feat: add isolated historical replay calibration

docker-compose.yml

@@ -92,6 +92,28 @@ services:
     networks:
       - nginx_proxy_manager_default
 
+  replay:
+    build:
+      context: .
+      provenance: false
+    command: node workers/replay-entrypoint.js
+    env_file: .env
+    volumes:
+      - ./config.json:/app/config.json:ro
+      - ./data:/data
+    environment:
+      NODE_ENV: production
+      DURIIN_DB: /data/archive.sqlite
+      INTELLIGENCE_DB: /data/intelligence.sqlite
+      AUTONOMY_REPLAY_POLL_MS: "${AUTONOMY_REPLAY_POLL_MS:-15000}"
+      AUTONOMY_REPLAY_DAILY_BUDGET: "${AUTONOMY_REPLAY_DAILY_BUDGET:-100}"
+      AUTONOMY_REPLAY_WATERMARK_DAYS: "${AUTONOMY_REPLAY_WATERMARK_DAYS:-7}"
+    cpus: "0.50"
+    mem_limit: 768m
+    restart: unless-stopped
+    networks:
+      - nginx_proxy_manager_default
+
   calibration:
     build:
       context: .

package.json

@@ -10,7 +10,8 @@
     "autonomy:init": "node scripts/initialize-autonomy.js",
     "autonomy:allowlist": "node scripts/set-autonomy-instrument.js",
     "autonomy:sync-assets": "node scripts/sync-paper-assets.js",
-    "autonomy:import-legacy": "node scripts/import-legacy-intelligence.js"
+    "autonomy:import-legacy": "node scripts/import-legacy-intelligence.js",
+    "autonomy:replay": "node workers/replay-entrypoint.js"
   },
   "keywords": [],
   "author": "",

public/admin/assets/js/autonomy.js

@@ -79,6 +79,12 @@
     byId("perf-cohorts").textContent = formatNumber(data.calibration?.length || 0);
     if (outcomes) byId("performance-note").textContent = `Measured on ${outcomes} matured predictions. Results remain descriptive until the sample is large enough for stable calibration.`;
 
+    const replay = data.replay;
+    byId("replay-status").textContent = replay ? replay.status : "Not started";
+    byId("replay-articles").textContent = replay ? formatNumber(replay.processed_articles || 0) : "—";
+    byId("replay-evaluations").textContent = replay ? formatNumber(replay.evaluations || 0) : "—";
+    byId("replay-watermark").textContent = replay?.watermark_at ? formatRelative(replay.watermark_at) : "—";
+
     byId("runtime-queue").textContent = `${formatNumber(pendingHistorical, true)} pending`;
     byId("runtime-coordinator").textContent = pendingHistorical ? "Processing" : "Watching";
     if (data.account) {

public/admin/pages/autonomy.html

@@ -128,6 +128,16 @@
       </div>
     </aside>
   </div>
+
+  <section class="panel" aria-label="Historical replay">
+    <div class="section-head"><div><span class="section-index">06</span><h3>Historical replay</h3></div><span class="mode-pill">Isolated from execution</span></div>
+    <div class="performance-facts">
+      <div><span>Run state</span><strong id="replay-status">Starting…</strong></div>
+      <div><span>Articles replayed</span><strong id="replay-articles">—</strong></div>
+      <div><span>Walk-forward evaluations</span><strong id="replay-evaluations">—</strong></div>
+      <div><span>Watermark</span><strong id="replay-watermark">—</strong></div>
+    </div>
+  </section>
 </main>
 
 <div id="toast"><span class="toast-dot"></span><span id="toast-msg"></span></div>

src/autonomy/coordinator.js

@@ -34,9 +34,22 @@ function normalizeProposal(raw, { informationCutoff, model = 'unknown', promptVe
   };
 }
 
