fix(schema-pack): restore v2 capability parity + derive bundled-pack list + calibration holder config

- #2109: extract-timeline-from-meetings matches frontmatter.legacy_type='meeting'
  in both SQL sites so unify-types-migrated (gbrain-base-v2) brains keep the
  feature alive; pre-unify type='meeting' behavior unchanged.
- #2117: gbrain-base-v2 declares phases: [extract_atoms] and ports v1's
  founded/works_at/invested_in inference regexes so extract_atoms is no longer
  pack-gated off and extract-ner no longer returns pack_unavailable on the
  bundled default pack. (attended's page_type:meeting inference deliberately
  not ported — v2 declares no meeting type; lint would reject it.)
- #1726 (A): list_schema_packs derives from the exported BUNDLED_PACKS registry
  in load-active.ts instead of a frozen 2-of-7 literal.
- #1726 (B): new calibration.user_holder config key (symmetric with
  emotional_weight.user_holder) resolved by the calibration_profile phase, the
  gbrain calibration CLI, and the get_calibration_profile op; explicit
  holder param still wins; 'garry' stays the fallback.

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

src/commands/calibration.ts

@@ -19,7 +19,7 @@
  */
 
 import type { BrainEngine } from '../core/engine.ts';
-import { runPhaseCalibrationProfile } from '../core/cycle/calibration-profile.ts';
+import { resolveCalibrationHolder, runPhaseCalibrationProfile } from '../core/cycle/calibration-profile.ts';
 import { sourceScopeOpts, type OperationContext } from '../core/operations.ts';
 import type { GBrainConfig } from '../core/config.ts';
 import { GBrainError } from '../core/types.ts';
@@ -167,7 +167,7 @@ export async function runCalibration(
   config: GBrainConfig,
 ): Promise<void> {
   const { opts } = parseArgs(args);
-  const holder = opts.holder ?? 'garry';
+  const holder = await resolveCalibrationHolder(engine, opts.holder);
   // Resolve --source / GBRAIN_SOURCE / .gbrain-source so the (now reachable, #2035)
   // calibration command targets the right source in a multi-source brain instead
   // of always reading `default`. No signal → 'default' (prior behavior).
@@ -253,14 +253,14 @@ export async function getCalibrationProfileOp(
   ctx: OperationContext,
   params: { holder?: string },
 ): Promise<CalibrationProfileRow | null> {
-  const holder = params.holder ?? 'garry';
-  if (typeof holder !== 'string' || holder.length === 0) {
+  if (params.holder !== undefined && (typeof params.holder !== 'string' || params.holder.length === 0)) {
     throw new GBrainError(
       'INVALID_HOLDER',
       'get_calibration_profile.holder must be a non-empty string',
-      'pass holder="<slug>" or omit to default to "garry"',
+      'pass holder="<slug>" or omit to default to the calibration.user_holder config (then "garry")',
     );
   }
+  const holder = await resolveCalibrationHolder(ctx.engine, params.holder);
   const scope = sourceScopeOpts(ctx);
   return getLatestProfile(ctx.engine, { holder, ...scope });
 }

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/config.ts

@@ -928,6 +928,10 @@ export const KNOWN_CONFIG_KEYS: readonly string[] = [
   // Emotional weight (v0.29)
   'emotional_weight.high_tags',
   'emotional_weight.user_holder',
+  // Calibration holder (#1726): persistent default for the nightly
+  // calibration_profile phase + `gbrain calibration`, symmetric with
+  // emotional_weight.user_holder. Falls back to 'garry' when unset.
+  'calibration.user_holder',
   // Cycle phase config
   'cycle.grade_takes.write_gstack_learnings',
   // Content sanity (v0.41)

src/core/cycle/calibration-profile.ts

@@ -96,7 +96,7 @@ export type PatternStatementsGenerator = (input: {
 export type BiasTagsGenerator = (patterns: string[]) => Promise<string[]>;
 
 export interface CalibrationProfileOpts extends BasePhaseOpts {
-  /** Holder to generate the profile for. Default 'garry'. */
+  /** Holder to generate the profile for. Default: `calibration.user_holder` config, then 'garry'. */
   holder?: string;
   /** Inject the patterns generator (tests). */
   patternsGenerator?: PatternStatementsGenerator;
@@ -194,6 +194,26 @@ export function parseBiasTagsOutput(raw: string): string[] {
     .slice(0, 4);
 }
 
