// claude-mem-lite: Background LLM workers for episode extraction and session summaries
// Extracted from hook.mjs for testability and reduced complexity

import { basename } from 'path';
import { existsSync, readFileSync, unlinkSync, readdirSync } from 'fs';
import {
  jaccardSimilarity, truncate, clampImportance, computeRuleImportance,
  inferProject, parseJsonFromLLM,
  computeMinHash, estimateJaccardFromMinHash, cjkBigrams, EDIT_TOOLS, LOW_SIGNAL_TITLE, debugCatch, debugLog, OBS_BM25,
  getCurrentBranch, notLowSignalTitleClause,
} from './utils.mjs';
import { acquireLLMSlot, releaseLLMSlot } from './hook-semaphore.mjs';
import { scrubRecord } from './lib/scrub-record.mjs';
import { getVocabulary, computeVector } from './tfidf.mjs';
import {
  RUNTIME_DIR, DEDUP_WINDOW_MS, RELATED_OBS_WINDOW_MS,
  sessionFile, getSessionId, openDb, callLLM, sleep,
} from './hook-shared.mjs';
import { EVENT_TYPES, saveEvent } from './lib/activity.mjs';
import { isNoiseObservation, capNoiseImportance, isLowYieldChangeObs } from './lib/low-signal-patterns.mjs';

// T9: memdir-incompatible types live in the `events` table, not `observations`.
// Set lookup is O(1) — authoritative source is lib/activity.mjs::EVENT_TYPES.
const EVENT_TYPE_SET = new Set(EVENT_TYPES);

// ─── Lesson-retry stats (v29 / B2) ──────────────────────────────────────────
//
// Persists the {attempts, recovered} counters per UTC date_bucket. Aggregate
// table (not per-row) — the question being answered is "is the retry path
// paying off in aggregate?", per-obs detail isn't needed.

/** Convert a Date (or now) to a YYYY-MM-DD UTC bucket. */
function dateBucketUtc(date = new Date()) {
  const y = date.getUTCFullYear();
  const m = String(date.getUTCMonth() + 1).padStart(2, '0');
  const d = String(date.getUTCDate()).padStart(2, '0');
  return `${y}-${m}-${d}`;
}

/**
 * UPSERT a single retry-attempt outcome into lesson_retry_stats. attempts
 * always +1; recovered +1 only when the retry returned a non-low-signal lesson.
 * @param {Database} db open better-sqlite3 handle
 * @param {boolean} recovered whether the retry recovered a usable lesson
 * @param {string} [bucket] optional override (test path); defaults to today UTC
 */
export function recordRetryAttempt(db, recovered, bucket = dateBucketUtc()) {
  // Single-statement atomic UPSERT (post-review fix Important #4). The
  // previous two-statement form let a concurrent reader observe the
  // {attempts:0, recovered:0} intermediate state between the INSERT OR
  // IGNORE and the UPDATE; ON CONFLICT collapses this to one statement
  // that runs entirely under the writer lock with no observable middle
  // state. SQLite ≥3.24 supports the syntax (better-sqlite3 ships ≥3.30).
  db.prepare(`
    INSERT INTO lesson_retry_stats (date_bucket, attempts, recovered)
    VALUES (?, 1, ?)
    ON CONFLICT(date_bucket) DO UPDATE SET
      attempts = attempts + 1,
      recovered = recovered + excluded.recovered
  `).run(bucket, recovered ? 1 : 0);
}

/**
 * Read recent retry-stats rows. Returns rows ordered by date_bucket DESC,
 * limited to the last `days` UTC buckets (using string comparison; safe for
 * YYYY-MM-DD lexicographic order).
 */
export function readRetryStats(db, days = 30) {
  const cutoff = new Date(Date.now() - days * 86400000);
  return db.prepare(
    `SELECT date_bucket, attempts, recovered FROM lesson_retry_stats
     WHERE date_bucket >= ? ORDER BY date_bucket DESC`
  ).all(dateBucketUtc(cutoff));
}

// ─── Save Observation to DB ─────────────────────────────────────────────────

/** Build the FTS5 text field from observation data (concepts + facts + searchAliases + CJK bigrams). */
function buildFtsTextField(obs) {
  const conceptsText = Array.isArray(obs.concepts) ? obs.concepts.join(' ') : '';
  const factsText = Array.isArray(obs.facts) ? obs.facts.join(' ') : '';
  const aliasesText = obs.searchAliases || '';
  const bigramText = cjkBigrams((obs.title || '') + ' ' + (obs.narrative || ''));

  // Degraded fallback: when LLM enrichment is missing, extract lightweight keywords
  // from title + narrative so degraded observations remain FTS-searchable
  let fallbackText = '';
  if (!conceptsText && !factsText && !aliasesText) {
    const raw = (obs.title || '') + ' ' + (obs.narrative || '');
    // Extract file basenames (without extension) as searchable terms
    const fileNames = [...new Set(
      [...raw.matchAll(/\b([\w.-]+\.(?:mjs|js|ts|tsx|jsx|py|rs|go|vue|css|html|json|yaml|yml|md|sh|sql|toml|cfg))\b/g)]
        .map(m => m[1].replace(/\.[^.]+$/, ''))
    )];
    // Extract error keywords from "→ ERROR: ..." patterns
    const errorTerms = raw.split(/→ ERROR[: ]+/).slice(1)
      .map(s => s.split(/[;{[\]"\\|→\n]/)[0].trim())
      .filter(t => t.length >= 4 && t.length <= 50);
    fallbackText = [...fileNames, ...errorTerms].join(' ');
  }

  return { conceptsText, factsText, textField: [conceptsText, factsText, aliasesText, bigramText, fallbackText].filter(Boolean).join(' ') };
}

/**
 * Save an observation to the database with three-tier dedup.
 * @returns {number|null} The saved observation ID, or null if deduped.
 *   Throws on DB error (callers should catch if needed).
 */
export function saveObservation(obs, projectOverride, sessionIdOverride, externalDb) {
  const db = externalDb || openDb();
  if (!db) return null;

  try {
    const now = new Date();
    const project = projectOverride || inferProject();
    const sessionId = sessionIdOverride || getSessionId();

    db.prepare(`
      INSERT OR IGNORE INTO sdk_sessions (content_session_id, memory_session_id, project, started_at, started_at_epoch, status)
      VALUES (?, ?, ?, ?, ?, 'active')
    `).run(sessionId, sessionId, project, now.toISOString(), now.getTime());