-function verifyEvidence(archiveDb, articleIds) {
+function verifyEvidence(archiveDb, articleIds, informationCutoff = null) {
   const placeholders = articleIds.map(() => '?').join(',');
-  const rows = archiveDb.prepare(`SELECT id FROM articles WHERE id IN (${placeholders})`).all(...articleIds);
+  // A replay must only see material which existed at its information cutoff.
+  // Live proposals retain the simpler existence check.
+  const cutoffClause = informationCutoff ? ' AND datetime(COALESCE(pub_date_effective, pub_date, ingested_at)) <= datetime(?)' : '';
+  let rows;
+  try {
+    rows = archiveDb.prepare(`SELECT id FROM articles WHERE id IN (${placeholders})${cutoffClause}`)
+      .all(...articleIds, ...(informationCutoff ? [informationCutoff] : []));
+  } catch (error) {
+    // Minimal/test archives may not retain publication metadata.  A production
+    // replay archive is required to have it, so this fallback is only for the
+    // existing live evidence contract.
+    if (informationCutoff) throw error;
+    rows = archiveDb.prepare(`SELECT id FROM articles WHERE id IN (${placeholders})`).all(...articleIds);
+  }
   const found = new Set(rows.map((row) => row.id));
   return articleIds.every((id) => found.has(id));
 }
@@ -44,7 +57,7 @@ function verifyEvidence(archiveDb, articleIds) {
 function acceptProposal(intelligenceDb, archiveDb, raw, metadata = {}) {
   const proposal = normalizeProposal(raw, metadata);
   for (const prediction of proposal.predictions) {
-    if (!verifyEvidence(archiveDb, prediction.evidenceArticleIds)) {
+    if (!verifyEvidence(archiveDb, prediction.evidenceArticleIds, metadata.origin === 'replay' ? proposal.informationCutoff : null)) {
       throw new Error(`proposal references missing evidence for ${prediction.instrument}`);
     }
     const instrument = intelligenceDb.prepare(
@@ -60,8 +73,8 @@ function acceptProposal(intelligenceDb, archiveDb, raw, metadata = {}) {
   const insertPrediction = intelligenceDb.prepare(`
       INSERT INTO autonomy_predictions
       (proposal_id, event_id, instrument, direction, event_type, causal_channel,
-       horizon_days, information_cutoff, evidence_article_ids, invalidation_condition, learning_eligible, strategy_version)
-    VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+       horizon_days, information_cutoff, evidence_article_ids, invalidation_condition, learning_eligible, strategy_version, origin, replay_run_id)
+    VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
   `);
   const tx = intelligenceDb.transaction(() => {
     const proposalResult = insert.run(metadata.eventId || null, JSON.stringify(proposal), proposal.informationCutoff,
@@ -70,7 +83,8 @@ function acceptProposal(intelligenceDb, archiveDb, raw, metadata = {}) {
       insertPrediction.run(proposalResult.lastInsertRowid, metadata.eventId || null, prediction.instrument,
         prediction.direction, prediction.eventType, prediction.causalChannel, prediction.horizonDays,
         proposal.informationCutoff, JSON.stringify(prediction.evidenceArticleIds), prediction.invalidationCondition,
-        metadata.learningEligible ? 1 : 0, metadata.strategyVersion || 'autonomy-1');
+        metadata.learningEligible ? 1 : 0, metadata.strategyVersion || 'autonomy-1',
+        metadata.origin || 'live', metadata.replayRunId || null);
     }
     return Number(proposalResult.lastInsertRowid);
   });

src/autonomy/schema.js

@@ -1,4 +1,4 @@
-const AUTONOMY_SCHEMA_VERSION = 1;
+const AUTONOMY_SCHEMA_VERSION = 2;
 
 function initAutonomySchema(db) {
   db.exec(`
@@ -178,12 +178,52 @@ function initAutonomySchema(db) {
       captured_at TEXT NOT NULL DEFAULT (datetime('now'))
     );
 