+/**
+ * #1726: resolve the calibration holder. Explicit param wins, then the
+ * persistent `calibration.user_holder` config key (symmetric with
+ * emotional_weight.user_holder), then the legacy 'garry' default. Fail-open:
+ * a missing config table / mock engine without getConfig falls through.
+ */
+export async function resolveCalibrationHolder(
+  engine: BrainEngine,
+  explicit?: string,
+): Promise<string> {
+  if (explicit) return explicit;
+  try {
+    const configured = await engine.getConfig('calibration.user_holder');
+    if (configured && configured.trim().length > 0) return configured.trim();
+  } catch {
+    // Config unavailable — use the legacy default.
+  }
+  return 'garry';
+}
+
 /** Pick the "loudest" pattern slot for the template fallback. */
 function pickFallbackSlots(scorecard: TakesScorecard): PatternStatementSlots {
   if (!scorecard || scorecard.resolved === 0) {
@@ -227,7 +247,7 @@ class CalibrationProfilePhase extends BaseCyclePhase {
     _ctx: OperationContext,
     opts: CalibrationProfileOpts,
   ): Promise<{ summary: string; details: Record<string, unknown>; status?: PhaseStatus }> {
-    const holder = opts.holder ?? 'garry';
+    const holder = await resolveCalibrationHolder(engine, opts.holder);
     const promptVersion = opts.promptVersion ?? CALIBRATION_PROFILE_PROMPT_VERSION;
     const modelId = opts.model ?? TIER_DEFAULTS.reasoning;
     const gradeCompletion = opts.gradeCompletion ?? 1.0;

src/core/extract-timeline-from-meetings.ts

@@ -68,11 +68,14 @@ export async function extractTimelineFromMeetings(
   // 1. Fetch all meeting pages (one round-trip).
   const sourceFilter = opts.sourceIdFilter ? `AND source_id = $1` : '';
   const meetingParams = opts.sourceIdFilter ? [opts.sourceIdFilter] : [];
+  // #2109: gbrain-base-v2's unify-types catch-all retypes meeting pages to
+  // `note` with frontmatter.legacy_type = 'meeting'. Match both spellings so
+  // the extractor keeps working on migrated (v2) brains, not just v1 ones.
   const meetings = await engine.executeRaw<MeetingRow>(
     `SELECT slug, source_id, title, effective_date, updated_at,
             compiled_truth, COALESCE(timeline, '') AS timeline
        FROM pages
-      WHERE type = 'meeting'
+      WHERE (type = 'meeting' OR frontmatter ->> 'legacy_type' = 'meeting')
         AND deleted_at IS NULL
         ${sourceFilter}
       ORDER BY effective_date DESC NULLS LAST, slug`,
@@ -94,7 +97,7 @@ export async function extractTimelineFromMeetings(
        JOIN pages pf ON pf.id = l.from_page_id
        JOIN pages pt ON pt.id = l.to_page_id
       WHERE l.link_type = 'attended'
-        AND pf.type = 'meeting'
+        AND (pf.type = 'meeting' OR pf.frontmatter ->> 'legacy_type' = 'meeting')
         AND pf.deleted_at IS NULL
         AND pt.deleted_at IS NULL`,
   );

src/core/operations.ts

@@ -4562,7 +4562,10 @@ 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'];
+    // #1726: derive from the locator's registry instead of a hand-copied
+    // subset (which had frozen at 2 of 7 bundled packs).
+    const { BUNDLED_PACKS } = await import('./schema-pack/load-active.ts');
+    const bundled = [...BUNDLED_PACKS];
     const installedDir = gbrainPath('schema-packs');
     const installed: string[] = [];
     if (existsSync(installedDir)) {

src/core/schema-pack/base/gbrain-base-v2.yaml

@@ -41,6 +41,12 @@ migration_from:
   pack: gbrain-base
   version: "1.x"
 
