fix(takes): kill propose_takes rescan loop, keep every claim, and route cycle/brainstorm models through config (#2804 #2805)

Takeover of #2804 and #2805 (stacked), rebased onto current master.

Rescan loop + dropped claims (#2804):
- Zero-claim scans now write a status='empty' sentinel row so the
  (source_id, page_slug, content_hash, prompt_version) cache hits on
  every subsequent cycle instead of re-spending the extractor LLM call
  on the same unchanged page forever.
- The idempotency index gains md5(claim_text): multi-claim pages keep
  every claim (the 4-column unique index silently dropped claims 2..N
  via ON CONFLICT DO NOTHING). proposals_inserted now counts rows that
  actually landed (RETURNING id), not insert attempts.
- Migration renumbered 123 -> 125 (master shipped v123
  configurable_fts_language and v124 after the PR was cut; the
  duplicate v123 would never have run under the version > current
  runner). Schema parity across schema.sql, pglite-schema.ts,
  schema-embedded.ts.

Model-tier honoring (#2805), reworked for current master:
- propose_takes, grade_takes, calibration_profile resolve their model
  through resolveModel(models.<phase> > models.default > env >
  getChatModel()) — per-phase config keys are now honored while the
  gateway chat model (already tier-resolved by
  reconfigureGatewayWithEngine) stays the default, preserving master's
  #2451 semantics (provider-prefixed stored ids, nested prefixes like
  openrouter:... intact) and the #2997 opts.model ?? getChatModel()
  idiom. The PR's original bare-tail-everywhere approach was dropped
  where it conflicted with #2451; grade_takes keeps the bare tail ONLY
  for its cache key / stored judge_model_id (continuity with historical
  rows), while the judge call itself gets the full resolved string —
  fixing the live label-vs-actual mismatch (call rode chat_model,
  telemetry recorded a hardcoded claude-sonnet-4-6).
- brainstorm resolves via models.brainstorm > tier chain (was
  hardcoded anthropic:claude-sonnet-4-6).
- gbrain models lists the four new per-task keys; output caps and
  context-window entries added for newer Claude models.

Tests: test/propose-takes-rescan.test.ts (new, hermetic PGLite);
config-key coverage in propose-takes/grade-takes tests; existing #2451
and gateway-chat-model tests pass unchanged.

Co-authored-by: p3ob7o <p3ob7o@users.noreply.github.com>
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

src/commands/import.ts

@@ -170,14 +170,10 @@ export async function runImport(
   // v0.22.13 (PR #490 Q2): shared parseWorkers helper rejects bad input
   // (--workers 0, -3, "foo") with a loud error instead of silently falling
   // through to 1. Mirrors sync.ts's flag handling.
-  const { parseWorkers, autoConcurrency } = await import('../core/sync-concurrency.ts');
-  // #1207: undefined (no --workers flag) defers to autoConcurrency below —
-  // the shared sync/import policy (PGLite → 1, >100 files → 4) — instead of
-  // hardcoding serial. Large Postgres imports stop paying one embedding
-  // round-trip per file in sequence.
-  let workerCount: number | undefined;
+  const { parseWorkers } = await import('../core/sync-concurrency.ts');
+  let workerCount: number;
   try {
-    workerCount = parseWorkers(workersArg ?? undefined);
+    workerCount = parseWorkers(workersArg ?? undefined) ?? 1;
   } catch (e) {
     console.error(e instanceof Error ? e.message : String(e));
     process.exit(1);
@@ -256,9 +252,8 @@ export async function runImport(
   }
   const files = resumeFilter(allFiles, dir, completed);
 
-  // Determine actual worker count. Explicit --workers wins; otherwise the
-  // shared autoConcurrency policy decides from engine kind + file count.
-  const actualWorkers = autoConcurrency(engine, files.length, workerCount);
+  // Determine actual worker count
+  const actualWorkers = workerCount > 1 ? workerCount : 1;
   if (actualWorkers > 1) {
     console.log(`Using ${actualWorkers} parallel workers`);
   }

src/commands/models.ts

@@ -50,6 +50,10 @@ const PER_TASK_KEYS: Array<{ key: string; tier: ModelTier; description: string }
   { key: 'models.eval.contradictions_judge', tier: 'utility',  description: 'Contradiction probe judge (v0.34 temporal-aware)' },
   { key: 'models.expansion',                tier: 'utility',   description: 'Query expansion for hybrid search' },
   { key: 'models.chat',                     tier: 'reasoning', description: 'Default `gateway.chat()` model' },
+  { key: 'models.propose_takes',            tier: 'reasoning', description: 'propose_takes claim extractor' },
+  { key: 'models.grade_takes',              tier: 'reasoning', description: 'grade_takes verdict judge' },
+  { key: 'models.calibration_profile',      tier: 'reasoning', description: 'Calibration profile generator' },
+  { key: 'models.brainstorm',               tier: 'reasoning', description: '`gbrain brainstorm` orchestrator' },
 ];
 
 interface ModelEntry {

src/core/ai/gateway.ts

@@ -1513,21 +1513,12 @@ export async function embed(texts: string[], opts?: EmbedOpts): Promise<Float32A
 
   const embedding = recipe.touchpoints?.embedding;
   const maxBatchTokens = embedding?.max_batch_tokens;
-  const maxBatchCount = embedding?.max_batch_count;
   const charsPerToken = embedding?.chars_per_token ?? DEFAULT_CHARS_PER_TOKEN;
 
-  // Pre-split is gated on max_batch_tokens / max_batch_count. Recipes with
-  // neither (e.g. OpenAI) ride the fast path: one embedMany call, no
-  // recursion safety net.
-  const batches = (maxBatchTokens || maxBatchCount)
-    ? splitByTokenBudget(
-        truncated,
-        maxBatchTokens
-          ? Math.floor(maxBatchTokens * effectiveSafetyFactor(recipe))
-          : Number.MAX_SAFE_INTEGER,
-        charsPerToken,
-        maxBatchCount,
-      )
+  // Pre-split is gated on max_batch_tokens. Recipes without it (e.g. OpenAI)
+  // ride the fast path: one embedMany call, no recursion safety net.
+  const batches = maxBatchTokens
+    ? splitByTokenBudget(truncated, Math.floor(maxBatchTokens * effectiveSafetyFactor(recipe)), charsPerToken)
     : [truncated];
 
   const allEmbeddings: Float32Array[] = [];
@@ -1577,9 +1568,6 @@ export async function embed(texts: string[], opts?: EmbedOpts): Promise<Float32A
  *   responsible for applying any safety-factor shrink before passing in.
  * @param charsPerToken - Provider-specific character density. Defaults to
  *   `DEFAULT_CHARS_PER_TOKEN` (4) when omitted, matching OpenAI tiktoken.
- * @param maxBatchCount - #1199: optional cap on INPUTS per sub-batch, for
- *   providers that reject batches by count (DashScope: 10). When omitted,
- *   only the token budget governs.
  *
  * @internal exported for tests; not part of the public gateway API.
  */
@@ -1587,17 +1575,15 @@ export function splitByTokenBudget(
   texts: string[],
   budgetTokens: number,
   charsPerToken: number = DEFAULT_CHARS_PER_TOKEN,
-  maxBatchCount?: number,
 ): string[][] {
   const ratio = charsPerToken > 0 ? charsPerToken : DEFAULT_CHARS_PER_TOKEN;
-  const maxCount = maxBatchCount !== undefined && maxBatchCount > 0 ? maxBatchCount : Infinity;
   const batches: string[][] = [];
   let current: string[] = [];
   let currentTokens = 0;
 
   for (const text of texts) {
     const estTokens = Math.ceil(text.length / ratio);
-    if (current.length > 0 && (currentTokens + estTokens > budgetTokens || current.length >= maxCount)) {
+    if (current.length > 0 && currentTokens + estTokens > budgetTokens) {
       batches.push(current);
       current = [];
       currentTokens = 0;
@@ -1623,11 +1609,7 @@ export function isTokenLimitError(err: unknown): boolean {
     /token.*limit.*exceeded/i.test(msg) ||
     // OpenAI embeddings: "Invalid 'input': maximum request size is 300000 tokens per request."
     /maximum request size.*tokens/i.test(msg) ||
-    /max.*tokens.*per.*request/i.test(msg) ||
-    // DashScope: "batch size is invalid, it should not be larger than 10." (#1199)
-    // Count-cap error, but recursive halving shrinks count too, so the same
-    // safety net converges.
-    /batch size is invalid/i.test(msg)
+    /max.*tokens.*per.*request/i.test(msg)
   );
 }
 

src/core/ai/recipes/dashscope.ts

@@ -31,10 +31,6 @@ export const dashscope: Recipe = {
       // path. Conservative declaration so the gateway pre-splits before
       // hitting whatever undocumented server-side limit exists.
       max_batch_tokens: 8192,
-      // #1199: DashScope hard-caps embeddings at 10 inputs per request
-      // ("batch size is invalid, it should not be larger than 10"). The
-      // token budget alone admits far more than 10 short chunks per batch.
-      max_batch_count: 10,
       // text-embedding-v3 mixes English + CJK heavily; the tokenizer is
       // closer to Voyage density than OpenAI tiktoken for CJK-dominant
       // content. Conservative chars_per_token=2 leaves headroom.