+    -- Historical replay is a separate evidence path.  It deliberately never
+    -- writes to autonomy_decisions or order intents.
+    CREATE TABLE IF NOT EXISTS autonomy_replay_runs (
+      id INTEGER PRIMARY KEY AUTOINCREMENT,
+      status TEXT NOT NULL DEFAULT 'running'
+        CHECK (status IN ('running', 'paused', 'complete', 'superseded', 'failed')),
+      start_at TEXT,
+      watermark_at TEXT,
+      cursor_article_id INTEGER NOT NULL DEFAULT 0,
+      cursor_effective_at TEXT,
+      processed_articles INTEGER NOT NULL DEFAULT 0,
+      strategy_version TEXT NOT NULL,
+      prompt_version TEXT NOT NULL,
+      coordinator_model TEXT,
+      price_provider TEXT NOT NULL DEFAULT 'yahoo',
+      created_at TEXT NOT NULL DEFAULT (datetime('now')),
+      updated_at TEXT NOT NULL DEFAULT (datetime('now')),
+      completed_at TEXT,
+      last_error TEXT
+    );
+    CREATE INDEX IF NOT EXISTS idx_autonomy_replay_runs_active
+      ON autonomy_replay_runs(status, cursor_article_id);
+
+    CREATE TABLE IF NOT EXISTS autonomy_replay_evaluations (
+      prediction_id INTEGER PRIMARY KEY REFERENCES autonomy_predictions(id),
+      replay_run_id INTEGER NOT NULL REFERENCES autonomy_replay_runs(id),
+      snapshot_cutoff TEXT NOT NULL,
+      sample_size INTEGER NOT NULL,
+      action TEXT NOT NULL CHECK (action IN ('BUY', 'SELL', 'HOLD', 'ABSTAIN')),
+      calibrated_probability REAL,
+      expected_excess_return REAL,
+      rationale TEXT NOT NULL,
+      created_at TEXT NOT NULL DEFAULT (datetime('now'))
+    );
+
     INSERT OR IGNORE INTO autonomy_schema(version) VALUES (${AUTONOMY_SCHEMA_VERSION});
   `);
   for (const statement of [
     'ALTER TABLE autonomy_order_intents ADD COLUMN attempts INTEGER NOT NULL DEFAULT 0',
     'ALTER TABLE autonomy_order_intents ADD COLUMN last_error TEXT',
     'ALTER TABLE autonomy_predictions ADD COLUMN learning_eligible INTEGER NOT NULL DEFAULT 0',
+    "ALTER TABLE autonomy_predictions ADD COLUMN origin TEXT NOT NULL DEFAULT 'live'",
+    'ALTER TABLE autonomy_predictions ADD COLUMN replay_run_id INTEGER',
+    'ALTER TABLE autonomy_replay_runs ADD COLUMN cursor_effective_at TEXT',
+    "ALTER TABLE autonomy_calibration_snapshots ADD COLUMN source TEXT NOT NULL DEFAULT 'live'",
+    'ALTER TABLE autonomy_calibration_snapshots ADD COLUMN replay_run_id INTEGER',
   ]) {
     try { db.exec(statement); } catch (_) {}
   }

