diff --git a/src/core/calibration/domain-aggregators.ts b/src/core/calibration/domain-aggregators.ts
new file mode 100644
index 000000000..8f4cb1a2a
--- /dev/null
+++ b/src/core/calibration/domain-aggregators.ts
@@ -0,0 +1,279 @@
+// v0.41 T10 — calibration domain aggregators.
+//
+// Closed registry of algorithms that aggregate resolved takes within a
+// calibration domain. Each aggregator runs against the active pack's
+// `calibration_domains: [{name, aggregator, page_types}]` declarations
+// (T3 schema) and produces a per-domain scorecard for the JSONB stored
+// in calibration_profiles.domain_scorecards.
+//
+// The aggregator algorithms are CLOSED (this enum + their SQL stays in
+// code; pack manifests reference them by name). Domain NAMES are open —
+// any pack can declare new domains pointing at known aggregators. See
+// T3 (codex refinement of D6).
+//
+// JOIN shape: takes → take_domain_assignments WHERE domain = $name
+// AND assignments.take_id = takes.id. Pages filtering happens via
+// page_types: [...] from the domain declaration — JOIN pages too and
+// filter by p.type = ANY($page_types::text[]).
+
+import type { BrainEngine } from '../engine.ts';
+import type { AggregatorKind, CalibrationDomain } from '../schema-pack/manifest-v1.ts';
+
+export interface DomainScorecard {
+  /** Number of resolved takes contributing to this scorecard. */
+  n: number;
+  /** Brier score (lower = better). null when n === 0 or aggregator doesn't compute one. */
+  brier: number | null;
+  /** Accuracy fraction in [0, 1]. null when n === 0 or aggregator doesn't compute one. */
+  accuracy: number | null;
+  /** Aggregator algorithm used. Stamped for downstream debugging. */
+  aggregator: AggregatorKind;
+  /** Page types whose takes feed this domain (per pack manifest). */
+  page_types: string[];
+  /** Aggregator-specific extras. cluster_summary fills tier_counts here. */
+  extras?: Record<string, unknown>;
+}
+
+export type DomainScorecards = Record<string, DomainScorecard>;
+
+/**
+ * Aggregate every declared calibration_domain for the given holder.
+ *
+ * Returns a Record<domain_name, DomainScorecard>. Empty domains (n=0)
+ * are STILL included in the result so consumers can distinguish
+ * "domain is declared but has no resolved takes yet" from "domain
+ * isn't declared by the active pack" (the latter case never appears
+ * in this return shape).
+ *
+ * Fail-soft per domain: if one domain's SQL throws (e.g. the pack
+ * declares a page_type that doesn't exist in the brain yet), the
+ * domain gets {n: 0, brier: null, accuracy: null, extras: {error: msg}}
+ * and the rest of the domains still aggregate. The phase keeps running.
+ */
+export async function aggregateDomainScorecards(
+  engine: BrainEngine,
+  holder: string,
+  domains: CalibrationDomain[],
+  sourceId: string,
+): Promise<DomainScorecards> {
+  const out: DomainScorecards = {};
+  for (const domain of domains) {
+    try {
+      const scorecard = await aggregateOneDomain(engine, holder, domain, sourceId);
+      out[domain.name] = scorecard;
+    } catch (err) {
+      out[domain.name] = {
+        n: 0,
+        brier: null,
+        accuracy: null,
+        aggregator: domain.aggregator,
+        page_types: [...domain.page_types],
+        extras: { error: err instanceof Error ? err.message : String(err) },
+      };
+    }
+  }
+  return out;
+}
+
+async function aggregateOneDomain(
+  engine: BrainEngine,
+  holder: string,
+  domain: CalibrationDomain,
+  sourceId: string,
+): Promise<DomainScorecard> {
+  switch (domain.aggregator) {
+    case 'scalar_brier':
+      return aggregateScalarBrier(engine, holder, domain, sourceId);
+    case 'weighted_brier':
+      return aggregateWeightedBrier(engine, holder, domain, sourceId);
+    case 'count_based':
+      return aggregateCountBased(engine, holder, domain, sourceId);
+    case 'cluster_summary':
+      return aggregateClusterSummary(engine, holder, domain, sourceId);
+  }
+}
+
+/**
+ * Standard Brier score over resolved binary takes.