    // P0: write-side noise block — LOW_SIGNAL title with no recoverable signal
    // (no lesson, importance<2, empty facts, thin narrative) is dropped before
    // dedup/MinHash/vector work. Opt-out: CLAUDE_MEM_KEEP_LOW_SIGNAL=1.
    if (isNoiseObservation(obs)) {
      debugLog('saveObservation', `dropped noise: ${truncate(obs.title || '', 60)}`);
      return null;
    }

    // v2.47 P0-3: importance cap for LOW_SIGNAL titles that kept the drop gate
    // open via importance>=2 but carry no lesson/facts signal. 341 rows in live
    // DB had imp=3 under these conditions (99.4% noise). Cap to 1 so they
    // enter the 7-day accelerated auto-compress window in hook.mjs.
    const capped = capNoiseImportance(obs);
    if (capped !== (obs.importance ?? 1)) {
      debugLog('saveObservation', `capped imp ${obs.importance}→${capped}: ${truncate(obs.title || '', 60)}`);
      obs.importance = capped;
    }

    // Three-tier dedup — returns null (not throw) for dedup hits
    // Tier 1 (fast): 5-min Jaccard on titles
    const fiveMinAgo = now.getTime() - DEDUP_WINDOW_MS;
    const recent = db.prepare(`
      SELECT title FROM observations
      WHERE project = ? AND created_at_epoch > ?
      ORDER BY created_at_epoch DESC LIMIT 10
    `).all(project, fiveMinAgo);

    if (obs.title && recent.some(r => jaccardSimilarity(r.title, obs.title) > 0.7)) {
      return null; // dedup: Jaccard title match
    }

    // Tier 1.5: Extended title dedup for low-signal degraded titles
    // "Error in X", "Modified X" titles are low-specificity → use longer dedup window
    // 7-day exact match prevents cross-day accumulation of "Modified package.json" noise;
    // 3-day Jaccard catches near-duplicates without blocking legitimately new observations
    const LOW_SIGNAL = LOW_SIGNAL_TITLE;
    if (obs.title && LOW_SIGNAL.test(obs.title)) {
      const sevenDaysAgo = now.getTime() - 7 * 86400000;
      const threeDaysAgo = now.getTime() - 3 * 86400000;
      // Phase 1: exact title match within 7 days
      const exactDup = db.prepare(`
        SELECT 1 FROM observations
        WHERE project = ? AND title = ? AND created_at_epoch > ? AND created_at_epoch <= ?
        LIMIT 1
      `).get(project, obs.title, sevenDaysAgo, fiveMinAgo);
      if (exactDup) return null; // dedup: exact title match
      // Phase 2: Jaccard similarity for near-duplicates (3-day window)
      const extRecent = db.prepare(`
        SELECT title FROM observations
        WHERE project = ? AND created_at_epoch > ? AND created_at_epoch <= ?
        ORDER BY created_at_epoch DESC LIMIT 60
      `).all(project, threeDaysAgo, fiveMinAgo);
      if (extRecent.some(r => jaccardSimilarity(r.title, obs.title) > 0.85)) {
        return null; // dedup: low-signal Jaccard match
      }
    }

    // Tier 2 (slow): MinHash cross-session dedup (7-day window)
    const minhashSig = computeMinHash((obs.title || '') + ' ' + (obs.narrative || ''));
    if (minhashSig) {
      const sevenDaysAgo = now.getTime() - RELATED_OBS_WINDOW_MS;
      const recentSigs = db.prepare(`
        SELECT minhash_sig FROM observations
        WHERE project = ? AND created_at_epoch > ? AND minhash_sig IS NOT NULL
        ORDER BY created_at_epoch DESC LIMIT 200
      `).all(project, sevenDaysAgo);

      if (recentSigs.some(r => estimateJaccardFromMinHash(minhashSig, r.minhash_sig) > 0.8)) {
        return null; // dedup: MinHash similarity match
      }
    }

    const { conceptsText, factsText, textField } = buildFtsTextField(obs);

    // Defense-in-depth: scrub text fields before INSERT. Source is LLM output
    // (Haiku occasionally regurgitates input verbatim — error logs, hashes).
    const safe = scrubRecord('observations', {
      text: textField,
      title: obs.title || '',
      subtitle: obs.subtitle || '',
      narrative: obs.narrative || '',
      concepts: conceptsText,
      facts: factsText,
      lesson_learned: obs.lessonLearned || null,
      search_aliases: obs.searchAliases || null,
    });

    // Atomic: observation INSERT + observation_files + vector in one transaction
    const savedId = db.transaction(() => {
      const result = db.prepare(`
        INSERT INTO observations (memory_session_id, project, text, type, title, subtitle, narrative, concepts, facts, files_read, files_modified, importance, minhash_sig, lesson_learned, search_aliases, branch, created_at, created_at_epoch)
        VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
      `).run(
        sessionId, project,
        safe.text, obs.type, safe.title, safe.subtitle,
        safe.narrative,
        safe.concepts,
        safe.facts,
        JSON.stringify(obs.filesRead || []),
        JSON.stringify(obs.files || []),
        obs.importance ?? 1,
        minhashSig,
        safe.lesson_learned,
        safe.search_aliases,
        getCurrentBranch(),
        now.toISOString(), now.getTime()
      );
      const id = Number(result.lastInsertRowid);

      // Populate observation_files junction table
      if (id && obs.files && obs.files.length > 0) {
        const insertFile = db.prepare('INSERT OR IGNORE INTO observation_files (obs_id, filename) VALUES (?, ?)');
        for (const f of obs.files) {
          if (typeof f === 'string' && f.length > 0) insertFile.run(id, f);
        }
      }

      // Write TF-IDF vector (non-critical — catch inside transaction to avoid rollback)
      try {
        const vocab = getVocabulary(db);
        if (vocab) {
          const vecText = [obs.title || '', obs.narrative || '', (Array.isArray(obs.concepts) ? obs.concepts.join(' ') : '')].filter(Boolean).join(' ');
          const vec = computeVector(vecText, vocab);
          if (vec) {
            db.prepare('INSERT OR REPLACE INTO observation_vectors (observation_id, vector, vocab_version, created_at_epoch) VALUES (?, ?, ?, ?)')
              .run(id, Buffer.from(vec.buffer), vocab.version, Date.now());
          }
        }
      } catch (e) { debugCatch(e, 'saveObservation-vector'); }

      return id;
    })();

    return savedId;
  } finally {
    if (!externalDb) db.close();
  }
}

// ─── obs → summary shape mapping ────────────────────────────────────────────
// handleLLMEpisode's internal `obs` uses camelCase/legacy names (lessonLearned,
// files, filesRead). persistHaikuSummary takes the plan's stable snake_case
// shape. Keep the mapping here so the dispatcher's public signature stays
// clean for external callers that already use the plan shape.
function obsToSummary(obs) {
  return {
    type: obs.type,
    title: obs.title,
    subtitle: obs.subtitle,
    narrative: obs.narrative,
    concepts: obs.concepts,
    facts: obs.facts,
    files_modified: obs.files,
    files_read: obs.filesRead,
    importance: obs.importance,
    lesson_learned: obs.lessonLearned,
    search_aliases: obs.searchAliases,
  };
}