src/core/ai/recipes/google.ts

@@ -16,15 +16,6 @@ export const google: Recipe = {
       dims_options: [768, 1536, 3072],
       cost_per_1m_tokens_usd: 0.15,
       price_last_verified: '2026-04-20',
-      // #970: Gemini's documented limits are per-INPUT (2048 tokens,
-      // silently truncated beyond) and per-REQUEST count (batchEmbedContents
-      // caps at 100 inputs). There is no separate per-request token cap, so
-      // the token budget is derived: 100 inputs × 2048 tokens. The count cap
-      // binds first for typical chunk sizes. Do NOT copy the 2048 per-input
-      // limit into max_batch_tokens — that would over-split 50×.
-      max_batch_tokens: 204_800,
-      chars_per_token: 4,
-      max_batch_count: 100,
     },
     expansion: {
       models: ['gemini-2.0-flash', 'gemini-2.0-flash-lite'],

src/core/ai/recipes/index.ts

@@ -58,8 +58,5 @@ export function getRecipe(id: string): Recipe | undefined {
 }
 
 export function listRecipes(): Recipe[] {
-  // Read the map (not ALL) so there is one source of truth — getRecipe,
-  // model-resolver, and listRecipes all see the same registry, and tests
-  // can inject a synthetic recipe via RECIPES to exercise registry walks.
-  return [...RECIPES.values()];
+  return [...ALL];
 }

src/core/ai/types.ts

@@ -46,16 +46,6 @@ export interface EmbeddingTouchpoint {
    * Only consulted when `max_batch_tokens` is also set.
    */
   chars_per_token?: number;
-  /**
-   * #1199: maximum number of INPUTS per embedding request, for providers
-   * that hard-cap batch size by count rather than (or in addition to)
-   * tokens — DashScope text-embedding-v3 rejects batches > 10 with
-   * `InvalidParameter`, Gemini batchEmbedContents caps at 100 requests.
-   * When set, the gateway's pre-split flushes a sub-batch at this count
-   * even if the token budget still has room. Independent of
-   * `max_batch_tokens`; either alone triggers the pre-split.
-   */
-  max_batch_count?: number;
   /**
    * Budget-utilization ceiling in (0, 1]. The gateway pre-splits at
    * `safety_factor × max_batch_tokens` to leave headroom for tokenizer

src/core/brainstorm/judges.ts

@@ -61,7 +61,10 @@ export const MAX_OUTPUT_TOKENS_CEIL = 32_000;
  * (with a readable error) instead of the provider's opaque HTTP 400.
  */
 export const ANTHROPIC_OUTPUT_CAPS: Record<string, number> = {
+  'claude-fable-5': 64_000,
+  'claude-opus-4-8': 32_000,
   'claude-opus-4-7': 32_000,
+  'claude-sonnet-5': 64_000,
   'claude-sonnet-4-6': 64_000,
   'claude-haiku-4-5': 64_000,
   'claude-haiku-4-5-20251001': 64_000,

src/core/brainstorm/orchestrator.ts

@@ -32,6 +32,7 @@
  */
 
 import type { BrainEngine } from '../engine.ts';
+import { resolveModel } from '../model-config.ts';
 import { chat as defaultChat, embedQuery, type ChatResult, type ChatOpts } from '../ai/gateway.ts';
 import { hybridSearch, hybridSearchCached } from '../search/hybrid.ts';
 import { fetchFar, type CloseRef, type FarPage } from './domain-bank.ts';
@@ -538,7 +539,14 @@ async function _runBrainstormInner(
   const embedFn = opts.embedQueryFn ?? embedQuery;
 
   // ---- Phase 0: cost preview + TTY grace ----
-  const modelStr = opts.modelOverride ?? 'anthropic:claude-sonnet-4-6';
+  // Tier-resolved (mirrors the cycle phases): honors models.brainstorm >
+  // models.default > models.tier.reasoning; the fallback keeps stock
+  // behavior identical (reasoning tier default IS claude-sonnet-4-6).
+  const modelStr = opts.modelOverride ?? await resolveModel(engine, {
+    configKey: 'models.brainstorm',
+    tier: 'reasoning',
+    fallback: 'anthropic:claude-sonnet-4-6',
+  });
   const { aborted, estimate } = await previewCostAndWait({
     profile,
     model: modelStr,

src/core/cycle/calibration-profile.ts

@@ -26,8 +26,8 @@
  */
 
 import { BaseCyclePhase, type ScopedReadOpts, type BasePhaseOpts } from './base-phase.ts';
-import { chat as gatewayChat } from '../ai/gateway.ts';
-import { TIER_DEFAULTS } from '../model-config.ts';
+import { chat as gatewayChat, getChatModel } from '../ai/gateway.ts';
+import { resolveModel } from '../model-config.ts';
 import { gateVoice, type VoiceGateGenerator, type VoiceGateJudge } from '../calibration/voice-gate.ts';
 import { patternStatementTemplate, type PatternStatementSlots } from '../calibration/templates.ts';
 // v0.41 T10 — domain widening. The aggregator module resolves the active
@@ -229,7 +229,16 @@ class CalibrationProfilePhase extends BaseCyclePhase {
   ): Promise<{ summary: string; details: Record<string, unknown>; status?: PhaseStatus }> {
     const holder = opts.holder ?? 'garry';
     const promptVersion = opts.promptVersion ?? CALIBRATION_PROFILE_PROMPT_VERSION;
-    const modelId = opts.model ?? TIER_DEFAULTS.reasoning;
+    // Resolved once (see propose-takes.ts for the chain): models.calibration_profile
+    // > models.default > env > the gateway's chat model (itself resolved
+    // through models.chat + the reasoning tier). Provider-prefixed per #2451
+    // — a bare id would make gateway.chat() throw "missing a provider
+    // prefix". Drives the generator's chat call, the budget label, and the
+    // persisted model_id, so the three can never disagree.
+    const modelId = opts.model ?? await resolveModel(engine, {
+      configKey: 'models.calibration_profile',
+      fallback: getChatModel(),
+    });
     const gradeCompletion = opts.gradeCompletion ?? 1.0;
     const patternsGenerator = opts.patternsGenerator ?? defaultPatternsGenerator;
     const biasTagsGenerator = opts.biasTagsGenerator ?? defaultBiasTagsGenerator;
@@ -265,6 +274,7 @@ class CalibrationProfilePhase extends BaseCyclePhase {
         scorecard,
         holder,
         attempt,
+        modelHint: modelId,
         ...(feedback !== undefined ? { feedback } : {}),
       });
       return lines.join('\n');

src/core/cycle/grade-takes.ts

@@ -36,7 +36,9 @@
 
 import { createHash } from 'node:crypto';
 import { BaseCyclePhase, type ScopedReadOpts, type BasePhaseOpts } from './base-phase.ts';
-import { chat as gatewayChat } from '../ai/gateway.ts';
+import { chat as gatewayChat, getChatModel } from '../ai/gateway.ts';
+import { resolveModel } from '../model-config.ts';
+import { splitProviderModelId } from '../model-id.ts';
 import { GBrainError } from '../types.ts';
 import type { OperationContext } from '../operations.ts';
 import type { BrainEngine, Take, TakeResolution } from '../engine.ts';
@@ -395,7 +397,24 @@ class GradeTakesPhase extends BaseCyclePhase {
     const autoResolve = opts.autoResolve ?? false; // D17 default OFF
     const autoResolveThreshold = opts.autoResolveThreshold ?? 0.95; // D12 conservative
     const resolvedByLabel = opts.resolvedByLabel ?? 'gbrain:grade_takes';
-    const judgeModelId = opts.model ?? 'claude-sonnet-4-6';
+    // Resolve the judge model ONCE (see propose-takes.ts for the chain —
+    // same label-vs-actual split fixed here: the judge call rode the
+    // gateway's chat_model while the grade cache key, evidence signature,
+    // and budget label recorded a hardcoded 4.6).
+    // NOTE: changing the resolved judge model invalidates the grade cache
+    // (judge_model_id is part of its key) — a one-time, budget-capped
+    // re-grade wave that is CORRECT, since the actual judge did change.
+    const judgeModelFull = opts.model ?? await resolveModel(engine, {
+      configKey: 'models.grade_takes',
+      fallback: getChatModel(),
+    });
+    // Bare tail for cache keys / evidence signatures / stored ids — the
+    // grade cache has always been keyed on bare ids; the gateway default
+    // resolves provider-prefixed, and normalizing preserves cache continuity
+    // on stock installs (no spurious re-judge wave from a prefix change). A
+    // genuinely different configured judge still invalidates, which is
+    // correct. The FULL string drives the actual judge call.
+    const judgeModelId = splitProviderModelId(judgeModelFull).model || judgeModelFull;
 
     const useEnsemble = opts.useEnsemble ?? false;
     const ensembleThreshold = opts.ensembleThreshold ?? 0.85;
@@ -468,7 +487,7 @@ class GradeTakesPhase extends BaseCyclePhase {
       // Call the single-model judge. Errors on a single take log warning + continue.
       let verdict: JudgeVerdict;
       try {
-        verdict = await judge({ take, evidence, modelHint: opts.model });
+        verdict = await judge({ take, evidence, modelHint: judgeModelFull });
       } catch (err) {
         const msg = err instanceof Error ? err.message : String(err);
         result.warnings.push(`judge failed on take ${take.id}: ${msg}`);