+ * Brier = mean((p - outcome)^2) where p = take.weight (probability),
+ * outcome = resolved_outcome::int (0 or 1).
+ */
+async function aggregateScalarBrier(
+  engine: BrainEngine,
+  holder: string,
+  domain: CalibrationDomain,
+  sourceId: string,
+): Promise<DomainScorecard> {
+  const rows = await engine.executeRaw<{
+    n: number;
+    brier: number | null;
+    accuracy: number | null;
+  }>(
+    `SELECT
+       COUNT(*)::int AS n,
+       AVG(POWER(t.weight - (t.resolved_outcome::int)::real, 2))::real AS brier,
+       (SUM(CASE WHEN (t.weight >= 0.5) = t.resolved_outcome THEN 1 ELSE 0 END)::real
+          / NULLIF(COUNT(*), 0))::real AS accuracy
+     FROM takes t
+     JOIN take_domain_assignments a ON a.take_id = t.id
+     JOIN pages p ON p.id = t.page_id
+     WHERE a.domain = $1
+       AND t.holder = $2
+       AND t.active = TRUE
+       AND t.resolved_outcome IS NOT NULL
+       AND p.type = ANY($3::text[])
+       AND p.source_id = $4`,
+    [domain.name, holder, domain.page_types, sourceId],
+  );
+  const row = rows[0] ?? { n: 0, brier: null, accuracy: null };
+  return {
+    n: row.n,
+    brier: row.n > 0 ? row.brier : null,
+    accuracy: row.n > 0 ? row.accuracy : null,
+    aggregator: 'scalar_brier',
+    page_types: [...domain.page_types],
+  };
+}
+
+/**
+ * Weighted Brier — weight each prediction by its CONVICTION (ABS(weight - 0.5) * 2).
+ * Low-conviction (weight ≈ 0.5) hunches count less than high-conviction calls.
+ * Mirrors the "market_call cares more about strong-conviction misses" semantics
+ * from the investor pack.
+ */
+async function aggregateWeightedBrier(
+  engine: BrainEngine,
+  holder: string,
+  domain: CalibrationDomain,
+  sourceId: string,
+): Promise<DomainScorecard> {
+  const rows = await engine.executeRaw<{
+    n: number;
+    brier: number | null;
+    accuracy: number | null;
+  }>(
+    `WITH scored AS (
+       SELECT
+         POWER(t.weight - (t.resolved_outcome::int)::real, 2) AS sq_err,
+         ABS(t.weight - 0.5) * 2.0 AS conviction,
+         (t.weight >= 0.5) = t.resolved_outcome AS hit
+       FROM takes t
+       JOIN take_domain_assignments a ON a.take_id = t.id
+       JOIN pages p ON p.id = t.page_id
+       WHERE a.domain = $1
+         AND t.holder = $2
+         AND t.active = TRUE
+         AND t.resolved_outcome IS NOT NULL
+         AND p.type = ANY($3::text[])
+         AND p.source_id = $4
+     )
+     SELECT
+       COUNT(*)::int AS n,
+       (SUM(sq_err * conviction) / NULLIF(SUM(conviction), 0))::real AS brier,
+       (SUM(CASE WHEN hit THEN 1 ELSE 0 END)::real / NULLIF(COUNT(*), 0))::real AS accuracy
+     FROM scored`,
+    [domain.name, holder, domain.page_types, sourceId],
+  );
+  const row = rows[0] ?? { n: 0, brier: null, accuracy: null };
+  return {
+    n: row.n,
+    brier: row.n > 0 ? row.brier : null,
+    accuracy: row.n > 0 ? row.accuracy : null,
+    aggregator: 'weighted_brier',
+    page_types: [...domain.page_types],
+  };
+}
+
+/**
+ * Simple accuracy ratio (correct / resolved). Use when binary outcomes
+ * don't have natural probability semantics — e.g., "did the event happen
+ * at all" rather than "what's the probability it happens."