src/routes/admin.js

@@ -174,7 +174,9 @@ async function adminRoutes(fastify) {
     const outcomeSummary = intelligenceDb.prepare(`
       SELECT COUNT(*) AS total, SUM(direction_correct) AS correct,
              AVG(excess_return) AS average_excess_return
-      FROM autonomy_outcomes
+      FROM autonomy_outcomes o
+      JOIN autonomy_predictions p ON p.id = o.prediction_id
+      WHERE p.origin = 'live'
     `).get();
     const instruments = intelligenceDb.prepare(`
       SELECT COUNT(*) AS count FROM autonomy_instruments WHERE active=1 AND tradable=1
@@ -214,6 +216,18 @@ async function adminRoutes(fastify) {
              expected_excess_return, lower_return, upper_return, created_at
       FROM autonomy_calibration_snapshots ORDER BY id DESC LIMIT 8
     `).all();
+    const replay = intelligenceDb.prepare(`
+      SELECT r.id, r.status, r.watermark_at, r.cursor_article_id, r.cursor_effective_at,
+             r.processed_articles, r.updated_at,
+             SUM(CASE WHEN p.status = 'resolved' THEN 1 ELSE 0 END) AS resolved_predictions,
+             COUNT(p.id) AS predictions,
+             SUM(o.direction_correct) AS correct_predictions,
+             (SELECT COUNT(*) FROM autonomy_replay_evaluations e WHERE e.replay_run_id = r.id) AS evaluations
+      FROM autonomy_replay_runs r
+      LEFT JOIN autonomy_predictions p ON p.replay_run_id = r.id
+      LEFT JOIN autonomy_outcomes o ON o.prediction_id = p.id
+      GROUP BY r.id ORDER BY r.id DESC LIMIT 1
+    `).get() || null;
 
     return {
       enabled: true,
@@ -232,6 +246,7 @@ async function adminRoutes(fastify) {
       latestOrders,
       account,
       calibration,
+      replay,
       generatedAt: new Date().toISOString(),
     };
   });

test/autonomy.test.js

@@ -53,6 +53,26 @@ test('accepted proposal preserves evidence and creates immutable prediction', ()
   assert.deepEqual(JSON.parse(intelligence.prepare('SELECT evidence_article_ids FROM autonomy_predictions').get().evidence_article_ids), [7]);
 });
 
+test('replay evidence cannot look beyond its information cutoff and remains non-executable', () => {
+  const archive = new Database(':memory:');
+  archive.exec('CREATE TABLE articles (id INTEGER PRIMARY KEY, pub_date_effective TEXT, pub_date TEXT, ingested_at TEXT)');
+  archive.prepare("INSERT INTO articles VALUES (7, '2020-01-01T00:00:00Z', NULL, '2020-01-01T00:00:00Z')").run();
+  const intelligence = new Database(':memory:');
+  initAutonomySchema(intelligence);
+  intelligence.prepare("INSERT INTO autonomy_instruments(symbol, broker, active, tradable) VALUES ('NVDA', 'test', 1, 1)").run();
+  assert.throws(() => acceptProposal(intelligence, archive, {
+    predictions: [{ instrument: 'NVDA', direction: 'positive', event_type: 'earnings', horizon_days: 10, evidence_article_ids: [7] }],
+  }, { informationCutoff: '2019-12-31T00:00:00Z', origin: 'replay', replayRunId: 1 }), /missing evidence/);
+  const proposal = intelligence.prepare("INSERT INTO autonomy_proposals(payload, information_cutoff, status) VALUES ('{}', datetime('now'), 'accepted')").run();
+  const prediction = intelligence.prepare(`INSERT INTO autonomy_predictions
+    (proposal_id, instrument, direction, event_type, horizon_days, information_cutoff, evidence_article_ids, strategy_version, origin)
+    VALUES (?, 'NVDA', 'positive', 'test', 10, datetime('now'), '[7]', 'test', 'replay')`).run(proposal.lastInsertRowid);
+  intelligence.prepare("INSERT INTO autonomy_decisions(prediction_id, action, rationale, strategy_version) VALUES (?, 'BUY', 'test', 'test')").run(prediction.lastInsertRowid);
+  const executable = intelligence.prepare(`SELECT d.id FROM autonomy_decisions d JOIN autonomy_predictions p ON p.id=d.prediction_id
+    WHERE d.action IN ('BUY','SELL') AND p.origin='live'`).all();
+  assert.equal(executable.length, 0);
+});
+
 test('calibration and policy abstain on insufficient evidence', () => {
   const calibration = calibrateOutcomes([
     { excess_return: 0.02, direction_correct: 1 },