src/core/cycle/propose-takes.ts

@@ -5,11 +5,16 @@
  * a tuned LLM extractor, writes the extracted gradeable claims to the
  * `take_proposals` queue. User accepts/rejects via `gbrain takes propose`.
  *
- * Idempotency contract (D17 schema spec):
- *   The unique index on (source_id, page_slug, content_hash, prompt_version)
- *   means an unchanged page never re-spends LLM tokens. Bumping
- *   PROPOSE_TAKES_PROMPT_VERSION cleanly invalidates the cache so a tuned
- *   prompt re-runs proposals on every page.
+ * Idempotency contract (D17 schema spec; per-claim rows since migration v125):
+ *   Every scan of a (source_id, page_slug, content_hash, prompt_version)
+ *   tuple leaves at least one row — one per extracted claim, or a single
+ *   status='empty' sentinel when extraction yields nothing — so an unchanged
+ *   page never re-spends LLM tokens. Pre-v125 only proposal rows were
+ *   written: a zero-claim page never entered the cache and was re-extracted
+ *   on EVERY cycle (observed live: ~60 such pages × every cycle ≈ 1,400
+ *   wasted extractor calls / ~$15 per day — ~90% of total autopilot spend).
+ *   Bumping PROPOSE_TAKES_PROMPT_VERSION cleanly invalidates the cache so a
+ *   tuned prompt re-runs proposals on every page.
  *
  * F2 fence dedup:
  *   The phase reads the page's existing `<!-- gbrain:takes:begin -->` fence
@@ -40,6 +45,7 @@
 import { randomUUID, createHash } from 'node:crypto';
 import { BaseCyclePhase, type ScopedReadOpts, type BasePhaseOpts } from './base-phase.ts';
 import { chat as gatewayChat, getChatModel } from '../ai/gateway.ts';
+import { resolveModel } from '../model-config.ts';
 import { writeReceipt } from '../extract/receipt-writer.ts';
 import { upsertExtractRollup } from '../extract/rollup-writer.ts';
 import { GBrainError } from '../types.ts';
@@ -307,6 +313,18 @@ class ProposeTakesPhase extends BaseCyclePhase {
     const promptVersion = opts.promptVersion ?? PROPOSE_TAKES_PROMPT_VERSION;
     const pageLimit = opts.pageLimit ?? 100;
     const skipPagesWithFence = opts.skipPagesWithFence ?? false;
+    // Resolve the extractor model ONCE: models.propose_takes >
+    // models.default > GBRAIN_MODEL env > the gateway's chat model (which
+    // reconfigureGatewayWithEngine already resolved through models.chat +
+    // the reasoning tier). One resolved provider-prefixed string drives the
+    // actual chat call, the budget estimate, AND the stored model_id — so
+    // the recorded model can never disagree with the model that ran (#2451
+    // convention: stored ids are provider-prefixed, nested prefixes like
+    // openrouter:anthropic/... stay intact).
+    const extractorModelId = opts.model ?? await resolveModel(engine, {
+      configKey: 'models.propose_takes',
+      fallback: getChatModel(),
+    });
     const proposalRunId = `propose-${new Date().toISOString().slice(0, 19).replace(/[-:T]/g, '')}-${randomUUID().slice(0, 8)}`;
 
     const result: ProposeTakesResult = {
@@ -330,8 +348,6 @@ class ProposeTakesPhase extends BaseCyclePhase {
       opts.reporter.start('propose_takes.pages' as never, pages.length);
     }
 
-    const modelId = opts.model ?? getChatModel();
-
     for (const page of pages) {
       result.pages_scanned += 1;
       this.tick(opts);
@@ -361,7 +377,7 @@ class ProposeTakesPhase extends BaseCyclePhase {
 
       // Budget pre-check before the LLM call. Estimate: ~1500 input tokens + 500 output.
       const budget = this.checkBudget({
-        modelId,
+        modelId: extractorModelId,
         estimatedInputTokens: 1500,
         maxOutputTokens: 500,
       });
@@ -380,7 +396,7 @@ class ProposeTakesPhase extends BaseCyclePhase {
           pagePath: page.slug,
           pageBody: body,
           existingTakes,
-          modelHint: opts.model,
+          modelHint: extractorModelId,
         });
       } catch (err) {
         const msg = err instanceof Error ? err.message : String(err);
@@ -388,16 +404,42 @@ class ProposeTakesPhase extends BaseCyclePhase {
         continue;
       }
 
-      // Write proposals to take_proposals. Each row is a separate INSERT
-      // because the composite idempotency key is on the per-page tuple — a
-      // bulk UPSERT would collapse a same-page-multi-claim run into one row.
-      for (const p of proposals) {
+      // Zero-claim scans MUST still enter the idempotency cache. Pre-v125
+      // only proposal rows were written, so a page whose extraction yielded
+      // no gradeable claims never got a row for its (page, content_hash) —
+      // the cache check above missed on every subsequent cycle and the LLM
+      // call was re-spent on the same unchanged page, forever. The sentinel
+      // row (status='empty', empty claim_text) is invisible to the review
+      // queue (pending_idx is partial on status='pending'); it exists only
+      // so the cache check hits.
+      if (proposals.length === 0) {
         await engine.executeRaw(
+          `INSERT INTO take_proposals
+             (source_id, page_slug, content_hash, prompt_version, proposal_run_id,
+              status, claim_text, kind, holder, weight, domain, dedup_against_fence_rows, model_id)
+           VALUES ($1, $2, $3, $4, $5, 'empty', '', 'none', 'brain', 0, NULL, NULL, $6)
+           ON CONFLICT (source_id, page_slug, content_hash, prompt_version, md5(claim_text)) DO NOTHING`,
+          [sourceId, page.slug, ch, promptVersion, proposalRunId, extractorModelId],
+        );
+        continue;
+      }
+
+      // Write proposals to take_proposals, one row per claim. The v125
+      // idempotency index includes md5(claim_text), so a same-page
+      // multi-claim run keeps EVERY claim — the pre-v125 four-column unique
+      // index made claims 2..N conflict with claim 1 and ON CONFLICT DO
+      // NOTHING silently dropped them (the review queue only ever saw the
+      // first claim of each page version). RETURNING id keeps
+      // proposals_inserted honest: it counts rows that actually landed,
+      // not insert attempts.
+      for (const p of proposals) {
+        const landed = await engine.executeRaw<{ id: number }>(
           `INSERT INTO take_proposals
              (source_id, page_slug, content_hash, prompt_version, proposal_run_id,
               claim_text, kind, holder, weight, domain, dedup_against_fence_rows, model_id)
            VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10, $11, $12)
-           ON CONFLICT (source_id, page_slug, content_hash, prompt_version) DO NOTHING`,
+           ON CONFLICT (source_id, page_slug, content_hash, prompt_version, md5(claim_text)) DO NOTHING
+           RETURNING id`,
           [
             sourceId,
             page.slug,
@@ -410,10 +452,10 @@ class ProposeTakesPhase extends BaseCyclePhase {
             p.weight,
             p.domain ?? null,
             JSON.stringify(existingTakes),
-            modelId,
+            extractorModelId,
           ],
         );
-        result.proposals_inserted += 1;
+        if (landed.length > 0) result.proposals_inserted += 1;
       }
     }
 

src/core/cycle/synthesize.ts

@@ -58,8 +58,11 @@ const SUMMARY_SLUG_RE = /^[a-z0-9][a-z0-9\-]*(\/[a-z0-9][a-z0-9\-]*)*$/;
  * resolver returns for known Anthropic aliases.
  */
 const MODEL_CONTEXT_TOKENS: Record<string, number> = {
+  'claude-fable-5': 1_000_000,
+  'claude-opus-4-8': 1_000_000,
   'claude-opus-4-7': 1_000_000,
   'claude-opus-4-6': 1_000_000,
+  'claude-sonnet-5': 1_000_000,
   'claude-sonnet-4-6': 200_000,
   'claude-sonnet-4-5': 200_000,
   'claude-haiku-4-5-20251001': 200_000,

src/core/embedding.ts

@@ -79,34 +79,15 @@ export interface EmbedBatchOptions {
    * and amplify rate-limit pressure.
    */
   maxRetries?: number;
-  /**
-   * #1818: bounded parallelism across BATCH_SIZE sub-batches. Defaults to
-   * `GBRAIN_EMBED_BATCH_CONCURRENCY` env, else 4. Results are
-   * index-addressed so output order always matches input order. Set 1 to
-   * force the pre-v0.42 serial dispatch.
-   */
-  concurrency?: number;
 }
 