+ */
+async function aggregateCountBased(
+  engine: BrainEngine,
+  holder: string,
+  domain: CalibrationDomain,
+  sourceId: string,
+): Promise<DomainScorecard> {
+  const rows = await engine.executeRaw<{ n: number; accuracy: number | null }>(
+    `SELECT
+       COUNT(*)::int AS n,
+       (SUM(CASE WHEN (t.weight >= 0.5) = t.resolved_outcome THEN 1 ELSE 0 END)::real
+          / NULLIF(COUNT(*), 0))::real AS accuracy
+     FROM takes t
+     JOIN take_domain_assignments a ON a.take_id = t.id
+     JOIN pages p ON p.id = t.page_id
+     WHERE a.domain = $1
+       AND t.holder = $2
+       AND t.active = TRUE
+       AND t.resolved_outcome IS NOT NULL
+       AND p.type = ANY($3::text[])
+       AND p.source_id = $4`,
+    [domain.name, holder, domain.page_types, sourceId],
+  );
+  const row = rows[0] ?? { n: 0, accuracy: null };
+  return {
+    n: row.n,
+    brier: null,
+    accuracy: row.n > 0 ? row.accuracy : null,
+    aggregator: 'count_based',
+    page_types: [...domain.page_types],
+  };
+}
+
+/**
+ * Descriptive rollup for domains where Brier doesn't apply (concept_themes
+ * — concepts don't have binary outcomes to score). Returns count of pages
+ * matching the domain's page_types plus tier histogram when frontmatter
+ * carries `tier: T1|T2|T3|T4`.
+ *
+ * v0.41 minimal: returns n=page count, brier=null, accuracy=null, extras
+ * carries tier_counts when available. v0.42+ can enrich with dominant
+ * topics + recency + cross-source breadth.
+ */
+async function aggregateClusterSummary(
+  engine: BrainEngine,
+  holder: string,
+  domain: CalibrationDomain,
+  sourceId: string,
+): Promise<DomainScorecard> {
+  // For cluster_summary, "holder" is informational only — concepts aren't
+  // owned by a holder the way takes are. We still scope by source.
+  const rows = await engine.executeRaw<{
+    n: number;
+    t1: number;
+    t2: number;
+    t3: number;
+    t4: number;
+  }>(
+    `SELECT
+       COUNT(*)::int AS n,
+       SUM(CASE WHEN frontmatter->>'tier' = 'T1' OR frontmatter->>'tier' = '1' THEN 1 ELSE 0 END)::int AS t1,
+       SUM(CASE WHEN frontmatter->>'tier' = 'T2' OR frontmatter->>'tier' = '2' THEN 1 ELSE 0 END)::int AS t2,
+       SUM(CASE WHEN frontmatter->>'tier' = 'T3' OR frontmatter->>'tier' = '3' THEN 1 ELSE 0 END)::int AS t3,
+       SUM(CASE WHEN frontmatter->>'tier' = 'T4' OR frontmatter->>'tier' = '4' THEN 1 ELSE 0 END)::int AS t4
+     FROM pages
+     WHERE type = ANY($1::text[])
+       AND source_id = $2
+       AND deleted_at IS NULL`,
+    [domain.page_types, sourceId],
+  );
+  const row = rows[0] ?? { n: 0, t1: 0, t2: 0, t3: 0, t4: 0 };
+  // holder is unused for cluster_summary but documented for symmetry
+  void holder;
+  return {
+    n: row.n,
+    brier: null,
+    accuracy: null,
+    aggregator: 'cluster_summary',
+    page_types: [...domain.page_types],
+    extras: {
+      tier_counts: {
+        T1: row.t1 ?? 0,
+        T2: row.t2 ?? 0,
+        T3: row.t3 ?? 0,
+        T4: row.t4 ?? 0,
+      },
+    },
+  };
+}
diff --git a/src/core/cycle/calibration-profile.ts b/src/core/cycle/calibration-profile.ts
index 5c3580090..05aff0234 100644
--- a/src/core/cycle/calibration-profile.ts
+++ b/src/core/cycle/calibration-profile.ts
@@ -29,6 +29,10 @@ import { BaseCyclePhase, type ScopedReadOpts, type BasePhaseOpts } from './base-
 import { chat as gatewayChat } from '../ai/gateway.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
+// pack's calibration_domains declarations into per-domain Brier+accuracy+
+// extras scorecards stored in calibration_profiles.domain_scorecards JSONB.