// ─── T9: Haiku Summary Dispatcher (events vs observations routing) ──────────
//
// Routes memdir-incompatible types (the 8 values in EVENT_TYPES) to the
// activity `events` table, and keeps legacy/memdir-aligned types (e.g.
// `change`, which is the only non-event type hook-llm currently emits) on
// the existing observations path.
//
// Input shape (matches the v2.31 MVP plan's stable interface):
//   summary: { type, title, lesson_learned?, narrative?, importance?, files_modified? }
//   ctx:     { project, session_id, preSavedObsId? }
//
// Returns { table: 'events'|'observations', id: number|null }. Callers inspect
// `table` to decide whether follow-up observations-only logic (linking, vector
// refresh) applies.
//
// NOTE: The foreground pre-save in hook.mjs:110/336 intentionally still writes
// to `observations` for immediate visibility. When the background worker
// processes the episode (handleLLMEpisode), it passes the pre-saved id in
// `ctx.preSavedObsId`; this dispatcher then deletes the pre-saved observations
// row and inserts a fresh event for event-typed summaries (upgrade-delete
// semantics). Observations-typed summaries reuse the pre-saved row directly
// (caller handles the UPDATE, since it needs the enriched FTS fields).
export function persistHaikuSummary(db, summary, ctx) {
  if (EVENT_TYPE_SET.has(summary.type)) {
    // Upgrade-delete: the foreground pre-save landed in `observations` with a
    // rule-inferred type; now that Haiku has classified it as an event type,
    // we must remove the stale observations row before inserting the event.
    // Atomic via better-sqlite3 transaction: either both succeed or neither.
    const insertEvent = () => saveEvent(db, {
      project: ctx.project,
      event_type: summary.type,
      title: summary.title,
      body: summary.lesson_learned || summary.narrative || null,
      file_paths: (Array.isArray(summary.files_modified) && summary.files_modified.length > 0)
        ? summary.files_modified
        : null,
      importance: summary.importance ?? 1,
      created_at_epoch: Date.now(),
    });

    if (ctx.preSavedObsId) {
      const id = db.transaction(() => {
        db.prepare(`DELETE FROM observations WHERE id = ?`).run(ctx.preSavedObsId);
        return insertEvent();
      })();
      return { table: 'events', id };
    }

    return { table: 'events', id: insertEvent() };
  }

  // Fallthrough: memdir-compatible / legacy types use the observations path.
  // Map the Haiku/plan field names to saveObservation's expected shape.
  const id = saveObservation({
    type: summary.type,
    title: summary.title,
    subtitle: summary.subtitle || '',
    narrative: summary.narrative || '',
    concepts: summary.concepts || [],
    facts: summary.facts || [],
    files: summary.files_modified || [],
    filesRead: summary.files_read || [],
    importance: summary.importance ?? 1,
    lessonLearned: summary.lesson_learned || null,
    searchAliases: summary.search_aliases || null,
  }, ctx.project, ctx.session_id, db);
  return { table: 'observations', id };
}

// ─── Related Observation Linking ─────────────────────────────────────────────

function linkRelatedObservations(db, savedId, obs, episode) {
  const newObs = db.prepare(`
    SELECT id, title, files_modified, related_ids FROM observations WHERE id = ?
  `).get(savedId);
  if (!newObs) return;

  const candidates = new Set();

  // Strategy 1: FTS5 title similarity (cross-session)
  if (obs.title) {
    const titleTokens = obs.title.replace(/[^a-zA-Z0-9_\s-]/g, ' ').split(/\s+/)
      .filter(t => t.length > 2).slice(0, 5);
    if (titleTokens.length > 0) {
      const ftsQuery = titleTokens.map(t => `"${t.replace(/"/g, '""')}"`).join(' OR ');
      try {
        const ftsMatches = db.prepare(`
          SELECT o.id FROM observations_fts
          JOIN observations o ON observations_fts.rowid = o.id
          WHERE observations_fts MATCH ? AND o.id != ? AND o.project = ?
          ORDER BY ${OBS_BM25}
          LIMIT 5
        `).all(ftsQuery, newObs.id, episode.project);
        for (const m of ftsMatches) candidates.add(m.id);
      } catch (e) { debugCatch(e, 'linkRelated-fts'); }
    }
  }

  // Strategy 2: file overlap (any session, recent observations)
  let newFiles;
  try { newFiles = JSON.parse(newObs.files_modified || '[]'); } catch (e) { debugCatch(e, 'linkRelated-newFiles'); newFiles = []; }
  if (!Array.isArray(newFiles) || !newFiles.every(f => typeof f === 'string')) newFiles = [];
  if (newFiles.length > 0) {
    const recentObs = db.prepare(`
      SELECT id, files_modified FROM observations
      WHERE id != ? AND created_at_epoch > ? AND project = ?
      ORDER BY created_at_epoch DESC LIMIT 50
    `).all(newObs.id, Date.now() - RELATED_OBS_WINDOW_MS, episode.project);
    for (const r of recentObs) {
      let rFiles;
      try { rFiles = JSON.parse(r.files_modified || '[]'); } catch (e) { debugCatch(e, 'linkRelated-rFiles'); rFiles = []; }
      if (!Array.isArray(rFiles) || !rFiles.every(f => typeof f === 'string')) rFiles = [];
      if (rFiles.some(f => newFiles.includes(f))) candidates.add(r.id);
    }
  }

  // Apply bidirectional links (max 5 related)
  if (candidates.size > 0) {
    let newRelated;
    try { newRelated = JSON.parse(newObs.related_ids || '[]'); } catch (e) { debugCatch(e, 'linkRelated-newRelated'); newRelated = []; }
    if (!Array.isArray(newRelated) || !newRelated.every(id => Number.isInteger(id))) newRelated = [];

    for (const relId of [...candidates].slice(0, 5)) {
      if (newRelated.includes(relId)) continue;
      newRelated.push(relId);

      const rel = db.prepare('SELECT related_ids FROM observations WHERE id = ?').get(relId);
      if (rel) {
        let relRelated;
        try { relRelated = JSON.parse(rel.related_ids || '[]'); } catch (e) { debugCatch(e, 'linkRelated-relRelated'); relRelated = []; }
        if (!Array.isArray(relRelated) || !relRelated.every(id => Number.isInteger(id))) relRelated = [];
        if (!relRelated.includes(newObs.id)) {
          relRelated.push(newObs.id);
          db.prepare('UPDATE observations SET related_ids = ? WHERE id = ?').run(JSON.stringify(relRelated.slice(-10)), relId);
        }
      }
    }

    db.prepare('UPDATE observations SET related_ids = ? WHERE id = ?').run(JSON.stringify(newRelated.slice(-10)), newObs.id);
  }
}