workers/calibrationWorker.js

@@ -11,7 +11,7 @@ function refreshCalibration(db, version = `cal-${Date.now()}`) {
     SELECT p.direction, p.event_type, p.horizon_days, o.*
     FROM autonomy_predictions p
     JOIN autonomy_outcomes o ON o.prediction_id = p.id
-    WHERE p.status = 'resolved' AND p.learning_eligible = 1
+    WHERE p.status = 'resolved' AND p.learning_eligible = 1 AND p.origin = 'live'
   `).all().reduce((map, row) => {
     const key = cohortKey({ direction: row.direction, eventType: row.event_type, horizonDays: row.horizon_days });
     if (!map.has(key)) map.set(key, []);
@@ -21,8 +21,8 @@ function refreshCalibration(db, version = `cal-${Date.now()}`) {
   const insert = db.prepare(`
     INSERT INTO autonomy_calibration_snapshots
       (cohort_key, sample_size, effective_sample_size, directional_probability,
-       expected_excess_return, lower_return, upper_return, parent_cohort_key, version)
-    VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)
+       expected_excess_return, lower_return, upper_return, parent_cohort_key, version, source, replay_run_id)
+    VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, 'live', NULL)
   `);
   const tx = db.transaction(() => {
     for (const [key, rows] of groups) {
@@ -40,7 +40,7 @@ function createDecisions(db, strategyVersion = 'autonomy-1') {
   const predictions = db.prepare(`
     SELECT p.* FROM autonomy_predictions p
     LEFT JOIN autonomy_decisions d ON d.prediction_id = p.id
-    WHERE d.prediction_id IS NULL AND p.status = 'open'
+    WHERE d.prediction_id IS NULL AND p.status = 'open' AND p.origin = 'live'
   `).all();
   const latest = db.prepare(`
     SELECT * FROM autonomy_calibration_snapshots
@@ -68,6 +68,44 @@ function createDecisions(db, strategyVersion = 'autonomy-1') {
   return created;
 }
 
+// Replay evaluations are walk-forward: each historical prediction is scored
+// against calibration data that had matured strictly before its cutoff.  They
+// are stored in their own ledger, never in autonomy_decisions.
+function refreshReplayEvaluations(db) {
+  const predictions = db.prepare(`
+    SELECT p.*, o.excess_return, o.direction_correct
+    FROM autonomy_predictions p JOIN autonomy_outcomes o ON o.prediction_id = p.id
+    LEFT JOIN autonomy_replay_evaluations e ON e.prediction_id = p.id
+    WHERE p.origin = 'replay' AND p.status = 'resolved' AND e.prediction_id IS NULL
+    ORDER BY datetime(p.information_cutoff), p.id LIMIT 200
+  `).all();
+  const prior = db.prepare(`
+    SELECT p.direction, p.event_type, p.horizon_days, o.*
+    FROM autonomy_predictions p JOIN autonomy_outcomes o ON o.prediction_id = p.id
+    WHERE p.origin = 'replay' AND p.status = 'resolved'
+      AND datetime(p.information_cutoff, '+' || p.horizon_days || ' days') < datetime(?)
+  `);
+  const insert = db.prepare(`
+    INSERT INTO autonomy_replay_evaluations
+      (prediction_id, replay_run_id, snapshot_cutoff, sample_size, action, calibrated_probability, expected_excess_return, rationale)
+    VALUES (?, ?, ?, ?, ?, ?, ?, ?)
+  `);
+  const tx = db.transaction(() => {
+    for (const prediction of predictions) {
+      const key = cohortKey({ direction: prediction.direction, eventType: prediction.event_type, horizonDays: prediction.horizon_days });
+      const rows = prior.all(prediction.information_cutoff).filter((row) =>
+        cohortKey({ direction: row.direction, eventType: row.event_type, horizonDays: row.horizon_days }) === key);
+      const calibration = rows.length ? calibrateOutcomes(rows) : null;
+      const decision = calibration ? decide({ ...calibration, direction: prediction.direction }, { minSampleSize: 30 })
+        : { action: 'ABSTAIN', rationale: 'walk-forward calibration unavailable' };
+      insert.run(prediction.id, prediction.replay_run_id, prediction.information_cutoff, rows.length, decision.action,
+        calibration?.directionalProbability || null, calibration?.expectedExcessReturn || null, decision.rationale);
+    }
+  });
+  tx();
+  return predictions.length;
+}
+
 async function runCalibrationWorker({ intelligencePath, pollMs = 60000, workerId = `calibration-${os.hostname()}-${process.pid}` } = {}) {
   const db = new Database(intelligencePath);
   db.pragma('journal_mode = WAL');
@@ -78,7 +116,8 @@ async function runCalibrationWorker({ intelligencePath, pollMs = 60000, workerId
       const state = db.prepare('SELECT COUNT(*) AS count, COALESCE(MAX(prediction_id), 0) AS max_id FROM autonomy_outcomes').get();
       const groups = refreshCalibration(db, `cal-${state.count}-${state.max_id}`);
       const decisions = createDecisions(db);
-      if (groups || decisions) console.log(`[${workerId}] calibration groups=${groups} decisions=${decisions}`);
+      const replayEvaluations = refreshReplayEvaluations(db);
+      if (groups || decisions || replayEvaluations) console.log(`[${workerId}] calibration groups=${groups} decisions=${decisions} replay_evaluations=${replayEvaluations}`);
     } catch (error) {
       console.error(`[${workerId}] calibration error:`, error.message);
     }
@@ -86,4 +125,4 @@ async function runCalibrationWorker({ intelligencePath, pollMs = 60000, workerId
   }
 }
 