+# #2117 — cycle-phase participation. `phases:` is additive and pack-gated;
+# without this key extract_atoms is silently off on v2 brains even though
+# onboard + doctor recommend it (v2 declares the `atom` type it writes).
+phases:
+  - extract_atoms
+
 page_types:
   - name: person
     primitive: entity
@@ -319,6 +325,10 @@ page_types:
     extractable: false
     expert_routing: false
 
+# #2117 — inference rules ported from gbrain-base v1 so extract-ner keeps
+# working on v2 brains (it hard-skips with pack_unavailable when no
+# link_type declares an inference.regex). Same ReDoS-guarded sketch
+# regexes v1 ships; production matchers in link-extraction.ts still apply.
 link_types:
   - name: partner_of
     inverse: partner_of
@@ -328,14 +338,24 @@ link_types:
   - name: discusses
   - name: founded
     inverse: founded_by
+    inference:
+      regex: \b(founded|founder of|co-?founded|started)\b
   - name: works_at
     inverse: employs
+    inference:
+      regex: \b(works? at|employed by|works? for|joined|hired by|ceo of|cto of|cmo of)\b
   - name: invested_in
     inverse: investor_of
+    inference:
+      regex: \b(invested in|backed|seeded|funded|wrote a check)\b
   - name: sourced_from
   - name: derived_from
   - name: supersedes
   - name: redirects_to
+  # NOTE: v1's `attended` inference is page_type-bound to `meeting`, which
+  # v2 does not declare (lint: link_types_undeclared_page_type). Meeting
+  # pages retyped by unify-types are matched via frontmatter.legacy_type
+  # in extract-timeline-from-meetings (#2109) instead.
   - name: attended
     inverse: attended_by
   - name: authored

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

@@ -91,29 +91,33 @@ export function _resetPackLocatorForTests(): void {
  * Returns null when the pack is not found. Callers handle null by
  * throwing UnknownPackError with a paste-ready install hint.
  */
+// 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.
+//
+// #1726: exported so reporting surfaces (list_schema_packs) derive from the
+// same list the locator resolves — no more hand-copied 2-of-7 subsets.
+export const BUNDLED_PACKS: 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',
+];
+
 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 (BUNDLED_PACKS.includes(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));

test/calibration-profile.test.ts

@@ -32,7 +32,7 @@ interface CapturedSql {
   params: unknown[];
 }
 
-function buildMockEngine(opts: { scorecard: TakesScorecard }): {
+function buildMockEngine(opts: { scorecard: TakesScorecard; config?: Record<string, string> }): {
   engine: BrainEngine;
   captured: CapturedSql[];
 } {
@@ -42,6 +42,9 @@ function buildMockEngine(opts: { scorecard: TakesScorecard }): {
     async getScorecard() {
       return opts.scorecard;
     },
+    async getConfig(key: string) {
+      return opts.config?.[key] ?? null;
+    },
     async executeRaw<T>(sql: string, params?: unknown[]): Promise<T[]> {
       captured.push({ sql, params: params ?? [] });
       return [];
@@ -241,6 +244,36 @@ describe('runPhaseCalibrationProfile — phase integration', () => {
     expect(insert!.params[11]).toEqual(['over-confident-geography']); // active_bias_tags
   });
 