 /**
  * Embed a batch of texts via the gateway. Sub-batches of 100 so upstream
  * progress callbacks fire incrementally on large imports. The gateway owns
  * adaptive batch splitting and per-recipe token-budget logic; this paginator
- * owns progress-callback granularity and (#1818) bounded parallel dispatch
- * of the sub-batches — the embed-stale.ts worker-pool pattern, scoped down.
+ * is purely about progress-callback granularity.
  */
 const BATCH_SIZE = 100;
-const DEFAULT_EMBED_BATCH_CONCURRENCY = 4;
-
-function resolveEmbedBatchConcurrency(options: EmbedBatchOptions): number {
-  if (options.concurrency !== undefined) {
-    return Math.max(1, Math.floor(options.concurrency));
-  }
-  const env = Number(process.env.GBRAIN_EMBED_BATCH_CONCURRENCY);
-  if (Number.isFinite(env) && env >= 1) return Math.floor(env);
-  return DEFAULT_EMBED_BATCH_CONCURRENCY;
-}
-
 export async function embedBatch(
   texts: string[],
   options: EmbedBatchOptions = {},
@@ -122,44 +103,13 @@ export async function embedBatch(
   if (texts.length <= BATCH_SIZE && !options.onBatchComplete) {
     return gatewayEmbed(texts, gwOpts);
   }
-  // #1818: dispatch sub-batches through a bounded worker pool instead of a
-  // serial loop. Results are written into a preallocated index-addressed
-  // array so output order matches input order regardless of completion
-  // order; onBatchComplete reports a monotonic completed-embedding count.
-  const slices: Array<{ start: number; texts: string[] }> = [];
+  const results: Float32Array[] = [];
   for (let i = 0; i < texts.length; i += BATCH_SIZE) {
-    slices.push({ start: i, texts: texts.slice(i, i + BATCH_SIZE) });
+    const slice = texts.slice(i, i + BATCH_SIZE);
+    const out = await gatewayEmbed(slice, gwOpts);
+    results.push(...out);
+    options.onBatchComplete?.(results.length, texts.length);
   }
-  const results = new Array<Float32Array>(texts.length);
-  let next = 0;
-  let done = 0;
-  const numWorkers = Math.min(resolveEmbedBatchConcurrency(options), slices.length);
-  // Once any sub-batch fails, `failed` stops the surviving workers from
-  // dispatching FURTHER slices — the whole call is rejecting anyway, so
-  // continuing would burn real provider spend in the background and fire
-  // onBatchComplete after the caller already saw the failure (worst with
-  // embedBatchWithBackoff, whose 429 backoff assumes nothing is in flight).
-  // In-flight sibling calls still run to completion (bounded by numWorkers-1).
-  let failed = false;
-  const worker = async (): Promise<void> => {
-    while (!failed && next < slices.length) {
-      // NOTE: no local aborted-check here — an aborted signal makes the next
-      // gatewayEmbed call throw (SDK-side), which rejects the pool. Returning
-      // silently instead would resolve with holes in `results`.
-      const slice = slices[next++];
-      let out: Float32Array[];
-      try {
-        out = await gatewayEmbed(slice.texts, gwOpts);
-      } catch (err) {
-        failed = true;
-        throw err;
-      }
-      for (let j = 0; j < out.length; j++) results[slice.start + j] = out[j];
-      done += out.length;
-      if (!failed) options.onBatchComplete?.(done, texts.length);
-    }
-  };
-  await Promise.all(Array.from({ length: numWorkers }, () => worker()));
   return results;
 }
 

src/core/migrate.ts

@@ -5671,6 +5671,41 @@ export const MIGRATIONS: Migration[] = [
 `);
     },
   },
+  {
+    version: 125,
+    name: 'take_proposals_empty_scan_sentinels_and_per_claim_rows',
+    // v0.42.x — kill the propose_takes rescan loop + stop dropping claims.
+    //
+    // Two defects, one schema touch:
+    //   1. Zero-claim scans never entered the idempotency cache (only
+    //      proposal rows were written), so pages whose extraction yielded
+    //      nothing were re-extracted on EVERY cycle. Observed live: ~60
+    //      such pages per run ≈ 1,400 wasted extractor calls / ~$15 per
+    //      day — ~90% of total autopilot LLM spend. Fix: the phase now
+    //      writes a status='empty' sentinel row per zero-claim scan; the
+    //      status CHECK gains the 'empty' value. Sentinels are excluded
+    //      from the partial pending index, so the review queue never sees
+    //      them.
+    //   2. The 4-column unique index collapsed a same-page multi-claim run
+    //      to its FIRST claim: rows 2..N conflicted and ON CONFLICT DO
+    //      NOTHING silently dropped them (verified live: exactly one row
+    //      per (page, hash) across 3 days of runs). Fix: the idempotency
+    //      index gains md5(claim_text) — per-claim rows, while the
+    //      4-column prefix still serves the per-scan cache lookup.
+    //
+    // Existing data is index-safe by construction: the old index guaranteed
+    // at most one row per 4-tuple, so the widened index has no duplicates
+    // to trip on. The DROP+ADD CONSTRAINT pair is idempotent as a unit.
+    idempotent: true,
+    sql: `
+      ALTER TABLE take_proposals DROP CONSTRAINT IF EXISTS take_proposals_status_check;
+      ALTER TABLE take_proposals ADD CONSTRAINT take_proposals_status_check
+        CHECK (status IN ('pending','accepted','rejected','superseded','empty'));
+      DROP INDEX IF EXISTS take_proposals_idempotency_idx;
+      CREATE UNIQUE INDEX IF NOT EXISTS take_proposals_idempotency_idx
+        ON take_proposals (source_id, page_slug, content_hash, prompt_version, md5(claim_text));
+    `,
+  },
 ];
 
 export const LATEST_VERSION = MIGRATIONS.length > 0

src/core/pglite-schema.ts

@@ -762,7 +762,7 @@ CREATE TABLE IF NOT EXISTS take_proposals (
   proposed_at                 TIMESTAMPTZ  NOT NULL DEFAULT now(),
   proposal_run_id             TEXT         NOT NULL,
   status                      TEXT         NOT NULL DEFAULT 'pending'
-                                           CHECK (status IN ('pending','accepted','rejected','superseded')),
+                                           CHECK (status IN ('pending','accepted','rejected','superseded','empty')),
   claim_text                  TEXT         NOT NULL,
   kind                        TEXT         NOT NULL,
   holder                      TEXT         NOT NULL,
@@ -777,7 +777,7 @@ CREATE TABLE IF NOT EXISTS take_proposals (
   predicted_brier_bucket_n    INTEGER
 );
 CREATE UNIQUE INDEX IF NOT EXISTS take_proposals_idempotency_idx
-  ON take_proposals (source_id, page_slug, content_hash, prompt_version);
+  ON take_proposals (source_id, page_slug, content_hash, prompt_version, md5(claim_text));
 CREATE INDEX IF NOT EXISTS take_proposals_pending_idx
   ON take_proposals (source_id, status, proposed_at DESC)
   WHERE status = 'pending';

src/core/schema-embedded.ts

@@ -1274,8 +1274,14 @@ CREATE INDEX IF NOT EXISTS calibration_profiles_published_idx
   WHERE published = true;
 
 -- take_proposals: propose_takes phase queue. Idempotency cache via the
--- composite unique index (source_id, page_slug, content_hash, prompt_version)
--- mirrors v0.23 dream_verdicts. proposal_run_id supports --rollback by run.
+-- composite unique index (source_id, page_slug, content_hash, prompt_version,
+-- md5(claim_text)) — the 4-column prefix is the per-scan cache key (mirrors
+-- v0.23 dream_verdicts); md5(claim_text) makes rows per-claim so multi-claim
+-- pages keep every claim (v125). status='empty' rows are zero-claim scan
+-- sentinels: they hold the cache slot for a page version whose extraction
+-- yielded nothing — the phase never re-spends the LLM call on that page
+-- version. Excluded from the partial pending index. proposal_run_id supports
+-- --rollback by run.
 CREATE TABLE IF NOT EXISTS take_proposals (
   id                          BIGSERIAL PRIMARY KEY,
   source_id                   TEXT         NOT NULL REFERENCES sources(id) ON DELETE CASCADE,
@@ -1286,7 +1292,7 @@ CREATE TABLE IF NOT EXISTS take_proposals (
   proposed_at                 TIMESTAMPTZ  NOT NULL DEFAULT now(),
   proposal_run_id             TEXT         NOT NULL,
   status                      TEXT         NOT NULL DEFAULT 'pending'
-                                           CHECK (status IN ('pending','accepted','rejected','superseded')),
+                                           CHECK (status IN ('pending','accepted','rejected','superseded','empty')),
   claim_text                  TEXT         NOT NULL,
   kind                        TEXT         NOT NULL,
   holder                      TEXT         NOT NULL,
@@ -1301,7 +1307,7 @@ CREATE TABLE IF NOT EXISTS take_proposals (
   predicted_brier_bucket_n    INTEGER
 );
 CREATE UNIQUE INDEX IF NOT EXISTS take_proposals_idempotency_idx
-  ON take_proposals (source_id, page_slug, content_hash, prompt_version);
+  ON take_proposals (source_id, page_slug, content_hash, prompt_version, md5(claim_text));
 CREATE INDEX IF NOT EXISTS take_proposals_pending_idx
   ON take_proposals (source_id, status, proposed_at DESC)
   WHERE status = 'pending';

src/schema.sql

@@ -1270,8 +1270,14 @@ CREATE INDEX IF NOT EXISTS calibration_profiles_published_idx
   WHERE published = true;
 
 -- take_proposals: propose_takes phase queue. Idempotency cache via the
--- composite unique index (source_id, page_slug, content_hash, prompt_version)
--- mirrors v0.23 dream_verdicts. proposal_run_id supports --rollback by run.
+-- composite unique index (source_id, page_slug, content_hash, prompt_version,
+-- md5(claim_text)) — the 4-column prefix is the per-scan cache key (mirrors
+-- v0.23 dream_verdicts); md5(claim_text) makes rows per-claim so multi-claim
+-- pages keep every claim (v125). status='empty' rows are zero-claim scan
+-- sentinels: they hold the cache slot for a page version whose extraction
+-- yielded nothing — the phase never re-spends the LLM call on that page
+-- version. Excluded from the partial pending index. proposal_run_id supports
+-- --rollback by run.
 CREATE TABLE IF NOT EXISTS take_proposals (
   id                          BIGSERIAL PRIMARY KEY,
   source_id                   TEXT         NOT NULL REFERENCES sources(id) ON DELETE CASCADE,
@@ -1282,7 +1288,7 @@ CREATE TABLE IF NOT EXISTS take_proposals (
   proposed_at                 TIMESTAMPTZ  NOT NULL DEFAULT now(),
   proposal_run_id             TEXT         NOT NULL,
   status                      TEXT         NOT NULL DEFAULT 'pending'
-                                           CHECK (status IN ('pending','accepted','rejected','superseded')),
+                                           CHECK (status IN ('pending','accepted','rejected','superseded','empty')),
   claim_text                  TEXT         NOT NULL,
   kind                        TEXT         NOT NULL,
   holder                      TEXT         NOT NULL,
@@ -1297,7 +1303,7 @@ CREATE TABLE IF NOT EXISTS take_proposals (
   predicted_brier_bucket_n    INTEGER
 );
 CREATE UNIQUE INDEX IF NOT EXISTS take_proposals_idempotency_idx
-  ON take_proposals (source_id, page_slug, content_hash, prompt_version);
+  ON take_proposals (source_id, page_slug, content_hash, prompt_version, md5(claim_text));
 CREATE INDEX IF NOT EXISTS take_proposals_pending_idx
   ON take_proposals (source_id, status, proposed_at DESC)
   WHERE status = 'pending';

test/ai/adaptive-embed-batch.test.ts

@@ -39,8 +39,6 @@ import {
   __getShrinkStateForTests,
 } from '../../src/core/ai/gateway.ts';
 import { AIConfigError, AITransientError } from '../../src/core/ai/errors.ts';
-import { RECIPES } from '../../src/core/ai/recipes/index.ts';
-import type { Recipe } from '../../src/core/ai/types.ts';
 