-module.exports = { refreshCalibration, createDecisions, runCalibrationWorker };
+module.exports = { refreshCalibration, createDecisions, refreshReplayEvaluations, runCalibrationWorker };

workers/executionWorker.js

@@ -51,8 +51,9 @@ async function runExecutionWorker({ intelligencePath, pollMs = 10000, mode = 'sh
     }
     const decisions = db.prepare(`
       SELECT d.id FROM autonomy_decisions d
+      JOIN autonomy_predictions p ON p.id = d.prediction_id
       LEFT JOIN autonomy_order_intents oi ON oi.decision_id = d.id
-      WHERE oi.id IS NULL AND d.action IN ('BUY', 'SELL')
+      WHERE oi.id IS NULL AND d.action IN ('BUY', 'SELL') AND p.origin = 'live'
       ORDER BY d.created_at ASC LIMIT 25
     `).all();
     for (const decision of decisions) {

workers/outcomeAutonomyWorker.js

@@ -20,7 +20,9 @@ function httpGet(url) {
 }
 
 async function history(symbol) {
-  const url = `https://query1.finance.yahoo.com/v8/finance/chart/${encodeURIComponent(symbol)}?range=10y&interval=1d`;
+  // GDELT backfills predate the normal rolling quote window.  Use an explicit
+  // point-in-time range so replay outcomes do not silently become unresolvable.
+  const url = `https://query1.finance.yahoo.com/v8/finance/chart/${encodeURIComponent(symbol)}?period1=946684800&period2=${Math.floor(Date.now() / 1000)}&interval=1d`;
   const body = JSON.parse(await httpGet(url));
   const result = body?.chart?.result?.[0];
   if (!result) return [];

workers/replay-entrypoint.js

@@ -0,0 +1,8 @@
+const path = require('path');
+const { runReplayWorker } = require('./replayWorker');
+
+runReplayWorker({
+  archivePath: process.env.DURIIN_DB || path.resolve('/data/archive.sqlite'),
+  intelligencePath: process.env.INTELLIGENCE_DB || path.resolve('/data/intelligence.sqlite'),
+  pollMs: Number(process.env.AUTONOMY_REPLAY_POLL_MS) || 15000,
+}).catch((error) => { console.error('[replay] fatal:', error); process.exit(1); });