+  test('#1726: calibration.user_holder config drives the holder when no explicit opt', async () => {
+    const { engine, captured } = buildMockEngine({
+      scorecard: ENOUGH_RESOLVED_SCORECARD,
+      config: { 'calibration.user_holder': 'alice-example' },
+    });
+    await runPhaseCalibrationProfile(buildCtx(engine), {
+      patternsGenerator: async () => ['You call early-stage tactics well — 8 of 10 held up.'],
+      biasTagsGenerator: async () => [],
+      voiceGateJudge: passJudge,
+    });
+    const insert = captured.find(c => c.sql.includes('INSERT INTO calibration_profiles'));
+    expect(insert).toBeDefined();
+    expect(insert!.params[1]).toBe('alice-example'); // holder from config
+  });
+
+  test('#1726: explicit holder opt wins over calibration.user_holder config', async () => {
+    const { engine, captured } = buildMockEngine({
+      scorecard: ENOUGH_RESOLVED_SCORECARD,
+      config: { 'calibration.user_holder': 'alice-example' },
+    });
+    await runPhaseCalibrationProfile(buildCtx(engine), {
+      holder: 'charlie-example',
+      patternsGenerator: async () => ['You call early-stage tactics well — 8 of 10 held up.'],
+      biasTagsGenerator: async () => [],
+      voiceGateJudge: passJudge,
+    });
+    const insert = captured.find(c => c.sql.includes('INSERT INTO calibration_profiles'));
+    expect(insert!.params[1]).toBe('charlie-example');
+  });
+
   test('default model is a provider-prefixed id, persisted to model_id (#2451)', async () => {
     const { engine, captured } = buildMockEngine({ scorecard: ENOUGH_RESOLVED_SCORECARD });
     const patternsGenerator: PatternStatementsGenerator = async () => [

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/extract-timeline-legacy-type.test.ts

@@ -0,0 +1,106 @@
+// #2109 — gbrain-base-v2's unify-types retypes meeting pages to `note`
+// with frontmatter.legacy_type='meeting'. extract-timeline-from-meetings
+// used to hardcode type='meeting' and silently scan 0 meetings on migrated
+// brains. These tests fail without the legacy_type fallback in both SQL
+// sites (meeting walk + attended-edge join).
+
+import { afterAll, beforeAll, beforeEach, describe, expect, it } from 'bun:test';
+import { PGLiteEngine } from '../src/core/pglite-engine.ts';
+import { resetPgliteState } from './helpers/reset-pglite.ts';
+import { extractTimelineFromMeetings } from '../src/core/extract-timeline-from-meetings.ts';
+
+let engine: PGLiteEngine;
+
+beforeAll(async () => {
+  engine = new PGLiteEngine();
+  await engine.connect({});
+  await engine.initSchema();
+});
+
+afterAll(async () => {
+  await engine.disconnect();
+});
+
+beforeEach(async () => {
+  await resetPgliteState(engine);
+});
+
+async function insertPage(opts: {
+  slug: string;
+  type: string;
+  title: string;
+  effectiveDate?: string;
+  legacyType?: string;
+}): Promise<number> {
+  const frontmatterLiteral = opts.legacyType
+    ? `'{"legacy_type": "${opts.legacyType}"}'::jsonb`
+    : `'{}'::jsonb`;
+  const rows = await engine.executeRaw<{ id: number }>(
+    `INSERT INTO pages (slug, source_id, type, title, compiled_truth, timeline, effective_date, frontmatter)
+     VALUES ($1, 'default', $2, $3, '', '', $4, ${frontmatterLiteral})
+     RETURNING id`,
+    [opts.slug, opts.type, opts.title, opts.effectiveDate ?? null],
+  );
+  return rows[0]!.id;
+}
+
+describe('extractTimelineFromMeetings — legacy_type fallback (#2109)', () => {
+  it('scans pages retyped to note with legacy_type=meeting and walks their attended edges', async () => {
+    const meetingId = await insertPage({
+      slug: 'meetings/2026-01-05',
+      type: 'note', // post-unify-types shape on a gbrain-base-v2 brain
+      legacyType: 'meeting',
+      title: 'Weekly sync',
+      effectiveDate: '2026-01-05',
+    });
+    const personId = await insertPage({
+      slug: 'people/alice-example',
+      type: 'person',
+      title: 'Alice Example',
+    });
+    await engine.executeRaw(
+      `INSERT INTO links (from_page_id, to_page_id, link_type) VALUES ($1, $2, 'attended')`,
+      [meetingId, personId],
+    );
+
+    const result = await extractTimelineFromMeetings(engine);
+    expect(result.meetings_scanned).toBe(1);
+    expect(result.entries_created).toBe(1);
+    expect(result.entities_touched).toBe(1);
+    expect(result.batch_errors).toBe(0);
+  });
+
+  it('still scans pre-unify pages with type=meeting (v1 behavior preserved)', async () => {
+    const meetingId = await insertPage({
+      slug: 'meetings/2026-02-01',
+      type: 'meeting',
+      title: 'Board prep',
+      effectiveDate: '2026-02-01',
+    });
+    const personId = await insertPage({
+      slug: 'people/charlie-example',
+      type: 'person',
+      title: 'Charlie Example',
+    });
+    await engine.executeRaw(
+      `INSERT INTO links (from_page_id, to_page_id, link_type) VALUES ($1, $2, 'attended')`,
+      [meetingId, personId],
+    );
+
+    const result = await extractTimelineFromMeetings(engine);
+    expect(result.meetings_scanned).toBe(1);
+    expect(result.entries_created).toBe(1);
+  });
+
+  it('does not scan unrelated note pages without legacy_type=meeting', async () => {
+    await insertPage({
+      slug: 'notes/random',
+      type: 'note',
+      title: 'Random note',
+      effectiveDate: '2026-03-01',
+    });
+    const result = await extractTimelineFromMeetings(engine);
+    expect(result.meetings_scanned).toBe(0);
+    expect(result.entries_created).toBe(0);
+  });
+});