// ─── Degraded Title Builder ──────────────────────────────────────────────────
// When LLM is unavailable, build a readable title from episode metadata
// instead of using raw makeEntryDesc output (which contains JSON stdout).

export function buildDegradedTitle(episode) {
  const files = (episode.files || []).filter(Boolean);
  const hasError = episode.entries.some(e => e.isError);
  const hasEdit = episode.entries.some(e => EDIT_TOOLS.has(e.tool));

  // Extract a short error hint from the first error entry's desc
  let errorHint = '';
  if (hasError) {
    const errEntry = episode.entries.find(e => e.isError);
    if (errEntry?.desc) {
      // Extract meaningful error text from "cmd → ERROR: ..." format
      const errMatch = errEntry.desc.match(/→ ERROR: (.{3,80})/);
      if (errMatch) {
        // Clean JSON/noise/tabs/CI-status from the error snippet
        const cleaned = errMatch[1]
          .replace(/\t/g, ' ')
          .replace(/[{"[\]]/g, '')
          .replace(/\\n/g, ' ')
          .replace(/\b(?:in_progress|completed|queued|failure|success|waiting)\b/gi, '')
          .replace(/\s{2,}/g, ' ')
          .trim();
        if (cleaned.length >= 4) errorHint = `: ${truncate(cleaned, 50)}`;
      }
    }
  }

  if (files.length > 0) {
    const uniqueNames = [...new Set(files.map(f => basename(f)))];
    const names = uniqueNames.slice(0, 3).join(', ');
    const suffix = uniqueNames.length > 3 ? ` +${uniqueNames.length - 3} more` : '';
    if (hasError) {
      // Include the triggering command for richer context: "Error: dispatch.mjs — npm test failed"
      const errEntry = episode.entries.find(e => e.isError);
      const cmd = errEntry?.desc?.match(/^(.{3,30}?) →/)?.[1]?.trim();
      const cmdHint = cmd ? ` — ${cmd}` : '';
      return `Error: ${names}${suffix}${errorHint || cmdHint}`;
    }
    if (hasEdit) return `Modified ${names}${suffix}`;
    return `Worked on ${names}${suffix}`;
  }
  // No files: strip raw output (JSON, arrays, long tails) from Bash descriptions
  const desc = episode.entries[0]?.desc || '(no description)';
  return desc.replace(/ → (?:ERROR: )?[[{].*$/, hasError ? ' (error)' : '')
    .replace(/ → .*---EXIT:\d+$/, hasError ? ' (error)' : '')
    .replace(/\t/g, ' ')
    .replace(/\s{2,}/g, ' ')
    .trim();
}

/**
 * Build a rule-based observation from episode metadata for immediate DB persistence.
 * Used as pre-save (before LLM) and as fallback when LLM is unavailable.
 * @param {object} episode Episode with entries, files, filesRead arrays
 * @returns {object} Observation object ready for saveObservation()
 */
export function buildImmediateObservation(episode) {
  const hasError = episode.entries.some(e => e.isError);
  const hasEdit = episode.entries.some(e => EDIT_TOOLS.has(e.tool));
  const readCount = episode.entries.filter(e => e.tool === 'Read' || e.tool === 'Grep').length;
  const isReviewPattern = !hasEdit && !hasError && readCount >= 5;
  const inferredType = hasError ? 'bugfix' : hasEdit ? 'change' : 'discovery';
  const fileList = (episode.files || []).map(f => basename(f)).join(', ') || '(multiple)';

  // Review/research episodes: use a descriptive title with file count
  let title;
  if (isReviewPattern) {
    const allFiles = [...new Set([
      ...(episode.files || []),
      ...(episode.filesRead || []),
    ])].map(f => basename(f));
    const names = allFiles.slice(0, 4).join(', ');
    const suffix = allFiles.length > 4 ? ` +${allFiles.length - 4} more` : '';
    title = truncate(`Reviewed ${allFiles.length} files: ${names}${suffix}`, 120);
  } else {
    title = truncate(buildDegradedTitle(episode), 120);
  }

  const ruleImportance = computeRuleImportance(episode);
  // Low-signal degraded titles ("Modified X", "Worked on X", "Reviewed N files")
  // should not inflate importance. computeRuleImportance's file-name heuristics
  // (schema.*, migration, auth.*, .env, .pem) fire on any matching file in the
  // episode, so a 5-file review that incidentally reads one schema.js triggers
  // imp=3 even though schema.js was one of 5 scanned — not the focus. Combined
  // with a LOW_SIGNAL title (Haiku couldn't extract meaning), we can't justify
  // imp=3; cap at 2 so rule says "notable" but not "critical".
  //
  // Production baseline (2026-04-23, projects--mem): 34/100 discovery/imp=3
  // obs were LOW_SIGNAL titles; 7 change/imp=3 same. Prior cap `rule<=2 → 1`
  // only fired when rule was weak, letting rule=3 leak through. New cap:
  //   isReviewPattern → 2 (was Math.max(2, rule) → rule=3 leaked as 3)
  //   isLowSignal & !review:
  //     rule=3 → 2 (was 3)             — the fix
  //     rule<=2 → 1 (unchanged)        — original cap preserved
  const LOW_SIGNAL = LOW_SIGNAL_TITLE;
  const isLowSignal = LOW_SIGNAL.test(title);
  let importance;
  if (isReviewPattern) {
    // Review titles are auto-generated from file count — can't distinguish
    // "critical file was primary focus" from "one of N files read". Cap at 2.
    importance = 2;
  } else if (isLowSignal) {
    importance = ruleImportance === 3 ? 2 : 1;
  } else {
    importance = ruleImportance;
  }