+import { aggregateDomainScorecards, type DomainScorecards } from '../calibration/domain-aggregators.ts';
 import { GBrainError } from '../types.ts';
 import type { OperationContext } from '../operations.ts';
 import type { BrainEngine, TakesScorecard } from '../engine.ts';
@@ -310,6 +314,39 @@ class CalibrationProfilePhase extends BaseCyclePhase {
 
     // Write the profile row.
     const sourceId = scope.sourceId ?? 'default';
+
+    // v0.41 T10 — domain_scorecards widening (replaces v0.36.1.0 `{}`
+    // placeholder). Resolve the active pack's calibration_domains
+    // declarations and run each one's aggregator. Per-domain fail-soft:
+    // a malformed domain or missing page_type produces a {n:0, error}
+    // entry rather than crashing the whole phase. When no pack is
+    // active or the active pack declares no calibration_domains, the
+    // JSONB stays {} (byte-identical to v0.36.1.0 — R1 IRON RULE).
+    let domainScorecards: DomainScorecards = {};
+    try {
+      const { loadActivePack } = await import('../schema-pack/load-active.ts');
+      const { loadConfig } = await import('../config.ts');
+      const cfg = loadConfig();
+      const resolved = await loadActivePack({ cfg, remote: false });
+      const domains = resolved.manifest.calibration_domains ?? [];
+      if (domains.length > 0) {
+        domainScorecards = await aggregateDomainScorecards(
+          engine,
+          holder,
+          domains,
+          sourceId,
+        );
+      }
+    } catch (err) {
+      // Pack resolution failed (e.g. registry not initialized, manifest
+      // malformed). Don't crash calibration — log a warning and write the
+      // empty {} scorecard. Matches the v0.36.1.0 baseline behavior so
+      // R1 byte-identical regression survives the widening.
+      result.warnings.push(
+        `domain_scorecards_aggregation_failed: ${err instanceof Error ? err.message : String(err)}`,
+      );
+    }
+
     await engine.executeRaw(
       `INSERT INTO calibration_profiles (
          source_id, holder, generated_at, published,
@@ -330,10 +367,10 @@ class CalibrationProfilePhase extends BaseCyclePhase {
         scorecard.accuracy,
         scorecard.partial_rate,
         gradeCompletion,
-        // domain_scorecards: per-domain breakdown placeholder — v0.36.1.0
-        // ships with the overall scorecard only; per-domain comes when
-        // batchGetTakesScorecards (F12) lands in Lane C.
-        JSON.stringify({}),
+        // v0.41 T10 — domain_scorecards JSONB populated by the
+        // domain-aggregators pass above. Empty {} when no active pack
+        // declares calibration_domains (R1 byte-identical regression).
+        JSON.stringify(domainScorecards),
         result.pattern_statements,
         result.voice_gate_passed,
         result.voice_gate_attempts,
diff --git a/test/domain-aggregators.test.ts b/test/domain-aggregators.test.ts
new file mode 100644
index 000000000..27f7b9ada
--- /dev/null
+++ b/test/domain-aggregators.test.ts
@@ -0,0 +1,377 @@
+// v0.41 T10 — calibration domain aggregators.