workers/replayWorker.js

@@ -0,0 +1,113 @@
+const os = require('os');
+const fs = require('fs');
+const path = require('path');
+const Database = require('better-sqlite3');
+const { initAutonomySchema } = require('../src/autonomy/schema');
+const { enqueueJob, leaseNextJob, completeJob, failJob } = require('../src/autonomy/jobs');
+const { callCoordinator } = require('../src/autonomy/llm');
+const { acceptProposal, recordRejectedProposal } = require('../src/autonomy/coordinator');
+
+function sleep(ms) { return new Promise((resolve) => setTimeout(resolve, ms)); }
+
+function loadConfig() {
+  const configPath = path.resolve(process.env.DURIIN_CONFIG || path.join(__dirname, '..', 'config.json'));
+  const raw = JSON.parse(fs.readFileSync(configPath, 'utf8'));
+  require('dotenv').config({ path: path.resolve(path.dirname(configPath), '.env') });
+  raw.openRouter = { ...(raw.openRouter || {}) };
+  if (process.env.OPEN_ROUTER_API_KEY) raw.openRouter.apiKey = process.env.OPEN_ROUTER_API_KEY;
+  if (process.env.OPEN_ROUTER_LLM_MODEL) raw.openRouter.llmModel = process.env.OPEN_ROUTER_LLM_MODEL;
+  return raw;
+}
+
+function articleTimeColumns(archiveDb) {
+  const columns = new Set(archiveDb.prepare('PRAGMA table_info(articles)').all().map((row) => row.name));
+  const candidates = ['pub_date_effective', 'pub_date', 'ingested_at'].filter((name) => columns.has(name));
+  if (!candidates.length) throw new Error('archive articles need publication or ingestion timestamps for replay');
+  return { columns, effective: `COALESCE(${candidates.join(', ')})` };
+}
+
+function replayPrompt(article) {
+  return `Historical evidence cutoff: ${article.effective_at}\n\n` +
+    `[Evidence 1] article_id=${article.id}\nTitle: ${article.title || ''}\n${String(article.content || article.description || '').slice(0, 6000)}\n\n` +
+    `Return JSON only in this shape:\n${JSON.stringify({ predictions: [{
+      instrument: 'NVDA', direction: 'positive|negative', event_type: 'stable_enum',
+      causal_channel: 'short description', horizon_days: 10, evidence_article_ids: [123],
+      invalidation_condition: 'condition',
+    }] }, null, 2)}\n\n` +
+    'Use only this dated evidence. Return an empty predictions array when there is no clear, tradable hypothesis. Never include probabilities, returns, confidence, position sizes, or actions.';
+}
+
+function activeRun(db, config) {
+  let run = db.prepare("SELECT * FROM autonomy_replay_runs WHERE status = 'running' ORDER BY id DESC LIMIT 1").get();
+  if (run) return run;
+  const watermarkDays = Math.max(1, Number(process.env.AUTONOMY_REPLAY_WATERMARK_DAYS) || 7);
+  const result = db.prepare(`
+    INSERT INTO autonomy_replay_runs (watermark_at, strategy_version, prompt_version, coordinator_model)
+    VALUES (datetime('now', ?), 'autonomy-1', 'replay-coordinator-1', ?)
+  `).run(`-${watermarkDays} days`, config.openRouter.llmModel || 'unknown');
+  return db.prepare('SELECT * FROM autonomy_replay_runs WHERE id = ?').get(result.lastInsertRowid);
+}
+
+function scheduleNext(db, archiveDb, run) {
+  const { columns, effective } = articleTimeColumns(archiveDb);
+  const content = columns.has('content') ? "content IS NOT NULL AND content != ''" : '1=1';
+  const indexFilter = columns.has('is_index_page') ? 'AND (is_index_page = 0 OR is_index_page IS NULL)' : '';
+  const cursorFilter = run.cursor_effective_at
