Correct Hermes Agent link in README.md by vincentamato · Pull Request #16 · garrytan/gbrain

vincentamato · 2026-04-10T07:50:44Z

Corrected the link to the Hermes Agent website in the README

garrytan · 2026-04-11T04:49:07Z

Thank you for catching the broken Hermes link! This was included in our community fix wave (PR #38, v0.6.1). We went with the GitHub repo URL from PR #34. Really appreciate you jumping on this!

vincentamato · 2026-04-11T04:51:21Z

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- #1: Crontab install used echo pipe with shell-interpolated values. Now uses a temp file via crontab(1) and single-quote escaping on all interpolated paths. No shell expansion possible. - #2: OPENAI_API_KEY was baked as plaintext into the launchd plist (readable by any local process, backed up by Time Machine). Now uses a wrapper script (~/.gbrain/autopilot-run.sh) that sources ~/.zshrc at runtime. No secrets in plist or crontab. - #16: extract.ts used a custom 20-line YAML parser that only handled single-line key:value pairs. Multi-line arrays (attendees list with - items) were silently ignored. Now uses the project's gray-matter parser via parseMarkdown() from src/core/markdown.ts. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* feat: migrate 8 existing skills to conformance format Add YAML frontmatter (name, version, description, triggers, tools, mutating), Contract, Anti-Patterns, and Output Format sections to all existing skills. Rename Workflow to Phases. Ingest becomes thin router delegating to specialized ingestion skills (Phase 2). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add RESOLVER.md, conventions directory, and output rules RESOLVER.md is the skill dispatcher modeled on Wintermute's AGENTS.md. Categorized routing table: Always-on, Brain ops, Ingestion, Thinking, Operational, Setup, Identity. Conventions directory extracts cross-cutting rules (quality, brain-first lookup, model routing, test-before-bulk). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * test: add skills conformance and resolver validation tests skills-conformance.test.ts validates every skill has YAML frontmatter with required fields, Contract, Anti-Patterns, and Output Format sections, and manifest.json coverage. resolver.test.ts validates routing table categories, skill path existence, and manifest-to-resolver coverage. 50 new tests. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add 9 brain skills from Wintermute (Phase 2) Generalized from Wintermute's battle-tested skills: - signal-detector: always-on idea+entity capture on every message - brain-ops: brain-first lookup, read-enrich-write loop, source attribution - idea-ingest: links/articles/tweets with author people page mandatory - media-ingest: video/audio/PDF/book with entity extraction (absorbs video/youtube/book) - meeting-ingestion: transcripts with attendee enrichment chaining - citation-fixer: audit and fix citation formatting - repo-architecture: filing rules by primary subject - skill-creator: create skills with conformance standard + MECE check - daily-task-manager: task lifecycle with priority levels All Garry-specific references generalized. Core workflows preserved. Updated RESOLVER.md and manifest.json. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add operational infrastructure + identity layer (Phase 3) Operational skills: - daily-task-prep: morning prep with calendar context and open threads - cross-modal-review: quality gate via second model with refusal routing - cron-scheduler: schedule staggering, quiet hours, wake-up override, idempotency - reports: timestamped reports with keyword routing - testing: skill validation framework (conformance checks) - soul-audit: 6-phase interview generating SOUL.md, USER.md, ACCESS_POLICY.md, HEARTBEAT.md - webhook-transforms: external events to brain signals with dead-letter queue Identity layer: - SOUL.md template (agent identity, generated by soul-audit) - USER.md template (user profile, generated by soul-audit) - ACCESS_POLICY.md template (4-tier access control) - HEARTBEAT.md template (operational cadence) - cross-modal.yaml convention (review pairs, refusal routing chain) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: update CLAUDE.md with 24 skills, RESOLVER.md, conventions, templates GBrain is now a GStack mod for agent platforms. Updated architecture description, key files listing (16 new skill files, RESOLVER.md, conventions, templates), skills section (24 skills organized by resolver categories), and testing section (new conformance and resolver tests). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add GStack detection + mod status to gbrain init (Phase 4) After brain initialization, gbrain init now reports: - Number of skills loaded (from manifest.json) - GStack detection (checks known host paths, uses gstack-global-discover if available) - GStack install instructions if not found - Resolver and soul-audit pointers Also adds installDefaultTemplates() for SOUL.md/USER.md/ACCESS_POLICY.md/HEARTBEAT.md deployment, and detectGStack() using gstack-global-discover with fallback to known paths (DRY: doesn't reimplement GStack's host detection logic). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: v0.10.0 release documentation - CHANGELOG: 24 skills, signal detector, RESOLVER.md, soul-audit, access control, conventions, conformance standard, GStack detection in init - README: updated skill section with 24 skills, resolver, conventions - TODOS: added runtime MCP access control (P1) - VERSION: 0.9.2 → 0.10.0 - package.json + manifest.json version bumped Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: add skill table to CHANGELOG v0.10.0 16-row table detailing every new skill, what it does, and why it matters. Written to sell the upgrade, not document the implementation. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: restore package.json version after merge conflict resolution Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: zero-based README rewrite for GStackBrain v0.10.0 Lead with GStack mod identity. 24 skills table organized by category. Install block references RESOLVER.md and soul-audit. GBrain+GStack relationship explained. Removed redundancy (733 -> 406 lines). All essential content preserved: install, recipes, architecture, search, commands, engines, voice, knowledge model. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: extract install block to INSTALL_FOR_AGENTS.md, simplify README The 30-line copy-paste install block becomes one line: "Retrieve and follow INSTALL_FOR_AGENTS.md" Benefits: agent always gets latest instructions (no stale copy-paste), README stays clean, install details live where agents read them. README now leads with what GBrain does ("gives your agent a brain") instead of GStack relationship. Removed "requires frontier model" note. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: 3 bugs in init.ts from merge conflict resolution 1. llstatSync typo (merge corruption) → lstatSync 2. __dirname undefined in ESM module → fileURLToPath polyfill 3. require('fs') in ESM → use imported readFileSync All three would crash gbrain init at runtime. Caught by /review. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add checkResolvable shared core function for resolver validation Shared function at src/core/check-resolvable.ts validates that all skills are reachable from RESOLVER.md, detects MECE overlaps (with whitelist for always-on/router skills), finds gaps in frontmatter triggers, and scans for DRY violations. Returns structured ResolvableIssue objects with machine-parseable fix objects alongside human-readable action strings. Three call sites: bun test, gbrain doctor, skill-creator skill. Cleans up test/resolver.test.ts: removes stale 9-line skip list, imports from production check-resolvable.ts instead of reimplementing parsing. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: expand doctor with resolver validation, filesystem-first architecture Doctor now runs filesystem checks (resolver health, skill conformance) before connecting to DB. New --fast flag skips DB checks. Falls back to filesystem-only when DB is unavailable. Adds schema_version: 2 to JSON output, composite health score (0-100), and structured issues array with action strings for agent parsing. Resolver health check calls checkResolvable() and surfaces actionable fix instructions. Link integrity check uses engine.getHealth() dead_links count. CLI routing split: doctor dispatched before connectEngine() so filesystem checks always run. Fixes Codex-identified blocker where doctor required DB. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add adaptive load-aware throttling and fail-improve loop backoff.ts: System load checking (CPU via os.loadavg, memory via os.freemem), exponential backoff with 20-attempt max guard, active hours multiplier (2x slower during waking hours), concurrent process limit (max 2). Windows-safe: defaults to "proceed" when os.loadavg returns zeros. fail-improve.ts: Deterministic-first, LLM-fallback pattern with JSONL failure logging. Cascade failure handling: when both paths fail, throws LLM error and logs both. Log rotation at 1000 entries. Call count tracking for deterministic hit rate metrics. Auto-generates test cases from successful LLM fallbacks. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add transcription service and enrichment-as-a-service transcription.ts: Groq Whisper (default) with OpenAI fallback. Files >25MB segmented via ffmpeg. Provider auto-detection from env vars. Clear error messages for missing API keys and unsupported formats. enrichment-service.ts: Global enrichment service callable from any ingest pathway. Entity slug generation (people/jane-doe, companies/acme-corp), mention counting via searchKeyword, tier auto-escalation (Tier 3→2→1 based on mention frequency and source diversity), batch enrichment with backoff throttling, regex-based entity extraction from text. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add data-research skill with recipe system, extraction, dedup, tracker New skill: data-research — one parameterized pipeline for any email-to- structured-data workflow (investor updates, donations, company metrics). 