+//
+// Tests the per-aggregator SQL shape + the R1 IRON-RULE byte-identical
+// regression (empty {} JSONB when no active pack declares domains).
+//
+// Covers all 4 aggregator kinds (scalar_brier, weighted_brier,
+// count_based, cluster_summary) against real PGLite. Seeds takes +
+// take_domain_assignments + pages and asserts the expected scorecard
+// shape comes back.
+
+import { describe, test, expect, beforeAll, afterAll, beforeEach } from 'bun:test';
+import { PGLiteEngine } from '../src/core/pglite-engine.ts';
+import { aggregateDomainScorecards } from '../src/core/calibration/domain-aggregators.ts';
+import { resetPgliteState } from './helpers/reset-pglite.ts';
+import type { CalibrationDomain } from '../src/core/schema-pack/manifest-v1.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 seedTakeWithAssignment(
+  slug: string,
+  pageType: string,
+  takeOpts: {
+    weight: number;
+    resolved_outcome: boolean;
+    holder?: string;
+    sourceId?: string;
+    rowNum?: number;
+  },
+  assignmentOpts: {
+    domain: string;
+    pack: string;
+    confidence?: number;
+  },
+): Promise<void> {
+  const holder = takeOpts.holder ?? 'garry';
+  const sourceId = takeOpts.sourceId ?? 'default';
+  const rowNum = takeOpts.rowNum ?? 1;
+
+  await engine.putPage(slug, {
+    title: slug,
+    type: pageType,
+    compiled_truth: '',
+    frontmatter: {},
+    timeline: '',
+  });
+  const pageRow = await engine.executeRaw<{ id: number }>(
+    `SELECT id FROM pages WHERE slug = $1 AND source_id = $2 LIMIT 1`,
+    [slug, sourceId],
+  );
+  const pageId = pageRow[0].id;
+  await engine.executeRaw(
+    `INSERT INTO takes (page_id, row_num, claim, kind, holder, weight, resolved_outcome, resolved_at, active)
+     VALUES ($1, $2, $3, 'take', $4, $5, $6, now(), TRUE)`,
+    [pageId, rowNum, `claim for ${slug}`, holder, takeOpts.weight, takeOpts.resolved_outcome],
+  );
+  const takeRow = await engine.executeRaw<{ id: number }>(
+    `SELECT id FROM takes WHERE page_id = $1 AND row_num = $2 LIMIT 1`,
+    [pageId, rowNum],
+  );
+  const takeId = takeRow[0].id;
+  await engine.executeRaw(
+    `INSERT INTO take_domain_assignments (take_id, domain, pack, confidence)
+     VALUES ($1, $2, $3, $4)`,
+    [takeId, assignmentOpts.domain, assignmentOpts.pack, assignmentOpts.confidence ?? 1.0],
+  );
+}
+
+describe('v0.41 T10 R1: empty domain list returns {} (byte-identical regression)', () => {
+  test('aggregateDomainScorecards with [] domains returns {}', async () => {
+    const result = await aggregateDomainScorecards(engine, 'garry', [], 'default');
+    expect(result).toEqual({});
+  });
+});
+
+describe('v0.41 T10: scalar_brier aggregator', () => {
+  const domain: CalibrationDomain = {
+    name: 'deal_success',
+    aggregator: 'scalar_brier',
+    page_types: ['deal'],
+  };
+
+  test('returns n:0 + null brier when no takes match', async () => {
+    const result = await aggregateDomainScorecards(engine, 'garry', [domain], 'default');
+    expect(result.deal_success.n).toBe(0);
+    expect(result.deal_success.brier).toBeNull();
+    expect(result.deal_success.accuracy).toBeNull();
+    expect(result.deal_success.aggregator).toBe('scalar_brier');
+    expect(result.deal_success.page_types).toEqual(['deal']);
+  });
+
+  test('computes Brier over resolved deal-attached takes', async () => {