  // Separate files_modified (from Edit/Write tools) from files_read (everything else)
  const modifiedFiles = new Set();
  const searchedFiles = new Set();
  for (const entry of episode.entries) {
    if (!entry.files) continue;
    if (EDIT_TOOLS.has(entry.tool)) {
      for (const f of entry.files) modifiedFiles.add(f);
    } else {
      for (const f of entry.files) searchedFiles.add(f);
    }
  }
  // Merge bash-tracked reads and search tool files into filesRead
  const allReads = new Set([...(episode.filesRead || []), ...searchedFiles]);
  // Remove files that were both searched AND modified — they're modified
  for (const f of modifiedFiles) allReads.delete(f);

  return {
    type: inferredType,
    title,
    subtitle: fileList,
    narrative: episode.entries.map(e => e.desc).join('; '),
    concepts: [],
    facts: [],
    files: [...modifiedFiles],
    filesRead: [...allReads],
    importance,
  };
}

// ─── Lesson retry prompt (P3) ───────────────────────────────────────────────

/**
 * Build a lesson-focused retry prompt after Haiku's first pass for
 * bugfix/decision returned null/empty/'none'. Narrow ask: one non-obvious
 * insight a future session would benefit from — either root cause (bugfix)
 * or tradeoff (decision).
 *
 * @param {object} episode
 * @param {object} firstPass — parsed first-pass response (title, type, narrative)
 * @returns {{system: string, user: string}} prompt in split form
 */
export function buildLessonRetryPrompt(episode, firstPass) {
  const actionList = episode.entries.map((e, i) =>
    `${i + 1}. [${e.tool}] ${e.desc}${e.isError ? ' (ERROR)' : ''}`
  ).join('\n');
  const typeHint = firstPass.type === 'bugfix'
    ? 'For this bugfix: what was the root cause + how to spot it next time? Example: "FTS5 trigger fires on any UPDATE — wrap access_count writes in try/catch."'
    : 'For this decision: what tradeoff was made + why? Example: "Chose single-source module over schema column because 1 drift point, not 4."';

  const system = `${typeHint}

If the work was purely mechanical with no insight worth remembering, reply {"lesson":null}.
Otherwise reply in 12-280 chars. Do NOT invent a fake lesson, do NOT write the string "none".

Reply ONLY valid JSON, no markdown fences: {"lesson":"..."} or {"lesson":null}`;
  const user = `A ${firstPass.type} episode just completed. First-pass title: "${firstPass.title || 'untitled'}".

Actions:
${actionList}`;
  return { system, user };
}

// ─── Background: LLM Episode Extraction (Tier 2 F) ──────────────────────────

export async function handleLLMEpisode() {
  const tmpFile = process.argv[3];
  if (!tmpFile) return;

  let episode;
  try {
    episode = JSON.parse(readFileSync(tmpFile, 'utf8'));
  } catch {
    try { unlinkSync(tmpFile); } catch {}
    return;
  }

  if (!episode.entries || episode.entries.length === 0) {
    try { unlinkSync(tmpFile); } catch {}
    return;
  }

  // Rate-limit background LLM calls to avoid competing with active sessions
  if (!process.env.CLAUDE_MEM_NO_DELAY) {
    const sessionActive = existsSync(sessionFile());
    const delayMs = sessionActive
      ? 2000 + Math.random() * 3000
      : 500 + Math.random() * 1000;
    debugLog('DEBUG', 'llm-episode', `delay: ${Math.round(delayMs)}ms (session ${sessionActive ? 'active' : 'ended'})`);
    await sleep(delayMs);
  }

  const fileList = episode.files.map(f => basename(f)).join(', ') || '(multiple)';

  // Defense-in-depth (cso F#4): split static instructions (system) from
  // per-call data (user). Episode descriptions and file paths come from tool
  // events; treating them as a separate role + boundary marker reduces the
  // attack surface for memory poisoning via crafted file content.
  const SHARED_OBS_SCHEMA_TAIL =
    `type: pick by strongest signal. decision = explicit tradeoff / "chose X over Y because Z" / rejected an approach (e.g. "Rejected schema migration — single-source module + sync test instead"; "Heterogeneous hook events → heterogeneous context budgets"). bugfix = prior-failing path fixed with a named root cause. feature = new user-visible capability. refactor = behavior unchanged but structure improved. discovery = learned how a system works (read-heavy, no writes). change = routine edit with no new principle (default if unsure and nothing else fits).
Facts: each MUST be (1) atomic—one claim, (2) self-contained—no pronouns, include file/function name, (3) specific—"refreshToken() in auth.ts:45 uses 1h TTL" not "handles tokens"
importance: Be strict — default to 1. 0=pure browsing with zero learning value. 1=routine file edits, standard changes, normal workflow (MOST episodes). 2=notable ONLY if it reveals something non-obvious: error fix with discovered root cause, architectural decision with explicit tradeoff, config change with unexpected side effects. 3=critical: breaking change affecting users, security vulnerability fix, data migration. Ask yourself: "would a future session benefit from knowing this?" — if not, it's importance=1.
lesson_learned: The non-obvious insight a future session would benefit from. Examples: "FTS5 porter stemmer doesn't tokenize CJK — need bigram workaround", "vitest --reporter=verbose hangs on large test suites, use default reporter". Look hard before giving up — most coding episodes contain at least one micro-lesson (an undocumented flag, a surprising default, a debugging shortcut, an unexpected interaction). If literally no insight worth teaching (e.g. version bump, whitespace fix, file rename), output JSON null. Do NOT invent a lesson, do NOT write the strings "none"/"n/a"/"todo"/"tbd"/"-" — those will be discarded as noise.
search_aliases: 2-6 alternative search terms someone might use to find this memory later (include CJK if project uses Chinese)`;

  let prompt;
  if (episode.entries.length === 1) {
    const e = episode.entries[0];
    const system = `Extract a structured observation from this code change. Return ONLY valid JSON, no markdown fences.

JSON: {"type":"decision|bugfix|feature|refactor|discovery|change","title":"concise ≤80 char description","narrative":"what changed, why, and outcome (2-3 sentences)","concepts":["kw1","kw2"],"facts":["fact1","fact2"],"importance":1,"lesson_learned":"non-obvious insight a future session needs, or null","search_aliases":["alt query 1","alt query 2"]}
${SHARED_OBS_SCHEMA_TAIL}`;
    const user = `Tool: ${e.tool}
File: ${episode.files.join(', ') || 'unknown'}
Action: ${e.desc}
Error: ${e.isError ? 'yes' : 'no'}`;
    prompt = { system, user };
  } else {
    const actionList = episode.entries.map((e, i) =>
      `${i + 1}. [${e.tool}] ${e.desc}${e.isError ? ' (ERROR)' : ''}`
    ).join('\n');

    const system = `Summarize this coding episode as ONE coherent observation. Return ONLY valid JSON, no markdown fences.