test/operations-schema-pack.test.ts

@@ -152,6 +152,19 @@ describe('list_schema_packs', () => {
       expect(result.installed).toContain('mine');
     });
   });
+
+  it('reports the full bundled registry, not a hand-copied subset (#1726)', async () => {
+    await withEnv({ GBRAIN_HOME: tmpDir }, async () => {
+      const { BUNDLED_PACKS } = await import('../src/core/schema-pack/load-active.ts');
+      const result = await operationsByName.list_schema_packs!.handler(ctxOf(), {}) as { bundled: string[] };
+      expect(result.bundled.slice().sort()).toEqual([...BUNDLED_PACKS].sort());
+      // The lens packs that declare extract_atoms/synthesize_concepts phases
+      // were the ones dropped by the frozen 2-pack literal.
+      for (const name of ['gbrain-creator', 'gbrain-everything', 'gbrain-base-v2']) {
+        expect(result.bundled).toContain(name);
+      }
+    });
+  });
 });
 
 // ── schema_stats ───────────────────────────────────────────────────────

test/schema-pack-base-v2-capabilities.test.ts

@@ -0,0 +1,40 @@
+// #2117 — gbrain-base-v2 shipped with no `phases:` declaration and zero
+// link_types[].inference regexes, so extract_atoms was silently pack-gated
+// off and extract-ner returned pack_unavailable on the bundled default pack.
+// These assertions fail against the pre-fix yaml.
+
+import { describe, expect, it } from 'bun:test';
+import { join } from 'node:path';
+import { loadPackFromFile } from '../src/core/schema-pack/loader.ts';
+import { linkTypesUndeclared } from '../src/core/schema-pack/lint-rules.ts';
+
+const V2_PATH = join(import.meta.dir, '..', 'src', 'core', 'schema-pack', 'base', 'gbrain-base-v2.yaml');
+
+describe('gbrain-base-v2 capability parity (#2117)', () => {
+  const manifest = loadPackFromFile(V2_PATH);
+
+  it('declares the extract_atoms cycle phase', () => {
+    expect(manifest.phases ?? []).toContain('extract_atoms');
+  });
+
+  it('ships at least one link_type inference regex so extract-ner is not pack_unavailable', () => {
+    // Mirrors the extract-ner hasRegex predicate exactly.
+    const hasRegex = manifest.link_types.some(
+      (lt) => lt.inference && typeof lt.inference === 'object' && 'regex' in lt.inference,
+    );
+    expect(hasRegex).toBe(true);
+  });
+
+  it('ports the v1 inference verbs it declares link types for', () => {
+    const withRegex = manifest.link_types
+      .filter((lt) => lt.inference?.regex)
+      .map((lt) => lt.name)
+      .sort();
+    expect(withRegex).toEqual(['founded', 'invested_in', 'works_at']);
+  });
+
+  it('inference rules pass the undeclared-page-type lint (no meeting-bound inference)', async () => {
+    const issues = await linkTypesUndeclared(manifest);
+    expect(issues).toEqual([]);
+  });
+});