 // The last test in this file leaves the gateway configured with a remote
 // provider + fake key and a REAL embed transport. Without a final reset,
@@ -95,14 +93,6 @@ function configureGoogle(): void {
   });
 }
 
-function configureDashscope(): void {
-  configureGateway({
-    embedding_model: 'dashscope:text-embedding-v3',
-    embedding_dimensions: 1024,
-    env: { DASHSCOPE_API_KEY: 'sk-fake' },
-  });
-}
-
 // --------- 1. Pure helpers ---------
 
 describe('splitByTokenBudget (pure helper)', () => {
@@ -159,27 +149,6 @@ describe('splitByTokenBudget (pure helper)', () => {
     expect(splitByTokenBudget(texts, 96_000, 0)).toEqual(splitByTokenBudget(texts, 96_000, 4));
     expect(splitByTokenBudget(texts, 96_000, -1)).toEqual(splitByTokenBudget(texts, 96_000, 4));
   });
-
-  // #1199: count cap for providers that reject batches by input count.
-  test('max_batch_count flushes even when token budget has room', () => {
-    const texts = Array.from({ length: 25 }, (_, i) => `t${i}`);
-    const result = splitByTokenBudget(texts, 1_000_000, 4, 10);
-    expect(result.map(b => b.length)).toEqual([10, 10, 5]);
-    expect(result.flat()).toEqual(texts);
-  });
-
-  test('token budget still governs alongside max_batch_count', () => {
-    const texts = ['a'.repeat(50_000), 'b'.repeat(50_000), 'c'.repeat(50_000)];
-    const result = splitByTokenBudget(texts, 96_000, 1, 10);
-    expect(result).toHaveLength(3);
-  });
-
-  test('undefined / zero / negative max_batch_count is ignored', () => {
-    const texts = Array.from({ length: 25 }, () => 'x');
-    expect(splitByTokenBudget(texts, 1_000_000, 4, undefined)).toHaveLength(1);
-    expect(splitByTokenBudget(texts, 1_000_000, 4, 0)).toHaveLength(1);
-    expect(splitByTokenBudget(texts, 1_000_000, 4, -5)).toHaveLength(1);
-  });
 });
 
 describe('isTokenLimitError (pure helper)', () => {
@@ -210,12 +179,6 @@ describe('isTokenLimitError (pure helper)', () => {
     expect(isTokenLimitError(new Error('Exceeded 300000 max tokens per request'))).toBe(true);
   });
 
-  test('matches DashScope batch-count error (#1199)', () => {
-    expect(isTokenLimitError(new Error(
-      'InvalidParameter: batch size is invalid, it should not be larger than 10.',
-    ))).toBe(true);
-  });
-
   test('does not match unrelated errors', () => {
     expect(isTokenLimitError(new Error('Connection refused'))).toBe(false);
     expect(isTokenLimitError(new Error('Invalid API key'))).toBe(false);
@@ -424,92 +387,26 @@ describe('shrink-on-miss adaptive cache', () => {
   });
 });
 
-// --------- 8. Pre-split count cap through public embed() (#1199 / #970) ---------
-
-describe('embed() pre-split honors max_batch_count', () => {
-  beforeEach(() => resetGateway());
-  afterEach(() => __setEmbedTransportForTests(null));
-
-  test('dashscope never dispatches more than 10 inputs per call (#1199)', async () => {
-    configureDashscope();
-    const stub = mock(async ({ values }: { values: string[] }) => fakeEmbeddings(values, 1024));
-    __setEmbedTransportForTests(stub as any);
-
-    // 25 short texts fit trivially in the 8192-token budget; without the
-    // count cap they'd ship as ONE batch and DashScope would reject it.
-    const texts = Array.from({ length: 25 }, (_, i) => `short-${i}`);
-    const result = await embed(texts);
-
-    expect(result).toHaveLength(25);
-    const callLengths = stub.mock.calls.map(([arg]) => (arg as { values: string[] }).values.length);
-    expect(Math.max(...callLengths)).toBeLessThanOrEqual(10);
-    expect(callLengths.reduce((a, b) => a + b, 0)).toBe(25);
-    // Order preserved across sub-batches.
-    expect((stub.mock.calls[0][0] as { values: string[] }).values[0]).toBe('short-0');
-  });
-
-  test('google pre-splits at 100 inputs per batchEmbedContents call (#970)', async () => {
-    configureGoogle();
-    const stub = mock(async ({ values }: { values: string[] }) => fakeEmbeddings(values, 768));
-    __setEmbedTransportForTests(stub as any);
-
-    const texts = Array.from({ length: 250 }, (_, i) => `g${i}`);
-    const result = await embed(texts);
-
-    expect(result).toHaveLength(250);
-    const callLengths = stub.mock.calls.map(([arg]) => (arg as { values: string[] }).values.length);
-    expect(callLengths).toEqual([100, 100, 50]);
-  });
-});
-
 // --------- 7. Startup warning (D9-B) ---------
 
 describe('startup warning for recipes missing max_batch_tokens', () => {
   beforeEach(() => resetGateway());
 
-  // #970 closed google's missing cap, so no registered recipe is capless
-  // anymore. Inject a synthetic capless recipe to keep the warning path
-  // covered for the NEXT recipe that forgets the field.
-  const caplessRecipe: Recipe = {
-    id: 'capless-test',
-    name: 'Capless Test Provider',
-    tier: 'openai-compat',
-    implementation: 'openai-compatible',
-    base_url_default: 'https://example.invalid/v1',
-    auth_env: { required: [] },
-    touchpoints: {
-      embedding: { models: ['capless-embed-1'], default_dims: 768 },
-    },
-  };
-
-  function configureCapless(): void {
-    configureGateway({
-      embedding_model: 'capless-test:capless-embed-1',
-      embedding_dimensions: 768,
-      env: {},
-    });
-  }
-
   test('configured missing-cap recipe warns once; unrelated recipes stay quiet', () => {
     const warnings: string[] = [];
     const original = console.warn;
     console.warn = (msg: string) => warnings.push(String(msg));
-    RECIPES.set(caplessRecipe.id, caplessRecipe);
     try {
       configureOpenAI();
       expect(warnings.length).toBe(0);
-      // #970 regression: google now declares max_batch_tokens → quiet.
       configureGoogle();
-      expect(warnings.length).toBe(0);
-      configureCapless();
       const firstCallCount = warnings.length;
       // Reconfigure: the warning should NOT re-fire for the same recipes
       // within one process (we already told the operator).
-      configureCapless();
+      configureGoogle();
       expect(warnings.length).toBe(firstCallCount);
     } finally {
       console.warn = original;
-      RECIPES.delete(caplessRecipe.id);
     }
 
     // The warning text should match the documented contract.
@@ -518,12 +415,11 @@ describe('startup warning for recipes missing max_batch_tokens', () => {
     );
     expect(contractMatch.length).toBe(1);
 
-    // Voyage + google declare max_batch_tokens → suppressed. OpenAI is the
-    // canonical fast-path recipe → also suppressed by id. All must be
-    // absent from the warnings; only the synthetic capless recipe fires.
+    // Voyage declares max_batch_tokens → suppressed. OpenAI is the
+    // canonical fast-path recipe → also suppressed by id. Both must be
+    // absent from the warnings.
     expect(warnings.find(w => w.includes('"voyage"'))).toBeUndefined();
     expect(warnings.find(w => w.includes('"openai"'))).toBeUndefined();
-    expect(warnings.find(w => w.includes('"google"'))).toBeUndefined();
-    expect(warnings.find(w => w.includes('"capless-test"'))).toBeDefined();
+    expect(warnings.find(w => w.includes('"google"'))).toBeDefined();
   });
 });

test/ai/no-batch-cap-suppression.serial.test.ts

@@ -52,7 +52,16 @@ describe('v0.32 #779: no_batch_cap suppresses the missing-max_batch_tokens warni
     }
   });
 