JSON: {"type":"decision|bugfix|feature|refactor|discovery|change","title":"coherent ≤80 char summary","narrative":"what was done, why, and outcome (3-5 sentences)","concepts":["keyword1","keyword2"],"facts":["specific fact 1","specific fact 2"],"importance":1,"lesson_learned":"non-obvious insight a future session needs, or null","search_aliases":["alt query 1","alt query 2"]}
${SHARED_OBS_SCHEMA_TAIL}`;
    const user = `Project: ${episode.project}
Files: ${fileList}
Actions (${episode.entries.length} total):
${actionList}`;
    prompt = { system, user };
  }

  const ruleImportance = computeRuleImportance(episode);

  let obs;
  const validTypes = new Set(['decision', 'bugfix', 'feature', 'refactor', 'discovery', 'change']);

  const gotSlot = await acquireLLMSlot();
  if (gotSlot) {
    let raw, parsed;
    try {
      raw = callLLM(prompt);
      parsed = parseJsonFromLLM(raw);
    } finally {
      releaseLLMSlot();
    }

    if (parsed && parsed.title) {
      // Discard if LLM judges observation has no learning value
      if (parsed.importance === 0 || parsed.importance === '0') {
        debugLog('DEBUG', 'llm-episode', `Discarded low-value observation: ${parsed.title}`);
        // If pre-saved, delete it too
        if (episode.savedId) {
          const ddb = openDb();
          if (ddb) {
            try { ddb.prepare('DELETE FROM observations WHERE id = ?').run(episode.savedId); }
            finally { ddb.close(); }
          }
        }
        try { unlinkSync(tmpFile); } catch {}
        return;
      }

      // v2.33.1: expanded low-signal filter. Historical data showed Haiku
      // returns 'none'/''/'n/a'/'null'/'-'/'todo'/'tbd' ~95% of the time —
      // all noise with no retrieval value. Also reject lessons <12 chars
      // (e.g. "ok", "works", "fixed it") — too short to teach a future session.
      // When filtered, downgrade importance to 0 so rule-based fallback in
      // hook.mjs:saveObservation writes the obs but hook queries (which all
      // require importance >= 1) ignore it.
      const rawLesson = typeof parsed.lesson_learned === 'string' ? parsed.lesson_learned.trim() : '';
      const lowSignalLesson = new Set(['none', '', 'n/a', 'null', 'todo', 'tbd', 'na', '-', 'nothing', 'nil']);
      const isLessonLowSignal = lowSignalLesson.has(rawLesson.toLowerCase()) || rawLesson.length < 12;
      let lessonLearned = isLessonLowSignal ? null : rawLesson.slice(0, 500);

      // P3: for bugfix/decision, retry once with a lesson-focused prompt.
      // These types have the highest reuse value (~72.7% hit-rate vs change
      // ~16.5%), and Haiku's first pass writes NULL ~70% of the time for
      // curated observations. Retry budget: 1 extra callLLM per bugfix/decision
      // episode. Opt-out: CLAUDE_MEM_NO_LESSON_RETRY=1.
      let retryAttempted = false;
      let retryRecovered = false;
      if (isLessonLowSignal &&
          (parsed.type === 'bugfix' || parsed.type === 'decision') &&
          !process.env.CLAUDE_MEM_NO_LESSON_RETRY) {
        retryAttempted = true;
        try {
          const retryPrompt = buildLessonRetryPrompt(episode, parsed);
          const retryRaw = callLLM(retryPrompt, 10000);
          if (retryRaw) {
            const retry = parseJsonFromLLM(retryRaw);
            const retryLesson = typeof retry?.lesson === 'string' ? retry.lesson.trim() : '';
            const retryIsLow = lowSignalLesson.has(retryLesson.toLowerCase()) || retryLesson.length < 12;
            if (!retryIsLow) {
              lessonLearned = retryLesson.slice(0, 500);
              retryRecovered = true;
              debugLog('DEBUG', 'llm-episode', `lesson-retry: recovered ${retryLesson.length}-char lesson for ${parsed.type}`);
            }
          }
        } catch (e) { debugCatch(e, 'lesson-retry'); }
      }
      // v2.57.x B2: persist retry outcome counters. The retry path costs
      // 1 extra Haiku call per bugfix/decision episode; if recovered/attempts
      // ratio is consistently <10% over a long window, the path should be
      // deleted to save the LLM cost. `claude-mem-lite stats --retry`
      // exposes the daily aggregate. Opens a short-lived db handle so the
      // counter survives even if the main `obs` build below fails (we want
      // the data point about the retry attempt, not just the success path).
      if (retryAttempted) {
        try {
          const cdb = openDb();
          if (cdb) {
            try { recordRetryAttempt(cdb, retryRecovered); } finally { cdb.close(); }
          }
        } catch (e) { debugCatch(e, 'retry-stats-write'); }
      }

      const searchAliases = Array.isArray(parsed.search_aliases)
        ? parsed.search_aliases.slice(0, 6).join(' ')
        : null;

      obs = {
        type: validTypes.has(parsed.type) ? parsed.type : 'change',
        title: truncate(parsed.title, 120),
        subtitle: fileList,
        narrative: truncate(parsed.narrative || '', 500),
        concepts: Array.isArray(parsed.concepts) ? parsed.concepts.slice(0, 10) : [],
        facts: Array.isArray(parsed.facts) ? parsed.facts.slice(0, 10) : [],
        files: episode.files,
        filesRead: episode.filesRead || [],
        // v2.33.1: when lesson is low-signal, don't trust Haiku's importance
        // inflation. v2.54.0: extended from {change, discovery} to all types
        // except `decision` after audit (2026-04-30) showed bugfix lesson
        // coverage 11.2% / refactor hit-rate 18.1% — Haiku marks bugfix/refactor
        // imp=2-3 even when lesson is null after retry. Keep `decision` exempt:
        // it's rare (39 obs / 94.9% hit-rate) and the retry path already gave
        // it a second chance; a no-lesson decision is still a worthwhile signal.
        importance: isLessonLowSignal && parsed.type !== 'decision'
          ? Math.min(ruleImportance, 1)
          : Math.max(ruleImportance, clampImportance(parsed.importance)),
        lessonLearned,
        searchAliases,
      };

