirSync(join(home, '.gbrain'), { recursive: true });
+      writeFileSync(join(home, '.gbrain', 'config.json'), JSON.stringify({ schema_pack: 'gbrain-recommended' }), 'utf-8');
+      const r = gbrain(['schema', 'active'], { GBRAIN_HOME: home });
+      expect(r.code).toBe(0);
+      expect(r.stdout).toContain('Active pack: gbrain-recommended');
+      expect(r.stdout).not.toContain('Page types: 0');
+    } finally {
+      rmSync(home, { recursive: true, force: true });
+    }
+  });
+
   test('schema active reports default resolution', () => {
     const r = gbrain(['schema', 'active']);
     expect(r.code).toBe(0);

test/schema-pack-loader.test.ts

@@ -345,6 +345,34 @@ describe('YAML mini-parser', () => {
     expect(result.types[1].weight).toBe(2);
   });
 
+  test('parses block scalar without swallowing following keys', () => {
+    const yaml = `name: blocky
+description: |
+  First line.
+  Second line.
+page_types:
+  - name: meeting
+    primitive: temporal
+    path_prefixes:
+      - meetings/
+    aliases: []
+    extractable: true
+    expert_routing: false`;
+    const result = parseYamlMini(yaml) as { description: string; page_types: Array<Record<string, unknown>> };
+    expect(result.description).toBe('First line.\nSecond line.');
+    expect(result.page_types).toHaveLength(1);
+    expect(result.page_types[0].name).toBe('meeting');
+  });
+
+  test('block scalar keeps # as literal content, not a comment', () => {
+    const yaml = `description: |
+  See issue #2029 for context.
+name: hashy`;
+    const result = parseYamlMini(yaml) as Record<string, unknown>;
+    expect(result.description).toBe('See issue #2029 for context.');
+    expect(result.name).toBe('hashy');
+  });
+
   test('strips comments', () => {
     const result = parseYamlMini('# top comment\nname: value # inline comment') as Record<string, unknown>;
     expect(result.name).toBe('value');
@@ -374,6 +402,27 @@ extends: null`;
     const pack = loadPackFromString(json, 'fixture.json');
     expect(pack.name).toBe('json-pack');
   });
+
+  test('loads block-scalar pack descriptions without losing page types', () => {
+    const pack = loadPackFromString(`api_version: gbrain-schema-pack-v1
+name: recommended-fixture
+version: 1.0.0
+extends: gbrain-base
+description: |
+  Operational starter pack.
+page_types:
+  - name: meeting
+    primitive: temporal
+    path_prefixes:
+      - meetings/
+    aliases: []
+    extractable: true
+    expert_routing: false
+link_types: []`, 'fixture.yaml');
+    expect(pack.name).toBe('recommended-fixture');
+    expect(pack.extends).toBe('gbrain-base');
+    expect(pack.page_types.map((t) => t.name)).toContain('meeting');
+  });
 });
 
 describe('ReDoS guard', () => {

test/schema-pack-mutate.test.ts

@@ -103,7 +103,10 @@ describe('locateMutablePackFile — bundled guard', () => {
     expect(BUNDLED_PACK_NAMES.has('gbrain-recommended')).toBe(true);
     // v0.42 (T22): gbrain-base-v2 joins the bundled set.
     expect(BUNDLED_PACK_NAMES.has('gbrain-base-v2')).toBe(true);
-    expect(BUNDLED_PACK_NAMES.size).toBe(3);
+    // Derived from the single bundled registry — the lens packs (creator,
+    // investor, engineer, everything) are read-only too.
+    expect(BUNDLED_PACK_NAMES.has('gbrain-investor')).toBe(true);
+    expect(BUNDLED_PACK_NAMES.size).toBe(7);
   });
 
   it('rejects gbrain-base-v2 with PACK_READONLY (bundled guard)', () => {