+    // Two takes: one perfect (p=1, outcome=true → sq_err=0), one wrong (p=1, outcome=false → sq_err=1)
+    await seedTakeWithAssignment(
+      'deals/perfect',
+      'deal',
+      { weight: 1.0, resolved_outcome: true, rowNum: 1 },
+      { domain: 'deal_success', pack: 'gbrain-investor' },
+    );
+    await seedTakeWithAssignment(
+      'deals/wrong',
+      'deal',
+      { weight: 1.0, resolved_outcome: false, rowNum: 1 },
+      { domain: 'deal_success', pack: 'gbrain-investor' },
+    );
+
+    const result = await aggregateDomainScorecards(engine, 'garry', [domain], 'default');
+    expect(result.deal_success.n).toBe(2);
+    // Mean of (0, 1) = 0.5
+    expect(result.deal_success.brier).toBeCloseTo(0.5, 2);
+    // Accuracy: weight>=0.5 (true) === outcome → 1 hit, 1 miss → 0.5
+    expect(result.deal_success.accuracy).toBeCloseTo(0.5, 2);
+  });
+
+  test('filters by holder', async () => {
+    await seedTakeWithAssignment(
+      'deals/mine',
+      'deal',
+      { weight: 0.9, resolved_outcome: true, holder: 'garry', rowNum: 1 },
+      { domain: 'deal_success', pack: 'gbrain-investor' },
+    );
+    await seedTakeWithAssignment(
+      'deals/theirs',
+      'deal',
+      { weight: 0.1, resolved_outcome: true, holder: 'alice-example', rowNum: 1 },
+      { domain: 'deal_success', pack: 'gbrain-investor' },
+    );
+
+    const garryResult = await aggregateDomainScorecards(engine, 'garry', [domain], 'default');
+    expect(garryResult.deal_success.n).toBe(1);
+    const aliceResult = await aggregateDomainScorecards(engine, 'alice-example', [domain], 'default');
+    expect(aliceResult.deal_success.n).toBe(1);
+  });
+
+  test('filters by page_types (only matching types counted)', async () => {
+    await seedTakeWithAssignment(
+      'deals/match',
+      'deal',
+      { weight: 0.8, resolved_outcome: true, rowNum: 1 },
+      { domain: 'deal_success', pack: 'gbrain-investor' },
+    );
+    await seedTakeWithAssignment(
+      'people/no-match',
+      'person',
+      { weight: 0.8, resolved_outcome: true, rowNum: 1 },
+      { domain: 'deal_success', pack: 'gbrain-investor' },
+    );
+
+    const result = await aggregateDomainScorecards(engine, 'garry', [domain], 'default');
+    expect(result.deal_success.n).toBe(1);
+  });
+
+  test('ignores unresolved takes', async () => {
+    await engine.putPage('deals/unresolved', {
+      title: 'unresolved',
+      type: 'deal',
+      compiled_truth: '',
+      frontmatter: {},
+      timeline: '',
+    });
+    const pageRow = await engine.executeRaw<{ id: number }>(
+      `SELECT id FROM pages WHERE slug = 'deals/unresolved' LIMIT 1`,
+    );
+    await engine.executeRaw(
+      `INSERT INTO takes (page_id, row_num, claim, kind, holder, weight, active)
+       VALUES ($1, 1, 'unresolved', 'take', 'garry', 0.7, TRUE)`,
+      [pageRow[0].id],
+    );
+    const takeRow = await engine.executeRaw<{ id: number }>(
+      `SELECT id FROM takes WHERE page_id = $1 LIMIT 1`,
+      [pageRow[0].id],
+    );
+    await engine.executeRaw(
+      `INSERT INTO take_domain_assignments (take_id, domain, pack)
+       VALUES ($1, 'deal_success', 'gbrain-investor')`,
+      [takeRow[0].id],
+    );
+
+    const result = await aggregateDomainScorecards(engine, 'garry', [domain], 'default');
+    expect(result.deal_success.n).toBe(0);
+  });
+});
+