      // v2.56.0 #1: paired-gate DROP. Haiku-titled `change` obs with null lesson
      // and capped importance=1 are the dominant noise band (16.5% hit-rate vs
      // decision 72.7%; 67% of recent corpus). Pairs with capNoiseImportance
      // demote at line above per #8152 paired-gate model. Existing
      // isNoiseObservation gate is title-pattern keyed and misses these because
      // Haiku writes substantive-looking titles. Discard pattern mirrors the
      // `parsed.importance === 0` block above: delete pre-saved row if any,
      // unlink tmp, return without insert.
      if (isLowYieldChangeObs(obs)) {
        debugLog('DEBUG', 'llm-episode', `dropped low-yield change: "${truncate(obs.title || '', 60)}"`);
        if (episode.savedId) {
          const ddb = openDb();
          if (ddb) {
            try { ddb.prepare('DELETE FROM observations WHERE id = ?').run(episode.savedId); }
            finally { ddb.close(); }
          }
        }
        try { unlinkSync(tmpFile); } catch {}
        return;
      }
    }
  }

  if (!obs) {
    if (!gotSlot) debugLog('WARN', 'llm-episode', 'semaphore timeout, using degraded storage');
    // If pre-saved observation exists, LLM degraded mode doesn't need to overwrite — keep pre-saved data
    if (episode.savedId) {
      debugLog('DEBUG', 'llm-episode', `LLM failed but pre-saved obs #${episode.savedId} exists, keeping`);
      try { unlinkSync(tmpFile); } catch {}
      return;
    }
    obs = buildImmediateObservation(episode);
  }

  const db = openDb();
  if (!db) { try { unlinkSync(tmpFile); } catch {} return; }

  try {
    let savedId;
    let savedTable;

    if (episode.savedId && obs) {
      if (EVENT_TYPE_SET.has(obs.type)) {
        // Upgrade-delete: pre-saved observation's rule-inferred type was later
        // classified by Haiku as an event type. Delete the stale observations
        // row and insert into events instead. Dispatcher handles the atomic
        // swap via transaction.
        const result = persistHaikuSummary(db, obsToSummary(obs), {
          project: episode.project,
          session_id: episode.sessionId,
          preSavedObsId: episode.savedId,
        });
        savedId = result.id;
        savedTable = result.table;
        debugLog('DEBUG', 'llm-episode', `upgrade-delete: obs #${episode.savedId} → event #${savedId}`);
      } else {
        // Non-event type (e.g. `change`) — upgrade pre-saved observations row in place
        // so the enriched FTS text field + minhash + vector are refreshed atomically.
        const { conceptsText, factsText, textField } = buildFtsTextField(obs);
        const minhashSig = computeMinHash((obs.title || '') + ' ' + (obs.narrative || ''));
        // Scrub LLM-output text fields at the UPDATE boundary, mirroring the
        // INSERT path. type is an enum, importance is numeric, files_read is a
        // JSON array (already scrubbed upstream), minhash_sig is hash bytes.
        const safe = scrubRecord('observations', {
          title: truncate(obs.title, 120),
          subtitle: obs.subtitle || '',
          narrative: truncate(obs.narrative || '', 500),
          concepts: conceptsText,
          facts: factsText,
          text: textField,
          lesson_learned: obs.lessonLearned || null,
          search_aliases: obs.searchAliases || null,
        });
        db.prepare(`
          UPDATE observations SET type=?, title=?, subtitle=?, narrative=?, concepts=?, facts=?,
            text=?, importance=?, files_read=?, minhash_sig=?, lesson_learned=?, search_aliases=?
          WHERE id = ?
        `).run(
          obs.type, safe.title, safe.subtitle,
          safe.narrative,
          safe.concepts, safe.facts, safe.text,
          obs.importance,
          JSON.stringify(obs.filesRead || []),
          minhashSig,
          safe.lesson_learned,
          safe.search_aliases,
          episode.savedId
        );
        savedId = episode.savedId;
        savedTable = 'observations';
        debugLog('DEBUG', 'llm-episode', `upgraded pre-saved obs #${savedId}`);

        // Update TF-IDF vector with enriched content
        try {
          const vocab = getVocabulary(db);
          if (vocab) {
            const vecText = [obs.title || '', obs.narrative || '', conceptsText].filter(Boolean).join(' ');
            const vec = computeVector(vecText, vocab);
            if (vec) {
              db.prepare('INSERT OR REPLACE INTO observation_vectors (observation_id, vector, vocab_version, created_at_epoch) VALUES (?, ?, ?, ?)')
                .run(savedId, Buffer.from(vec.buffer), vocab.version, Date.now());
            }
          }
        } catch (e) { debugCatch(e, 'handleLLMEpisode-vector'); }
      }
    } else {
      // Clean insert (no pre-save) — dispatcher routes by type.
      const result = persistHaikuSummary(db, obsToSummary(obs), {
        project: episode.project,
        session_id: episode.sessionId,
      });
      savedId = result.id;
      savedTable = result.table;
    }

    // Related-observation linking only applies to rows in `observations` —
    // the `events` table has its own lifecycle (supersede/accessed_count).
    if (savedId && savedTable === 'observations') {
      try {
        linkRelatedObservations(db, savedId, obs, episode);
      } catch (e) { debugCatch(e, 'relatedObsLinking'); }
    }
  } finally {
    db.close();
  }

  try { unlinkSync(tmpFile); } catch {}
}

// ─── Background: LLM Session Summary ────────────────────────────────────────

export async function handleLLMSummary() {
  const parsed = parseInt(process.env.CLAUDE_MEM_FLUSH_TIMEOUT, 10);
  const flushTimeout = Number.isNaN(parsed) ? 15 : parsed;
  for (let i = 0; i < flushTimeout; i++) {
    try {
      const files = readdirSync(RUNTIME_DIR).filter(f => f.startsWith('ep-flush-'));
      if (files.length === 0) break;
    } catch { break; }
    debugLog('DEBUG', 'llm-summary', `waiting for flush files (${i + 1}/15)`);
    await sleep(1000);
  }

  const db = openDb();
  if (!db) return;

  try {
    const sessionId = process.argv[3] || getSessionId();
    const project = process.argv[4] || inferProject();

    // Exclude LOW_SIGNAL hook-llm fallback titles ("Error: files +2 more: ...",
    // "Modified X", "Worked on X", etc.) from the Haiku summary input — they
    // pollute the `completed` field and mislead session-resume context.
    const recentObs = db.prepare(`
      SELECT id, type, title, narrative
      FROM observations
      WHERE memory_session_id = ?
        AND ${notLowSignalTitleClause('')}
      ORDER BY created_at_epoch DESC
      LIMIT 30
    `).all(sessionId);

    if (recentObs.length < 1) return;

    const obsList = recentObs.map((o, i) =>
      `${i + 1}. [${o.type}] ${o.title}${o.narrative ? ': ' + truncate(o.narrative, 200) : ''}`
    ).join('\n');

    // Include user prompts for richer context
    const userPrompts = db.prepare(`
      SELECT prompt_text FROM user_prompts
      WHERE content_session_id = ? ORDER BY prompt_number ASC LIMIT 10
    `).all(sessionId).map(p => truncate(p.prompt_text, 300));
    const promptCtx = userPrompts.length > 0
      ? `\nUser requests: ${userPrompts.join(' → ')}\n`
      : '';

    // cso F#4: split system/user. The userPrompts content (line 921) is the
    // single highest-leakage path for memory poisoning — putting it in the
    // user role behind an explicit boundary is the main win here.
    const system = `Summarize this coding session. Return ONLY valid JSON, no markdown fences.