-  test('configureGateway does NOT warn for google now that it declares batch caps (#970)', () => {
+  test('configureGateway warns for google only when google embedding is configured', () => {
+    warnSpy.mockClear();
+    resetGateway();
+    configureGateway({ env: {} });
+    let messages = warnSpy.mock.calls.map(c => String(c[0] ?? ''));
+    expect(
+      messages.some(m => m.includes('"google"') && m.includes('without max_batch_tokens')),
+      'google should not warn while OpenAI default is configured',
+    ).toBe(false);
+
     warnSpy.mockClear();
     resetGateway();
     configureGateway({
@@ -60,20 +69,11 @@ describe('v0.32 #779: no_batch_cap suppresses the missing-max_batch_tokens warni
       embedding_dimensions: 768,
       env: { GOOGLE_GENERATIVE_AI_API_KEY: 'fake' },
     });
-    const messages = warnSpy.mock.calls.map(c => String(c[0] ?? ''));
+    messages = warnSpy.mock.calls.map(c => String(c[0] ?? ''));
     expect(
       messages.some(m => m.includes('"google"') && m.includes('without max_batch_tokens')),
-      'google declares max_batch_tokens/max_batch_count since #970 — no warning',
-    ).toBe(false);
-  });
-
-  test('google recipe declares its derived batch caps (#970)', () => {
-    const e = getRecipe('google')!.touchpoints.embedding!;
-    // Count cap is the REAL Gemini limit (batchEmbedContents: 100 inputs);
-    // the token budget is derived (100 × 2048 per-input tokens), NOT the
-    // 2048 per-input limit — copying that verbatim would over-split 50×.
-    expect(e.max_batch_count).toBe(100);
-    expect(e.max_batch_tokens).toBe(204_800);
+      'google should warn when configured because it has fixed-cap models',
+    ).toBe(true);
   });
 
   test('every recipe with empty models[] declares user_provided_models OR has openai-fast-path', () => {

test/ai/recipe-dashscope.test.ts

@@ -55,11 +55,6 @@ describe('recipe: dashscope', () => {
     expect(r.touchpoints.embedding!.chars_per_token).toBeGreaterThan(0);
   });
 
-  test('declares max_batch_count: 10 — DashScope rejects larger batches (#1199)', () => {
-    const r = getRecipe('dashscope')!;
-    expect(r.touchpoints.embedding!.max_batch_count).toBe(10);
-  });
-
   test('dimsProviderOptions threads dimensions for text-embedding-v3 (Matryoshka)', async () => {
     // Codex finding #1: DashScope text-embedding-v3 is Matryoshka 64-1024.
     // Without `dimensions` on the wire, user-selected non-default dims are

test/calibration-profile.test.ts

@@ -38,6 +38,7 @@ function buildMockEngine(opts: { scorecard: TakesScorecard }): {
 } {
   const captured: CapturedSql[] = [];
   const engine = {
+    async getConfig() { return null; },
     kind: 'pglite',
     async getScorecard() {
       return opts.scorecard;

test/embed-batch-concurrency.test.ts

@@ -1,161 +0,0 @@
-/**
- * #1818: embedBatch dispatches its 100-input sub-batches through a bounded
- * worker pool (the embed-stale.ts concurrency pattern) instead of a serial
- * `for` loop. This file pins:
- *
- *   - output order matches input order regardless of completion order
- *     (index-addressed results)
- *   - parallelism actually happens (max in-flight > 1) and stays bounded
- *     (max in-flight <= configured concurrency)
- *   - concurrency: 1 restores the serial pre-#1818 dispatch
- *   - GBRAIN_EMBED_BATCH_CONCURRENCY env is honored when the option is unset
- *   - onBatchComplete reports a monotonic completed count ending at total
- *
- * Transport is stubbed via the gateway's __setEmbedTransportForTests seam
- * (same pattern as test/ai/adaptive-embed-batch.test.ts). OpenAI recipe =
- * fast path (no pre-split), so each embedBatch sub-batch is exactly one
- * transport call.
- */
-
-import { afterAll, afterEach, beforeEach, describe, expect, test } from 'bun:test';
-import {
-  configureGateway,
-  resetGateway,
-  __setEmbedTransportForTests,
-} from '../src/core/ai/gateway.ts';
-import { embedBatch } from '../src/core/embedding.ts';
-import { withEnv } from './helpers/with-env.ts';
-
-const DIMS = 1536;
-
-function configureOpenAI(): void {
-  configureGateway({
-    embedding_model: 'openai:text-embedding-3-large',
-    embedding_dimensions: DIMS,
-    env: { OPENAI_API_KEY: 'sk-fake' },
-  });
-}
-
-/**
- * Install a transport whose returned embedding encodes the GLOBAL input
- * index in dim 0 (texts are `t<N>`), so order can be asserted end-to-end.
- * Tracks the max number of concurrently in-flight transport calls.
- */
-function installTrackingTransport(delayMs = 5): { maxInFlight: () => number } {
-  let inFlight = 0;
-  let maxInFlight = 0;
-  __setEmbedTransportForTests((async ({ values }: { values: string[] }) => {
-    inFlight++;
-    maxInFlight = Math.max(maxInFlight, inFlight);
-    await new Promise(r => setTimeout(r, delayMs));
-    inFlight--;
-    return {
-      embeddings: values.map(v => {
-        const idx = Number(v.slice(1));
-        return Array.from({ length: DIMS }, (_, j) => (j === 0 ? idx : 0.1));
-      }),
-    };
-  }) as any);
-  return { maxInFlight: () => maxInFlight };
-}
-
-const texts = Array.from({ length: 250 }, (_, i) => `t${i}`);
-
-afterAll(() => resetGateway());
-
-describe('embedBatch bounded parallelism (#1818)', () => {
-  beforeEach(() => {
-    resetGateway();
-    configureOpenAI();
-  });
-  afterEach(() => {
-    __setEmbedTransportForTests(null);
-  });
-
-  test('default pool dispatches sub-batches in parallel, order preserved', async () => {
-    const tracker = installTrackingTransport();
-    const result = await embedBatch(texts, { onBatchComplete: () => {} });
-    expect(result).toHaveLength(250);
-    for (let i = 0; i < 250; i++) {
-      expect(result[i][0]).toBe(i);
-    }
-    // 250 texts → 3 sub-batches; default concurrency 4 → all 3 in flight.
-    expect(tracker.maxInFlight()).toBeGreaterThan(1);
-    expect(tracker.maxInFlight()).toBeLessThanOrEqual(4);
-  });
-
-  test('concurrency: 1 keeps the serial dispatch', async () => {
-    const tracker = installTrackingTransport();
-    const result = await embedBatch(texts, { concurrency: 1, onBatchComplete: () => {} });
-    expect(result).toHaveLength(250);
-    expect(tracker.maxInFlight()).toBe(1);
-  });
-
-  test('GBRAIN_EMBED_BATCH_CONCURRENCY env bounds the pool when option unset', async () => {
-    const tracker = installTrackingTransport();
-    await withEnv({ GBRAIN_EMBED_BATCH_CONCURRENCY: '2' }, async () => {
-      await embedBatch(texts, { onBatchComplete: () => {} });
-    });
-    expect(tracker.maxInFlight()).toBeGreaterThan(1);
-    expect(tracker.maxInFlight()).toBeLessThanOrEqual(2);
-  });
-
-  test('onBatchComplete reports a monotonic count ending at total', async () => {
-    installTrackingTransport();
-    const seen: number[] = [];
-    await embedBatch(texts, {
-      onBatchComplete: (done, total) => {
-        expect(total).toBe(250);
-        seen.push(done);
-      },
-    });
-    expect(seen).toHaveLength(3); // 100 + 100 + 50 sub-batches
-    for (let i = 1; i < seen.length; i++) {
-      expect(seen[i]).toBeGreaterThan(seen[i - 1]);
-    }
-    expect(seen[seen.length - 1]).toBe(250);
-  });
-
-  test('a failing sub-batch rejects the whole call', async () => {
-    let call = 0;
-    __setEmbedTransportForTests((async ({ values }: { values: string[] }) => {
-      call++;
-      if (call === 2) throw new Error('boom');
-      await new Promise(r => setTimeout(r, 2));
-      return { embeddings: values.map(() => Array.from({ length: DIMS }, () => 0.1)) };
-    }) as any);
-    await expect(embedBatch(texts, { onBatchComplete: () => {} })).rejects.toThrow();
-  });
-
-  test('after a failure, surviving workers stop dispatching new slices', async () => {
-    // 1000 texts → 10 slices, concurrency 2. First call fails immediately;
-    // without the `failed` flag the second worker would keep draining all
-    // 10 slices in the background AFTER embedBatch already rejected —
-    // burning provider spend and firing onBatchComplete post-rejection.
-    let calls = 0;
-    const completions: number[] = [];
-    __setEmbedTransportForTests((async ({ values }: { values: string[] }) => {
-      calls++;
-      if (calls === 1) throw new Error('boom');
-      await new Promise(r => setTimeout(r, 5));
-      return { embeddings: values.map(() => Array.from({ length: DIMS }, () => 0.1)) };
-    }) as any);
-    const many = Array.from({ length: 1000 }, (_, i) => `t${i}`);
-    await expect(
-      embedBatch(many, { concurrency: 2, onBatchComplete: d => completions.push(d) }),
-    ).rejects.toThrow('boom');
-    const callsAtRejection = calls;
-    await new Promise(r => setTimeout(r, 50)); // would-be background drain window
-    expect(calls).toBe(callsAtRejection); // no new dispatch after rejection
-    expect(calls).toBeLessThanOrEqual(2); // only the in-flight sibling ran
-    expect(completions).toHaveLength(0); // no progress reported after failure
-  });
-
-  test('single small batch without callback stays on the one-call fast path', async () => {
-    const tracker = installTrackingTransport(1);
-    const result = await embedBatch(['t0', 't1', 't2']);
-    expect(result).toHaveLength(3);
-    expect(result[1][0]).toBe(1);
-    expect(tracker.maxInFlight()).toBe(1);
-  });
-});

test/grade-takes-ensemble.test.ts

@@ -47,6 +47,7 @@ function buildMockEngine(opts: { takes: Take[] }): {
   const captured: CapturedSql[] = [];
   const resolves: CapturedResolve[] = [];
   const engine = {
+    async getConfig() { return null; },
     kind: 'pglite',
     async listTakes() {
       return opts.takes;

test/grade-takes.test.ts

@@ -46,12 +46,14 @@ interface CapturedResolve {
 function buildMockEngine(opts: {
   takes: Take[];
   cachedGrades?: Set<string>; // composite-key strings already in take_grade_cache
+  config?: Record<string, string>; // engine.getConfig plane (models.grade_takes etc.)
 }): { engine: BrainEngine; captured: CapturedSql[]; resolves: CapturedResolve[] } {
   const captured: CapturedSql[] = [];
   const resolves: CapturedResolve[] = [];
   const cached = opts.cachedGrades ?? new Set<string>();
 
   const engine = {
+    async getConfig(key: string) { return opts.config?.[key] ?? null; },
     kind: 'pglite',
     async listTakes() {
       return opts.takes;
@@ -224,6 +226,28 @@ describe('runPhaseGradeTakes — phase integration', () => {
     expect(resolves).toHaveLength(0); // no canonical mutation
   });
 