+    ? `AND (datetime(${effective}) > datetime(?) OR (datetime(${effective}) = datetime(?) AND id > ?))`
+    : '';
+  const params = [run.watermark_at];
+  if (run.cursor_effective_at) params.push(run.cursor_effective_at, run.cursor_effective_at, run.cursor_article_id);
+  const article = archiveDb.prepare(`
+    SELECT id, title, description, content, ${effective} AS effective_at
+    FROM articles
+    WHERE ${content} ${indexFilter} AND datetime(${effective}) <= datetime(?) ${cursorFilter}
+    ORDER BY datetime(${effective}) ASC, id ASC LIMIT 1
+  `).get(...params);
+  if (!article) return null;
+  enqueueJob(db, {
+    jobType: 'replay_article', lane: 'historical', priority: 1, entityType: 'article', entityId: article.id,
+    idempotencyKey: `replay:${run.id}:article:${article.id}`,
+  });
+  return article;
+}
+
+async function runReplayWorker({ archivePath, intelligencePath, workerId = `replay-${os.hostname()}-${process.pid}`, pollMs = 15000 } = {}) {
+  const archiveDb = new Database(archivePath, { readonly: true });
+  const db = new Database(intelligencePath);
+  db.pragma('journal_mode = WAL');
+  db.pragma('busy_timeout = 5000');
+  initAutonomySchema(db);
+  const config = loadConfig();
+  const dailyBudget = Math.max(1, Number(process.env.AUTONOMY_REPLAY_DAILY_BUDGET) || 100);
+  while (true) {
+    try {
+      const completedToday = db.prepare("SELECT COUNT(*) AS count FROM autonomy_jobs WHERE job_type='replay_article' AND status='complete' AND date(completed_at) = date('now')").get().count;
+      if (completedToday >= dailyBudget) { await sleep(Math.max(pollMs, 60000)); continue; }
+      const run = activeRun(db, config);
+      scheduleNext(db, archiveDb, run);
+      const job = leaseNextJob(db, workerId, 300, ['replay_article']);
+      if (!job) { await sleep(pollMs); continue; }
+      try {
+        const { effective } = articleTimeColumns(archiveDb);
+        const article = archiveDb.prepare(`SELECT id, title, description, content, ${effective} AS effective_at FROM articles WHERE id=?`).get(job.entity_id);
+        if (!article || !article.effective_at) throw new Error(`replay article ${job.entity_id} is unavailable`);
+        const raw = await callCoordinator(config, replayPrompt(article));
+        try {
+          acceptProposal(db, archiveDb, raw, {
+            informationCutoff: article.effective_at, model: config.openRouter.llmModel || 'unknown',
+            promptVersion: 'replay-coordinator-1', strategyVersion: 'autonomy-1', learningEligible: false,
+            origin: 'replay', replayRunId: run.id,
+          });
+        } catch (validationError) {
+          recordRejectedProposal(db, raw, { informationCutoff: article.effective_at, model: config.openRouter.llmModel || 'unknown', promptVersion: 'replay-coordinator-1' }, validationError.message);
+        }
+        db.prepare(`UPDATE autonomy_replay_runs SET cursor_article_id=?, cursor_effective_at=?, processed_articles=processed_articles+1, updated_at=datetime('now') WHERE id=?`)
+          .run(article.id, article.effective_at, run.id);
+        completeJob(db, job.id, workerId);
+      } catch (error) { failJob(db, job.id, workerId, error); }
+    } catch (error) { console.error(`[${workerId}] replay error:`, error.message); }
+    await sleep(pollMs);
+  }
+}
+
+module.exports = { articleTimeColumns, replayPrompt, scheduleNext, runReplayWorker };