JSON: {"request":"what the user was working on","completed":"specific items accomplished with file names","remaining_items":"specific unfinished items from the original request — compare investigation scope with actual changes to infer what was NOT yet done; be precise with file:issue format, or empty string if all done","next_steps":"suggested follow-up","lessons":["non-obvious insights discovered during this session"],"key_decisions":["important design choices made and WHY"]}
lessons: Only genuinely non-obvious insights (debugging discoveries, gotchas, architectural reasons). Empty array if routine.
key_decisions: Only decisions with lasting impact (library choices, architecture, data model). Include reasoning. Empty array if none.`;
    const user = `Project: ${project}${promptCtx}
Observations (${recentObs.length} total):
${obsList}`;
    const prompt = { system, user };

    if (!(await acquireLLMSlot())) {
      debugLog('WARN', 'llm-summary', 'semaphore timeout, skipping summary');
      return;
    }

    let raw, llmParsed;
    try {
      raw = callLLM(prompt, 20000);
      llmParsed = parseJsonFromLLM(raw);
    } finally {
      releaseLLMSlot();
    }

    if (llmParsed && llmParsed.request) {
      const now = new Date();
      const lessonsJson = Array.isArray(llmParsed.lessons) && llmParsed.lessons.length > 0
        ? JSON.stringify(llmParsed.lessons) : null;
      const decisionsJson = Array.isArray(llmParsed.key_decisions) && llmParsed.key_decisions.length > 0
        ? JSON.stringify(llmParsed.key_decisions) : null;

      // Upgrade existing fast summary instead of creating a duplicate
      const existingFast = db.prepare(`
        SELECT id FROM session_summaries
        WHERE memory_session_id = ? AND notes = 'fast'
        LIMIT 1
      `).get(sessionId);

      if (existingFast) {
        // Preserve structural-extractor content (completed / remaining_items written
        // by handleStop fast-baseline from CLAUDE.md §10 markers) when Haiku returns
        // empty for that field. Without COALESCE, a degraded Haiku pass would erase
        // the deterministic floor — the exact regression that made 72% of prod
        // session_summaries ship with empty remaining_items.
        //
        // Scrub LLM-output text fields at the UPDATE boundary. lessons /
        // key_decisions are JSON.stringify(array<string>); we scrub the JSON
        // string here to match the sibling INSERT path. scrubSecrets uses
        // opaque placeholders that preserve JSON structure; element-level
        // pre-scrub remains safer in principle but would diverge from the
        // merged INSERT contract.
        const safe = scrubRecord('session_summaries', {
          request: llmParsed.request || '',
          investigated: llmParsed.investigated || '',
          learned: llmParsed.learned || '',
          completed: llmParsed.completed || '',
          next_steps: llmParsed.next_steps || '',
          remaining_items: llmParsed.remaining_items || '',
          lessons: lessonsJson,
          key_decisions: decisionsJson,
        });
        db.prepare(`
          UPDATE session_summaries
          SET request = COALESCE(NULLIF(?, ''), request),
              investigated = COALESCE(NULLIF(?, ''), investigated),
              learned = COALESCE(NULLIF(?, ''), learned),
              completed = COALESCE(NULLIF(?, ''), completed),
              next_steps = COALESCE(NULLIF(?, ''), next_steps),
              remaining_items = COALESCE(NULLIF(?, ''), remaining_items),
              lessons = COALESCE(?, lessons),
              key_decisions = COALESCE(?, key_decisions),
              notes = 'llm',
              created_at = ?,
              created_at_epoch = ?
          WHERE id = ?
        `).run(
          safe.request, safe.investigated, safe.learned,
          safe.completed, safe.next_steps,
          safe.remaining_items,
          safe.lessons, safe.key_decisions,
          now.toISOString(), now.getTime(),
          existingFast.id
        );
      } else {
        const safe = scrubRecord('session_summaries', {
          request: llmParsed.request || '',
          investigated: llmParsed.investigated || '',
          learned: llmParsed.learned || '',
          completed: llmParsed.completed || '',
          next_steps: llmParsed.next_steps || '',
          remaining_items: llmParsed.remaining_items || '',
          lessons: lessonsJson,
          key_decisions: decisionsJson,
        });
        db.prepare(`
          INSERT INTO session_summaries (memory_session_id, project, request, investigated, learned, completed, next_steps, remaining_items, files_read, files_edited, notes, lessons, key_decisions, created_at, created_at_epoch)
          VALUES (?, ?, ?, ?, ?, ?, ?, ?, '[]', '[]', '', ?, ?, ?, ?)
        `).run(
          sessionId, project,
          safe.request, safe.investigated, safe.learned,
          safe.completed, safe.next_steps,
          safe.remaining_items,
          safe.lessons, safe.key_decisions,
          now.toISOString(), now.getTime()
        );
      }
    }
  } finally {
    db.close();
  }
}

// Test-only — DO NOT import outside tests/. Underscore prefix is a
// convention; the plugin has no `main`/`exports` field so external imports
// are blocked at the package level, but a misguided sibling import inside
// this repo could drag this into prod by accident. If that ever needs
// enforcing, move the helper to a tests/_helpers/ module that takes a
// db-insert callback.
//
// Exercises the same scrubRecord path used by saveObservation without
// spinning up the full LLM dispatcher. Lets the e2e leak test verify that
// the observations INSERT path scrubs all configured text fields.
export const __insertObservationForTest = (db, obs) => {
  const safe = scrubRecord('observations', obs);
  db.prepare(`INSERT INTO observations (memory_session_id, project, text, type, title, subtitle, narrative, concepts, facts, files_read, files_modified, importance, minhash_sig, lesson_learned, search_aliases, branch, created_at, created_at_epoch)
    VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)`).run(
    obs.session_id, obs.project, safe.text, 'change',
    safe.title, safe.subtitle, safe.narrative,
    safe.concepts, safe.facts, obs.files_read, obs.files_modified,
    obs.importance, obs.minhash_sig, safe.lesson_learned, safe.search_aliases,
    obs.branch, new Date().toISOString(), Date.now(),
  );
};