+describe('v0.41 T10: weighted_brier aggregator', () => {
+  const domain: CalibrationDomain = {
+    name: 'market_call',
+    aggregator: 'weighted_brier',
+    page_types: ['thesis'],
+  };
+
+  test('high-conviction miss weighted more than low-conviction miss', async () => {
+    // High-conviction miss: weight=0.95 (conviction = ABS(0.95-0.5)*2 = 0.9), outcome=false → sq_err=0.9025
+    await seedTakeWithAssignment(
+      'theses/high-conv-miss',
+      'thesis',
+      { weight: 0.95, resolved_outcome: false, rowNum: 1 },
+      { domain: 'market_call', pack: 'gbrain-investor' },
+    );
+    // Low-conviction hit: weight=0.55 (conviction = 0.1), outcome=true → sq_err=0.2025
+    await seedTakeWithAssignment(
+      'theses/low-conv-hit',
+      'thesis',
+      { weight: 0.55, resolved_outcome: true, rowNum: 1 },
+      { domain: 'market_call', pack: 'gbrain-investor' },
+    );
+
+    const result = await aggregateDomainScorecards(engine, 'garry', [domain], 'default');
+    expect(result.market_call.n).toBe(2);
+    // Weighted mean: (0.9025 * 0.9 + 0.2025 * 0.1) / (0.9 + 0.1) ≈ 0.8325
+    expect(result.market_call.brier).toBeCloseTo(0.8325, 2);
+  });
+
+  test('accuracy independent of conviction weighting', async () => {
+    await seedTakeWithAssignment(
+      'theses/a',
+      'thesis',
+      { weight: 0.9, resolved_outcome: true, rowNum: 1 },
+      { domain: 'market_call', pack: 'gbrain-investor' },
+    );
+    await seedTakeWithAssignment(
+      'theses/b',
+      'thesis',
+      { weight: 0.6, resolved_outcome: true, rowNum: 1 },
+      { domain: 'market_call', pack: 'gbrain-investor' },
+    );
+    const result = await aggregateDomainScorecards(engine, 'garry', [domain], 'default');
+    expect(result.market_call.accuracy).toBeCloseTo(1.0, 2);
+  });
+});
+
+describe('v0.41 T10: count_based aggregator', () => {
+  const domain: CalibrationDomain = {
+    name: 'simple_acc',
+    aggregator: 'count_based',
+    page_types: ['deal'],
+  };
+
+  test('computes accuracy without brier', async () => {
+    await seedTakeWithAssignment(
+      'deals/right',
+      'deal',
+      { weight: 0.8, resolved_outcome: true, rowNum: 1 },
+      { domain: 'simple_acc', pack: 'test' },
+    );
+    await seedTakeWithAssignment(
+      'deals/wrong',
+      'deal',
+      { weight: 0.8, resolved_outcome: false, rowNum: 1 },
+      { domain: 'simple_acc', pack: 'test' },
+    );
+    const result = await aggregateDomainScorecards(engine, 'garry', [domain], 'default');
+    expect(result.simple_acc.n).toBe(2);
+    expect(result.simple_acc.brier).toBeNull();
+    expect(result.simple_acc.accuracy).toBeCloseTo(0.5, 2);
+    expect(result.simple_acc.aggregator).toBe('count_based');
+  });
+});
+
+describe('v0.41 T10: cluster_summary aggregator', () => {
+  const domain: CalibrationDomain = {
+    name: 'concept_themes',
+    aggregator: 'cluster_summary',
+    page_types: ['concept'],
+  };
+
+  test('returns page count + tier histogram', async () => {
+    await engine.putPage('concepts/canon-a', {
+      title: 'a',
+      type: 'concept',
+      compiled_truth: '',
+      frontmatter: { tier: 'T1' },
+      timeline: '',
+    });
+    await engine.putPage('concepts/canon-b', {
+      title: 'b',
+      type: 'concept',
+      compiled_truth: '',
+      frontmatter: { tier: 'T1' },
+      timeline: '',