+  test('models.grade_takes config drives the judge call; cache key stays bare-tailed', async () => {
+    // Pre-fix the judge call rode the gateway's chat_model while the cache
+    // key / budget label recorded a hardcoded 'claude-sonnet-4-6'. The phase
+    // now resolves models.grade_takes; the judge gets the FULL string and
+    // the cache row keys on the bare tail (continuity with historical rows).
+    const takes = [buildTake({ id: 1, sinceDate: '2023-01-01' })];
+    const { engine, captured } = buildMockEngine({
+      takes,
+      config: { 'models.grade_takes': 'anthropic:claude-sonnet-5' },
+    });
+    const hints: Array<string | undefined> = [];
+    const judge: JudgeFn = async ({ modelHint }) => {
+      hints.push(modelHint);
+      return { verdict: 'correct', confidence: 0.9, reasoning: 'held' };
+    };
+    const result = await runPhaseGradeTakes(buildCtx(engine), { judge });
+    expect(result.status).toBe('ok');
+    expect(hints).toEqual(['anthropic:claude-sonnet-5']); // actual call gets the FULL string
+    const inserts = captured.filter(c => c.sql.includes('INSERT INTO take_grade_cache'));
+    expect(inserts[0]!.params[2]).toBe('claude-sonnet-5'); // judge_model_id is the bare tail
+  });
+
   test('D17: auto-resolve OFF by default — even high-confidence verdict does NOT mutate takes', async () => {
     const takes = [buildTake({ id: 1, sinceDate: '2023-01-01' })];
     const { engine, resolves } = buildMockEngine({ takes });

test/helpers/legacy-embedding-preload.ts

@@ -19,7 +19,7 @@
  * overwrites this preload.
  */
 import { configureGateway, getEmbeddingDimensions } from '../../src/core/ai/gateway.ts';
-import { afterEach, beforeEach } from 'bun:test';
+import { beforeEach } from 'bun:test';
 
 const LEGACY_CONFIG = {
   embedding_model: 'openai:text-embedding-3-large',
@@ -52,7 +52,7 @@ applyLegacy();
 //   2. file-local beforeAll → may overwrite to ZE/1280
 // Since beforeAll runs once per file BEFORE the first beforeEach,
 // file-local beforeAll wins for that file's tests. ✓
-function applyLegacyIfEmpty() {
+beforeEach(() => {
   try {
     // Only re-apply if the gateway was reset (or never configured).
     // Tests that explicitly configured a different model in their
@@ -62,28 +62,4 @@ function applyLegacyIfEmpty() {
   } catch {
     applyLegacy();
   }
-}
-
-beforeEach(applyLegacyIfEmpty);
-
-// PR #3130 shard-order fix: beforeEach alone leaves ONE window open — a file
-// whose LAST afterEach calls resetGateway() poisons the NEXT file's
-// beforeAll, which runs BEFORE any beforeEach fires. A beforeAll there that
-// does engine.initSchema() then sizes the embedding column from the gateway
-// DEFAULTS (zembed-1/1280d) instead of the pinned legacy 1536, and every
-// 1536-d Float32Array fixture in that file dies with
-// "expected 1280 dimensions, not 1536". Which file pair collides is a
-// function of shard composition, so adding/removing ANY test file can
-// surface it (that is exactly how it bit shard 9).
-//
-// Preload hooks are registered before any file-local hooks, and bun runs
-// after-hooks inside-out (file-local afterEach first, then this one), so
-// this repairs the empty slot immediately after the poisoning reset —
-// before the next file's beforeAll can observe it.
-//
-// Known remaining window: a file whose afterAll() resets the gateway (no
-// hook runs between its afterAll and the next file's beforeAll). Files
-// that reset in afterAll and can precede a schema-creating file should
-// re-apply their own config, or the victim file should configureGateway()
-// explicitly in its beforeAll.
-afterEach(applyLegacyIfEmpty);
+});

test/import-default-workers.test.ts

@@ -1,69 +0,0 @@
-/**
- * #1207: `gbrain import` without `--workers` used to hardcode workerCount=1,
- * so a large Postgres import paid one serial embedding round-trip per file.
- * runImport now routes the default through the shared autoConcurrency policy
- * (PGLite → 1, >100 files on Postgres → DEFAULT_PARALLEL_WORKERS), while an
- * explicit `--workers N` still wins.
- *
- * The engine here is a minimal postgres-kind stub with no database_url in
- * config — runImport's parallel branch then falls back to serial processing
- * (its PR #490 guard) but the WORKER-COUNT DECISION (the thing #1207 fixes)
- * is still observable via the "Using N parallel workers" log line. Per-file
- * imports fail against the stub engine and are swallowed by runImport's
- * per-file catch; that's fine — this test pins the policy, not the import.
- */
-
-import { afterEach, beforeEach, describe, expect, test } from 'bun:test';
-import { mkdtempSync, writeFileSync, mkdirSync, rmSync, realpathSync } from 'fs';
-import { tmpdir } from 'os';
-import { join } from 'path';
-import { withEnv } from './helpers/with-env.ts';
-import { runImport } from '../src/commands/import.ts';
-
-const fakePostgresEngine = {
-  kind: 'postgres',
-  executeRaw: async () => [],
-  logIngest: async () => {},
-  setConfig: async () => {},
-  getConfig: async () => null,
-} as any;
-
-let workspace: string;
-let brainDir: string;
-let logs: string[];
-const realLog = console.log;
-
-beforeEach(() => {
-  workspace = mkdtempSync(join(tmpdir(), 'gbrain-import-workers-home-'));
-  mkdirSync(join(workspace, '.gbrain'), { recursive: true });
-  brainDir = realpathSync(mkdtempSync(join(tmpdir(), 'gbrain-import-workers-brain-')));
-  // 101 files: one past AUTO_CONCURRENCY_FILE_THRESHOLD (100).
-  for (let i = 0; i < 101; i++) {
-    writeFileSync(join(brainDir, `page-${i}.md`), `# Page ${i}\n\nbody ${i}\n`);
-  }
-  logs = [];
-  console.log = (msg?: unknown) => logs.push(String(msg));
-});
-
-afterEach(() => {
-  console.log = realLog;
-  rmSync(workspace, { recursive: true, force: true });
-  rmSync(brainDir, { recursive: true, force: true });
-});
-
-describe('import default worker count (#1207)', () => {
-  test('no --workers flag → autoConcurrency picks 4 for >100 files on Postgres', async () => {
-    await withEnv({ GBRAIN_HOME: join(workspace, '.gbrain'), GBRAIN_SOURCE: undefined }, async () => {
-      await runImport(fakePostgresEngine, [brainDir, '--no-embed'], { sourceId: 'default' });
-    });
-    expect(logs.some(l => l.includes('Using 4 parallel workers'))).toBe(true);
-  });
-
-  test('explicit --workers 2 still wins over the auto policy', async () => {
-    await withEnv({ GBRAIN_HOME: join(workspace, '.gbrain'), GBRAIN_SOURCE: undefined }, async () => {
-      await runImport(fakePostgresEngine, [brainDir, '--no-embed', '--workers', '2'], { sourceId: 'default' });
-    });
-    expect(logs.some(l => l.includes('Using 2 parallel workers'))).toBe(true);
-    expect(logs.some(l => l.includes('Using 4 parallel workers'))).toBe(false);
-  });
-});