+    });
+    await engine.putPage('concepts/dev', {
+      title: 'dev',
+      type: 'concept',
+      compiled_truth: '',
+      frontmatter: { tier: 'T2' },
+      timeline: '',
+    });
+    await engine.putPage('concepts/no-tier', {
+      title: 'no-tier',
+      type: 'concept',
+      compiled_truth: '',
+      frontmatter: {},
+      timeline: '',
+    });
+
+    const result = await aggregateDomainScorecards(engine, 'garry', [domain], 'default');
+    expect(result.concept_themes.n).toBe(4);
+    expect(result.concept_themes.brier).toBeNull();
+    expect(result.concept_themes.accuracy).toBeNull();
+    expect(result.concept_themes.aggregator).toBe('cluster_summary');
+    const tiers = (result.concept_themes.extras as { tier_counts: Record<string, number> }).tier_counts;
+    expect(tiers.T1).toBe(2);
+    expect(tiers.T2).toBe(1);
+    expect(tiers.T3).toBe(0);
+    expect(tiers.T4).toBe(0);
+  });
+
+  test('returns n:0 + all-zero tiers when no concepts exist', async () => {
+    const result = await aggregateDomainScorecards(engine, 'garry', [domain], 'default');
+    expect(result.concept_themes.n).toBe(0);
+  });
+});
+
+describe('v0.41 T10: multi-domain aggregation', () => {
+  test('aggregates all declared domains in one call', async () => {
+    await seedTakeWithAssignment(
+      'deals/d1',
+      'deal',
+      { weight: 0.9, resolved_outcome: true, rowNum: 1 },
+      { domain: 'deal_success', pack: 'gbrain-investor' },
+    );
+    await seedTakeWithAssignment(
+      'people/p1',
+      'person',
+      { weight: 0.7, resolved_outcome: true, rowNum: 1 },
+      { domain: 'founder_evaluation', pack: 'gbrain-investor' },
+    );
+
+    const domains: CalibrationDomain[] = [
+      { name: 'deal_success', aggregator: 'scalar_brier', page_types: ['deal'] },
+      { name: 'founder_evaluation', aggregator: 'scalar_brier', page_types: ['person'] },
+      { name: 'empty_domain', aggregator: 'scalar_brier', page_types: ['deal'] },
+    ];
+    const result = await aggregateDomainScorecards(engine, 'garry', domains, 'default');
+
+    expect(Object.keys(result).sort()).toEqual([
+      'deal_success',
+      'empty_domain',
+      'founder_evaluation',
+    ]);
+    expect(result.deal_success.n).toBe(1);
+    expect(result.founder_evaluation.n).toBe(1);
+    expect(result.empty_domain.n).toBe(0);
+  });
+});
+
+describe('v0.41 T10: fail-soft per domain', () => {
+  test('one domain SQL error does NOT block other domains', async () => {
+    // Inject a malformed-but-shape-valid domain. The aggregator JOINs
+    // pages by source_id='default'; a domain pointing at a non-existent
+    // page_type still completes (returns n=0). Errors come from things
+    // like SQL syntax mistakes — harder to trigger via the public API.
+    // For now, assert that an empty page_types-mismatch domain produces
+    // a clean n=0 result without throwing.
+    const domains: CalibrationDomain[] = [
+      { name: 'good', aggregator: 'scalar_brier', page_types: ['deal'] },
+      { name: 'nonexistent', aggregator: 'scalar_brier', page_types: ['__fake_type__'] },
+    ];
+    const result = await aggregateDomainScorecards(engine, 'garry', domains, 'default');
+    expect(result.good).toBeDefined();
+    expect(result.nonexistent).toBeDefined();
+    expect(result.nonexistent.n).toBe(0);
+  });
+});