test/propose-takes-rescan.test.ts

@@ -0,0 +1,160 @@
+/**
+ * propose_takes rescan-loop + dropped-claims regression tests (migration v125).
+ *
+ * Two live-observed defects, both fixed by the v125 schema + phase change:
+ *
+ *   1. RESCAN LOOP — a page whose extraction yielded zero claims never
+ *      entered the idempotency cache (only proposal rows were written), so
+ *      every cycle re-spent the extractor call on the same unchanged page.
+ *      Live impact: ~60 such pages × every cycle ≈ 1,400 wasted LLM calls
+ *      (~$15) per day — ~90% of total autopilot spend. Fix: status='empty'
+ *      sentinel row per zero-claim scan.
+ *
+ *   2. DROPPED CLAIMS — the 4-column unique index collapsed a same-page
+ *      multi-claim run to its first claim (rows 2..N conflicted, ON CONFLICT
+ *      DO NOTHING dropped them silently; verified live: exactly 1 row per
+ *      (page, hash) over 3 days). Fix: idempotency index gains
+ *      md5(claim_text).
+ *
+ * Hermetic: PGLite engine + injected extractor; no gateway, no LLM.
+ */
+import { describe, test, expect, beforeAll, afterAll } from 'bun:test';
+import { PGLiteEngine } from '../src/core/pglite-engine.ts';
+import { runPhaseProposeTakes, type ProposeTakesExtractor, type ProposedTake } from '../src/core/cycle/propose-takes.ts';
+import type { OperationContext } from '../src/core/operations.ts';
+
+let engine: PGLiteEngine;
+
+function ctx(): OperationContext {
+  return {
+    engine,
+    remote: false,
+    config: {} as OperationContext['config'],
+    logger: { info() {}, warn() {}, error() {}, debug() {} } as unknown as OperationContext['logger'],
+  } as unknown as OperationContext;
+}
+
+/** Extractor stub that counts invocations per page slug. */
+function countingExtractor(
+  claimsBySlug: Record<string, ProposedTake[]>,
+): { extractor: ProposeTakesExtractor; calls: string[] } {
+  const calls: string[] = [];
+  const extractor: ProposeTakesExtractor = async ({ pagePath }) => {
+    calls.push(pagePath);
+    return claimsBySlug[pagePath] ?? [];
+  };
+  return { extractor, calls };
+}
+
+beforeAll(async () => {
+  engine = new PGLiteEngine();
+  await engine.connect({});
+  await engine.initSchema();
+  await engine.putPage('notes/zero-claims', {
+    type: 'note',
+    title: 'pure narrative',
+    compiled_truth: 'A quiet walk in the park. Nothing opinionated happened at all today.',
+  });
+  await engine.putPage('notes/three-claims', {
+    type: 'note',
+    title: 'opinionated',
+    compiled_truth: 'I bet acme-example wins the market. widget-co will struggle. fund-a is overexposed.',
+  });
+});
+
+afterAll(async () => {
+  await engine.disconnect();
+});
+
+describe('rescan loop — zero-claim scans enter the cache', () => {
+  test('second run cache-hits: extractor is NOT called again on unchanged pages', async () => {
+    const claims = {
+      'notes/three-claims': [
+        { claim_text: 'acme-example wins the market', kind: 'bet' as const, holder: 'brain', weight: 0.7 },
+        { claim_text: 'widget-co will struggle', kind: 'take' as const, holder: 'brain', weight: 0.6 },
+        { claim_text: 'fund-a is overexposed', kind: 'take' as const, holder: 'brain', weight: 0.55 },
+      ],
+    };
+
+    const first = countingExtractor(claims);
+    const r1 = await runPhaseProposeTakes(ctx(), { extractor: first.extractor });
+    expect(r1.status).toBe('ok');
+    // Both pages extracted on the first pass.
+    expect(first.calls).toContain('notes/zero-claims');
+    expect(first.calls).toContain('notes/three-claims');
+
+    const second = countingExtractor(claims);
+    const r2 = await runPhaseProposeTakes(ctx(), { extractor: second.extractor });
+    expect(r2.status).toBe('ok');
+    // THE regression: pre-fix the zero-claim page missed the cache every
+    // run and was re-extracted here. (Run 1's receipt page legitimately
+    // appears once — it's a new page — and its zero-claim scan now caches
+    // too; pre-fix, receipts re-scanned forever as well.)
+    expect(second.calls).not.toContain('notes/zero-claims');
+    expect(second.calls).not.toContain('notes/three-claims');
+
+    // Run 2 inserted nothing, so no new receipt page exists: run 3 must be
+    // fully quiescent — zero extractor calls, zero cache misses.
+    const third = countingExtractor(claims);
+    const r3 = await runPhaseProposeTakes(ctx(), { extractor: third.extractor });
+    expect(r3.status).toBe('ok');
+    expect(third.calls).toEqual([]);
+    expect((r3.details as Record<string, unknown>).cache_misses).toBe(0);
+  });
+
+  test('zero-claim scan wrote an "empty" sentinel invisible to the pending queue', async () => {
+    const sentinel = await engine.executeRaw<{ status: string; claim_text: string }>(
+      `SELECT status, claim_text FROM take_proposals WHERE page_slug = 'notes/zero-claims'`,
+      [],
+    );
+    expect(sentinel.length).toBe(1);
+    expect(sentinel[0].status).toBe('empty');
+    expect(sentinel[0].claim_text).toBe('');
+    const pending = await engine.executeRaw<{ n: number }>(
+      `SELECT COUNT(*)::int AS n FROM take_proposals WHERE page_slug = 'notes/zero-claims' AND status = 'pending'`,
+      [],
+    );
+    expect(Number(pending[0].n)).toBe(0);
+  });
+});
+
+describe('dropped claims — per-claim rows survive the idempotency index', () => {
+  test('a 3-claim page stores 3 rows and reports an honest inserted count', async () => {
+    const rows = await engine.executeRaw<{ claim_text: string }>(
+      `SELECT claim_text FROM take_proposals WHERE page_slug = 'notes/three-claims' AND status = 'pending' ORDER BY id`,
+      [],
+    );
+    // Pre-fix the 4-column unique index kept only the FIRST claim.
+    expect(rows.length).toBe(3);
+    expect(rows.map(r => r.claim_text)).toEqual([
+      'acme-example wins the market',
+      'widget-co will struggle',
+      'fund-a is overexposed',
+    ]);
+  });
+
+  test('content change re-extracts and stores the new version separately', async () => {
+    await engine.putPage('notes/zero-claims', {
+      type: 'note',
+      title: 'pure narrative',
+      compiled_truth: 'Updated: I now believe acme-example is undervalued and will re-rate within a year.',
+    });
+    const claims = {
+      'notes/zero-claims': [
+        { claim_text: 'acme-example is undervalued', kind: 'take' as const, holder: 'brain', weight: 0.6 },
+      ],
+    };
+    const run = countingExtractor(claims);
+    const r = await runPhaseProposeTakes(ctx(), { extractor: run.extractor });
+    expect(r.status).toBe('ok');
+    // Changed page re-extracts; the unchanged 3-claim page stays cached.
+    expect(run.calls).toEqual(['notes/zero-claims']);
+    expect((r.details as Record<string, unknown>).proposals_inserted).toBe(1);
+    const all = await engine.executeRaw<{ status: string }>(
+      `SELECT status FROM take_proposals WHERE page_slug = 'notes/zero-claims' ORDER BY id`,
+      [],
+    );
+    // Old hash's sentinel + new hash's pending claim coexist.
+    expect(all.map(r2 => r2.status).sort()).toEqual(['empty', 'pending']);
+  });
+});

test/propose-takes.test.ts

@@ -41,12 +41,16 @@ interface CapturedSql {
 function buildMockEngine(opts: {
   pages: Page[];
   existingProposals?: Set<string>; // composite-key strings already in take_proposals
+  config?: Record<string, string>; // engine.getConfig plane (models.tier.* etc.)
 }): { engine: BrainEngine; captured: CapturedSql[] } {
   const captured: CapturedSql[] = [];
   const existing = opts.existingProposals ?? new Set<string>();
 
   const engine = {
     kind: 'pglite',
+    async getConfig(key: string) {
+      return opts.config?.[key] ?? null;
+    },
     async listPages() {
       return opts.pages;
     },
@@ -59,7 +63,12 @@ function buildMockEngine(opts: {
         if (existing.has(key)) return [{ id: 1 } as unknown as T];
         return [];
       }
-      // INSERT — return nothing
+      // INSERT ... RETURNING id — emulate a successful insert so the
+      // honest proposals_inserted counter (counts RETURNING rows, not
+      // attempts) sees the row land. Conflicted inserts would return [].
+      if (sql.includes('INSERT INTO take_proposals') && sql.includes('RETURNING id')) {
+        return [{ id: 1 } as unknown as T];
+      }
       return [];
     },
   } as unknown as BrainEngine;
@@ -267,6 +276,29 @@ describe('runPhaseProposeTakes — phase integration', () => {
     expect(inserts[0]!.params[9]).toBe('market'); // domain
   });
 
+  test('extractor model resolves through models.propose_takes config', async () => {
+    // Pre-fix the phase's only model knob was the gateway chat model — there
+    // was no per-phase config key. The phase now resolves once via
+    // resolveModel(models.propose_takes > models.default > env > gateway
+    // chat model); the extractor hint and the stored model_id must both
+    // reflect the configured override (full provider-prefixed string, #2451).
+    const pages = [buildPage({ slug: 'wiki/concepts/tier-routing', body: 'Tier-routed models will win.' })];
+    const { engine, captured } = buildMockEngine({
+      pages,
+      config: { 'models.propose_takes': 'anthropic:claude-sonnet-5' },
+    });
+    const seen: Array<string | undefined> = [];
+    const extractor: ProposeTakesExtractor = async ({ modelHint }) => {
+      seen.push(modelHint);
+      return [{ claim_text: 'tier-routed models win', kind: 'bet', holder: 'brain', weight: 0.7 }];
+    };
+    const result = await runPhaseProposeTakes(buildCtx(engine), { extractor });
+    expect(result.status).toBe('ok');
+    expect(seen).toEqual(['anthropic:claude-sonnet-5']); // chat call gets the FULL string
+    const inserts = captured.filter(c => c.sql.includes('INSERT INTO take_proposals'));
+    expect(inserts[0]!.params[11]).toBe('anthropic:claude-sonnet-5'); // stored model_id matches the call
+  });
+
   test('cache hit: page already in take_proposals is skipped', async () => {
     const body = 'A page that was already processed.';
     const pages = [buildPage({ slug: 'wiki/old-page', body })];