7-phase pipeline: define recipe, search, classify, extract (with extraction integrity rule), archive, deduplicate, update tracker. data-research.ts: Recipe validation, MRR/ARR/runway/headcount regex extraction (battle-tested patterns), dedup with configurable tolerance, markdown tracker parsing/appending, quarterly/monthly date windowing, 6-phase HTML email stripping with 500KB ReDoS cap. Registers data-research in manifest.json (25th skill) and RESOLVER.md. Fixes backoff test robustness for high-load systems. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: update project documentation for v0.10.0 infrastructure additions CLAUDE.md: added 6 new core files (check-resolvable, backoff, fail-improve, transcription, enrichment-service, data-research), 6 new test files, updated skill count to 25, test file count to 34. README.md: updated skill count to 25, added data-research to skills table. CHANGELOG.md: added Infrastructure section documenting resolver validation, doctor expansion, adaptive throttling, fail-improve loop, voice transcription, enrichment service, and data-research skill. TODOS.md: anonymized personal references. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: doctor.ts use ES module imports, harden backoff test Replace require('fs') with ES module import in doctor.ts for consistency with the rest of the file. Backoff test made resilient to parallel test execution leaking module-level state. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: sync --watch routing, dead_links parity, doctor command, embed --slugs - Move sync to CLI_ONLY so --watch flag reaches runSync() (was routed through operation layer which only calls performSync single-pass) - Hide sync_brain from CLI help (MCP still exposes it) - Fix performFullSync missing sync state persistence (C1) - Align Postgres dead_links query to match PGLite (count dangling links, not empty-content chunks) (C3) - Fix doctor recommending nonexistent 'gbrain embed refresh' (C4) - Refactor doctor outputResults to not call process.exit directly - Add --slugs flag to embed for targeted page embedding - Add sync auto-extract + auto-embed after performSync - Add noExtract to SyncOpts - Route extract, features, autopilot in CLI_ONLY - Update help text with new commands Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: extract, features, and autopilot commands - gbrain extract <links|timeline|all> — batch extraction of links and timeline entries from brain markdown files. Broad regex for all .md links (C7: filters external URLs). Frontmatter field parsing (company, investors, attendees). Directory-based link type inference. JSONL progress on stderr for agents. Sync integration hooks (extractLinksForSlugs, extractTimelineForSlugs). - gbrain features [--json] [--auto-fix] — scan brain usage, pitch unused features with the user's own numbers. Priority 1 (data quality): missing embeddings, dead links. Priority 2 (unused features): zero links, zero timeline, low coverage, unconfigured integrations, no sync. Embedded recipe metadata for binary-safe integration detection. Persistence in ~/.gbrain/feature-offers.json. Doctor teaser hook. Upgrade hook. - gbrain autopilot [--repo] [--interval N] — self-maintaining brain daemon. Pipeline: sync → extract → embed. Health-based adaptive scheduling (brain_score >= 90 doubles interval, < 70 halves it). --install/--uninstall for launchd (macOS) and crontab (Linux). Signal handling. Consecutive error tracking (stops at 5). Log to ~/.gbrain/autopilot.log. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: hook features scan into post-upgrade flow After gbrain post-upgrade completes, automatically run gbrain features to show the user what's new and what to fix. Best-effort (doesn't fail the upgrade). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: brain_score (0-100) in BrainHealth Weighted composite score computed in getHealth() for both Postgres and PGLite: embed_coverage: 0.35, link_density: 0.25, timeline_coverage: 0.15, no_orphans: 0.15, no_dead_links: 0.10 Returns 0 for empty brains. Agents use brain_score as a health gate. Autopilot uses it for adaptive scheduling (>=90 slows down, <70 speeds up). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * test: extract and features unit tests 25 tests covering: - extractMarkdownLinks: relative links, external URL filtering, edge cases - extractLinksFromFile: slug resolution, frontmatter parsing, directory-based type inference (works_at, deal_for, invested_in) - extractTimelineFromContent: bullet format, header format with detail, em/en dash handling, empty content - features: module exports, brain_score calculation weights, CLI routing Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: instruction layer for extract, features, autopilot Agent-facing tools are invisible without instruction-layer coverage. - RESOLVER.md: add routing for extract, features, autopilot - maintain/SKILL.md: add link graph extraction, timeline extraction, autopilot check sections Without these, agents reading skills/ will never discover or run the new commands. This is the #1 DX finding from the devex review. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * chore: bump version and changelog (v0.10.1) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: sync CLAUDE.md with v0.10.1 additions Add extract.ts, features.ts, autopilot.ts to key files. Add extract.test.ts, features.test.ts to test list. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: adversarial review fixes — 7 issues - #3: autopilot extract step was a no-op (imported but never called) - #6: PGLite orphan_pages query aligned with Postgres (check both inbound+outbound) - #8: embedPage throws instead of process.exit (was killing sync/autopilot) - #9: dead-links set auto_fixable=false (needs repo path we may not have) - #10: JSON auto-fix output was dead code (unreachable !jsonMode check) - #14: autopilot lock file prevents concurrent instances - #20: --dir without value no longer crashes extract Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * security: fix command injection + plaintext API key in daemon install - #1: Crontab install used echo pipe with shell-interpolated values. Now uses a temp file via crontab(1) and single-quote escaping on all interpolated paths. No shell expansion possible. - #2: OPENAI_API_KEY was baked as plaintext into the launchd plist (readable by any local process, backed up by Time Machine). Now uses a wrapper script (~/.gbrain/autopilot-run.sh) that sources ~/.zshrc at runtime. No secrets in plist or crontab. - #16: extract.ts used a custom 20-line YAML parser that only handled single-line key:value pairs. Multi-line arrays (attendees list with - items) were silently ignored. Now uses the project's gray-matter parser via parseMarkdown() from src/core/markdown.ts. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

…ntract Two modules that together wire Cat 8 / Cat 9 / Cat 5 end-to-end scoring. **eval/runner/judge.ts** — Haiku 4.5 via tool-use `score_answer`. Input is the structured JudgeEvidence contract (fix #16 from the plan's codex review): probe + final_answer_text + evidence_refs + tool_call_summary + ground_truth_pages + rubric. Raw tool output NEVER reaches the judge — that's the Section-3 defense against paraphrased prompt-injection payloads in gold/poison.json. Retry policy: one retry on malformed tool_use response. If the second attempt is still malformed, score the probe as `judge_failed` (all scores 0, verdict=fail) so the run still completes. Aggregation: weighted mean across rubric criteria. Canonical thresholds (pass ≥3.5, partial 2.5-3.5, fail <2.5) — judge can propose a verdict but the computed verdict from the weighted mean is what the scorecard records. This prevents the model from inflating or deflating its own verdict. Score values are clamped to 0-5 on parse even if the model returns out of range. `assertNoRawToolOutput(evidence)` is a regression guard that returns the list of forbidden fields (tool_result, raw_transcript, etc.) if any leak into the evidence contract. **eval/runner/adapters/claude-sonnet-with-tools.ts** — The agent adapter. Implements `Adapter` interface minimally: `init()` spins up PGLite and seeds it, `query()` throws because the adapter is Cat 8/9-only and emits a final-answer text, not a RankedDoc[]. Retrieval scorecard stays at 4 adapters. `runAgentLoop(probeId, text, state, config)` drives the multi-turn loop: Sonnet → tool_use → tool-bridge.executeTool → tool_result → back to Sonnet. Turn cap 10. max_tokens 1024. System prompt (brain-first iron law, citation format, amara context) is cached via cache_control. Exponential backoff on rate-limit errors (1s, 2s, 4s). Emits a `Transcript` per eval/schemas/transcript.schema.json — consumed directly by recorder.ts for the flight-recorder bundle. `brain_first_ordering` classifies Cat 8's flagship metric: did the agent call search/get_page BEFORE producing the final answer? The `no_brain_calls` case (agent answers from general knowledge without ever hitting the brain) is the compliance failure to surface. ForbiddenOpError + UnknownToolError from the bridge are caught in the agent loop and surfaced as tool_result with is_error=true — keeps the loop going and preserves full audit trail for the judge. **Tests (35 new):** judge (23) — happy path, retry, fallback, evidence contract sanitization, rendered prompt does not contain raw tool_result text, verdict thresholds, score clamping, weighted mean with mixed weights, parseToolUse rejects malformed input. agent-adapter (12) — Adapter.query() throws, init() seeds PGLite, end-to-end tool loop with stubbed Sonnet, turn cap exhaustion, mutating-op rejection surfaces as tool_result error, extractSlugs regex. All 12 agent tests take ~23s because PGLite runs 13 schema migrations per test; the alternative of shared-engine-across-tests was rejected so each test is isolated. Total eval suite now: 167 pass, 0 fail. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* feat: GStackBrain — 16 new skills, resolver, conventions, identity layer (v0.10.0) (#120) * feat: migrate 8 existing skills to conformance format Add YAML frontmatter (name, version, description, triggers, tools, mutating), Contract, Anti-Patterns, and Output Format sections to all existing skills. Rename Workflow to Phases. Ingest becomes thin router delegating to specialized ingestion skills (Phase 2). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add RESOLVER.md, conventions directory, and output rules RESOLVER.md is the skill dispatcher modeled on Wintermute's AGENTS.md. Categorized routing table: Always-on, Brain ops, Ingestion, Thinking, Operational, Setup, Identity. Conventions directory extracts cross-cutting rules (quality, brain-first lookup, model routing, test-before-bulk). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * test: add skills conformance and resolver validation tests skills-conformance.test.ts validates every skill has YAML frontmatter with required fields, Contract, Anti-Patterns, and Output Format sections, and manifest.json coverage. resolver.test.ts validates routing table categories, skill path existence, and manifest-to-resolver coverage. 50 new tests. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add 9 brain skills from Wintermute (Phase 2) Generalized from Wintermute's battle-tested skills: - signal-detector: always-on idea+entity capture on every message - brain-ops: brain-first lookup, read-enrich-write loop, source attribution - idea-ingest: links/articles/tweets with author people page mandatory - media-ingest: video/audio/PDF/book with entity extraction (absorbs video/youtube/book) - meeting-ingestion: transcripts with attendee enrichment chaining - citation-fixer: audit and fix citation formatting - repo-architecture: filing rules by primary subject - skill-creator: create skills with conformance standard + MECE check - daily-task-manager: task lifecycle with priority levels All Garry-specific references generalized. Core workflows preserved. Updated RESOLVER.md and manifest.json. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add operational infrastructure + identity layer (Phase 3) Operational skills: - daily-task-prep: morning prep with calendar context and open threads - cross-modal-review: quality gate via second model with refusal routing - cron-scheduler: schedule staggering, quiet hours, wake-up override, idempotency - reports: timestamped reports with keyword routing - testing: skill validation framework (conformance checks) - soul-audit: 6-phase interview generating SOUL.md, USER.md, ACCESS_POLICY.md, HEARTBEAT.md - webhook-transforms: external events to brain signals with dead-letter queue Identity layer: - SOUL.md template (agent identity, generated by soul-audit) - USER.md template (user profile, generated by soul-audit) - ACCESS_POLICY.md template (4-tier access control) - HEARTBEAT.md template (operational cadence) - cross-modal.yaml convention (review pairs, refusal routing chain) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: update CLAUDE.md with 24 skills, RESOLVER.md, conventions, templates GBrain is now a GStack mod for agent platforms. Updated architecture description, key files listing (16 new skill files, RESOLVER.md, conventions, templates), skills section (24 skills organized by resolver categories), and testing section (new conformance and resolver tests). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add GStack detection + mod status to gbrain init (Phase 4) After brain initialization, gbrain init now reports: - Number of skills loaded (from manifest.json) - GStack detection (checks known host paths, uses gstack-global-discover if available) - GStack install instructions if not found - Resolver and soul-audit pointers Also adds installDefaultTemplates() for SOUL.md/USER.md/ACCESS_POLICY.md/HEARTBEAT.md deployment, and detectGStack() using gstack-global-discover with fallback to known paths (DRY: doesn't reimplement GStack's host detection logic). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: v0.10.0 release documentation - CHANGELOG: 24 skills, signal detector, RESOLVER.md, soul-audit, access control, conventions, conformance standard, GStack detection in init - README: updated skill section with 24 skills, resolver, conventions - TODOS: added runtime MCP access control (P1) - VERSION: 0.9.2 → 0.10.0 - package.json + manifest.json version bumped Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: add skill table to CHANGELOG v0.10.0 16-row table detailing every new skill, what it does, and why it matters. Written to sell the upgrade, not document the implementation. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: restore package.json version after merge conflict resolution Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: zero-based README rewrite for GStackBrain v0.10.0 Lead with GStack mod identity. 24 skills table organized by category. Install block references RESOLVER.md and soul-audit. GBrain+GStack relationship explained. Removed redundancy (733 -> 406 lines). All essential content preserved: install, recipes, architecture, search, commands, engines, voice, knowledge model. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: extract install block to INSTALL_FOR_AGENTS.md, simplify README The 30-line copy-paste install block becomes one line: "Retrieve and follow INSTALL_FOR_AGENTS.md" Benefits: agent always gets latest instructions (no stale copy-paste), README stays clean, install details live where agents read them. README now leads with what GBrain does ("gives your agent a brain") instead of GStack relationship. Removed "requires frontier model" note. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: 3 bugs in init.ts from merge conflict resolution 1. llstatSync typo (merge corruption) → lstatSync 2. __dirname undefined in ESM module → fileURLToPath polyfill 3. require('fs') in ESM → use imported readFileSync All three would crash gbrain init at runtime. Caught by /review. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add checkResolvable shared core function for resolver validation Shared function at src/core/check-resolvable.ts validates that all skills are reachable from RESOLVER.md, detects MECE overlaps (with whitelist for always-on/router skills), finds gaps in frontmatter triggers, and scans for DRY violations. Returns structured ResolvableIssue objects with machine-parseable fix objects alongside human-readable action strings. Three call sites: bun test, gbrain doctor, skill-creator skill. Cleans up test/resolver.test.ts: removes stale 9-line skip list, imports from production check-resolvable.ts instead of reimplementing parsing. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: expand doctor with resolver validation, filesystem-first architecture Doctor now runs filesystem checks (resolver health, skill conformance) before connecting to DB. New --fast flag skips DB checks. Falls back to filesystem-only when DB is unavailable. Adds schema_version: 2 to JSON output, composite health score (0-100), and structured issues array with action strings for agent parsing. Resolver health check calls checkResolvable() and surfaces actionable fix instructions. Link integrity check uses engine.getHealth() dead_links count. CLI routing split: doctor dispatched before connectEngine() so filesystem checks always run. Fixes Codex-identified blocker where doctor required DB. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add adaptive load-aware throttling and fail-improve loop backoff.ts: System load checking (CPU via os.loadavg, memory via os.freemem), exponential backoff with 20-attempt max guard, active hours multiplier (2x slower during waking hours), concurrent process limit (max 2). Windows-safe: defaults to "proceed" when os.loadavg returns zeros. fail-improve.ts: Deterministic-first, LLM-fallback pattern with JSONL failure logging. Cascade failure handling: when both paths fail, throws LLM error and logs both. Log rotation at 1000 entries. Call count tracking for deterministic hit rate metrics. Auto-generates test cases from successful LLM fallbacks. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add transcription service and enrichment-as-a-service transcription.ts: Groq Whisper (default) with OpenAI fallback. Files >25MB segmented via ffmpeg. Provider auto-detection from env vars. Clear error messages for missing API keys and unsupported formats. enrichment-service.ts: Global enrichment service callable from any ingest pathway. Entity slug generation (people/jane-doe, companies/acme-corp), mention counting via searchKeyword, tier auto-escalation (Tier 3→2→1 based on mention frequency and source diversity), batch enrichment with backoff throttling, regex-based entity extraction from text. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add data-research skill with recipe system, extraction, dedup, tracker New skill: data-research — one parameterized pipeline for any email-to- structured-data workflow (investor updates, donations, company metrics). 7-phase pipeline: define recipe, search, classify, extract (with extraction integrity rule), archive, deduplicate, update tracker. data-research.ts: Recipe validation, MRR/ARR/runway/headcount regex extraction (battle-tested patterns), dedup with configurable tolerance, markdown tracker parsing/appending, quarterly/monthly date windowing, 6-phase HTML email stripping with 500KB ReDoS cap. Registers data-research in manifest.json (25th skill) and RESOLVER.md. Fixes backoff test robustness for high-load systems. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: update project documentation for v0.10.0 infrastructure additions CLAUDE.md: added 6 new core files (check-resolvable, backoff, fail-improve, transcription, enrichment-service, data-research), 6 new test files, updated skill count to 25, test file count to 34. README.md: updated skill count to 25, added data-research to skills table. CHANGELOG.md: added Infrastructure section documenting resolver validation, doctor expansion, adaptive throttling, fail-improve loop, voice transcription, enrichment service, and data-research skill. TODOS.md: anonymized personal references. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: doctor.ts use ES module imports, harden backoff test Replace require('fs') with ES module import in doctor.ts for consistency with the rest of the file. Backoff test made resilient to parallel test execution leaking module-level state. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: README rewrite with production brain stats, sample output, new infrastructure Lead with the flex: 17,888 pages, 4,383 people, 723 companies, 526 meeting transcripts built in 12 days. Show sample query output so readers see what they'll get. Document self-improving infrastructure (tier auto-escalation, fail-improve loop, doctor trajectory). Add data-research recipes to Getting Data In. Update commands section with doctor --fix, transcribe, research init/list. Fix stale "24" references to "25". Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: README lead with YC President origin and production agent deployments Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: README lead with skill philosophy and link to Thin Harness Fat Skills Skills section now explains: skill files are code, they encode entire workflows, they call deterministic TypeScript for the parts that shouldn't be LLM judgment. Links to the tweet and the architecture essay. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: link GStack repo, add 70K stars and 30K daily users Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: remove meeting transcript count from README (sensitive) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: README lead with YC President origin and production agent deployments Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: rename political-donations recipe to expense-tracker (sensitivity) Renamed the built-in data-research recipe from political-donations to expense-tracker across README, CHANGELOG, SKILL.md, and reports routing. Same extraction patterns (amounts, dates, recipients), neutral framing. Also renamed social-radar keyword route to social-mentions. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: sync pipeline, extract, features, autopilot (v0.10.1) (#129) * feat: migrate 8 existing skills to conformance format Add YAML frontmatter (name, version, description, triggers, tools, mutating), Contract, Anti-Patterns, and Output Format sections to all existing skills. Rename Workflow to Phases. Ingest becomes thin router delegating to specialized ingestion skills (Phase 2). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add RESOLVER.md, conventions directory, and output rules RESOLVER.md is the skill dispatcher modeled on Wintermute's AGENTS.md. Categorized routing table: Always-on, Brain ops, Ingestion, Thinking, Operational, Setup, Identity. Conventions directory extracts cross-cutting rules (quality, brain-first lookup, model routing, test-before-bulk). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * test: add skills conformance and resolver validation tests skills-conformance.test.ts validates every skill has YAML frontmatter with required fields, Contract, Anti-Patterns, and Output Format sections, and manifest.json coverage. resolver.test.ts validates routing table categories, skill path existence, and manifest-to-resolver coverage. 50 new tests. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add 9 brain skills from Wintermute (Phase 2) Generalized from Wintermute's battle-tested skills: - signal-detector: always-on idea+entity capture on every message - brain-ops: brain-first lookup, read-enrich-write loop, source attribution - idea-ingest: links/articles/tweets with author people page mandatory - media-ingest: video/audio/PDF/book with entity extraction (absorbs video/youtube/book) - meeting-ingestion: transcripts with attendee enrichment chaining - citation-fixer: audit and fix citation formatting - repo-architecture: filing rules by primary subject - skill-creator: create skills with conformance standard + MECE check - daily-task-manager: task lifecycle with priority levels All Garry-specific references generalized. Core workflows preserved. Updated RESOLVER.md and manifest.json. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add operational infrastructure + identity layer (Phase 3) Operational skills: - daily-task-prep: morning prep with calendar context and open threads - cross-modal-review: quality gate via second model with refusal routing - cron-scheduler: schedule staggering, quiet hours, wake-up override, idempotency - reports: timestamped reports with keyword routing - testing: skill validation framework (conformance checks) - soul-audit: 6-phase interview generating SOUL.md, USER.md, ACCESS_POLICY.md, HEARTBEAT.md - webhook-transforms: external events to brain signals with dead-letter queue Identity layer: - SOUL.md template (agent identity, generated by soul-audit) - USER.md template (user profile, generated by soul-audit) - ACCESS_POLICY.md template (4-tier access control) - HEARTBEAT.md template (operational cadence) - cross-modal.yaml convention (review pairs, refusal routing chain) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: update CLAUDE.md with 24 skills, RESOLVER.md, conventions, templates GBrain is now a GStack mod for agent platforms. Updated architecture description, key files listing (16 new skill files, RESOLVER.md, conventions, templates), skills section (24 skills organized by resolver categories), and testing section (new conformance and resolver tests). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add GStack detection + mod status to gbrain init (Phase 4) After brain initialization, gbrain init now reports: - Number of skills loaded (from manifest.json) - GStack detection (checks known host paths, uses gstack-global-discover if available) - GStack install instructions if not found - Resolver and soul-audit pointers Also adds installDefaultTemplates() for SOUL.md/USER.md/ACCESS_POLICY.md/HEARTBEAT.md deployment, and detectGStack() using gstack-global-discover with fallback to known paths (DRY: doesn't reimplement GStack's host detection logic). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: v0.10.0 release documentation - CHANGELOG: 24 skills, signal detector, RESOLVER.md, soul-audit, access control, conventions, conformance standard, GStack detection in init - README: updated skill section with 24 skills, resolver, conventions - TODOS: added runtime MCP access control (P1) - VERSION: 0.9.2 → 0.10.0 - package.json + manifest.json version bumped Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: add skill table to CHANGELOG v0.10.0 16-row table detailing every new skill, what it does, and why it matters. Written to sell the upgrade, not document the implementation. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: restore package.json version after merge conflict resolution Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: zero-based README rewrite for GStackBrain v0.10.0 Lead with GStack mod identity. 24 skills table organized by category. Install block references RESOLVER.md and soul-audit. GBrain+GStack relationship explained. Removed redundancy (733 -> 406 lines). All essential content preserved: install, recipes, architecture, search, commands, engines, voice, knowledge model. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: extract install block to INSTALL_FOR_AGENTS.md, simplify README The 30-line copy-paste install block becomes one line: "Retrieve and follow INSTALL_FOR_AGENTS.md" Benefits: agent always gets latest instructions (no stale copy-paste), README stays clean, install details live where agents read them. README now leads with what GBrain does ("gives your agent a brain") instead of GStack relationship. Removed "requires frontier model" note. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: 3 bugs in init.ts from merge conflict resolution 1. llstatSync typo (merge corruption) → lstatSync 2. __dirname undefined in ESM module → fileURLToPath polyfill 3. require('fs') in ESM → use imported readFileSync All three would crash gbrain init at runtime. Caught by /review. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add checkResolvable shared core function for resolver validation Shared function at src/core/check-resolvable.ts validates that all skills are reachable from RESOLVER.md, detects MECE overlaps (with whitelist for always-on/router skills), finds gaps in frontmatter triggers, and scans for DRY violations. Returns structured ResolvableIssue objects with machine-parseable fix objects alongside human-readable action strings. Three call sites: bun test, gbrain doctor, skill-creator skill. Cleans up test/resolver.test.ts: removes stale 9-line skip list, imports from production check-resolvable.ts instead of reimplementing parsing. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: expand doctor with resolver validation, filesystem-first architecture Doctor now runs filesystem checks (resolver health, skill conformance) before connecting to DB. New --fast flag skips DB checks. Falls back to filesystem-only when DB is unavailable. Adds schema_version: 2 to JSON output, composite health score (0-100), and structured issues array with action strings for agent parsing. Resolver health check calls checkResolvable() and surfaces actionable fix instructions. Link integrity check uses engine.getHealth() dead_links count. CLI routing split: doctor dispatched before connectEngine() so filesystem checks always run. Fixes Codex-identified blocker where doctor required DB. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add adaptive load-aware throttling and fail-improve loop backoff.ts: System load checking (CPU via os.loadavg, memory via os.freemem), exponential backoff with 20-attempt max guard, active hours multiplier (2x slower during waking hours), concurrent process limit (max 2). Windows-safe: defaults to "proceed" when os.loadavg returns zeros. fail-improve.ts: Deterministic-first, LLM-fallback pattern with JSONL failure logging. Cascade failure handling: when both paths fail, throws LLM error and logs both. Log rotation at 1000 entries. Call count tracking for deterministic hit rate metrics. Auto-generates test cases from successful LLM fallbacks. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add transcription service and enrichment-as-a-service transcription.ts: Groq Whisper (default) with OpenAI fallback. Files >25MB segmented via ffmpeg. Provider auto-detection from env vars. Clear error messages for missing API keys and unsupported formats. enrichment-service.ts: Global enrichment service callable from any ingest pathway. Entity slug generation (people/jane-doe, companies/acme-corp), mention counting via searchKeyword, tier auto-escalation (Tier 3→2→1 based on mention frequency and source diversity), batch enrichment with backoff throttling, regex-based entity extraction from text. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: add data-research skill with recipe system, extraction, dedup, tracker New skill: data-research — one parameterized pipeline for any email-to- structured-data workflow (investor updates, donations, company metrics). 7-phase pipeline: define recipe, search, classify, extract (with extraction integrity rule), archive, deduplicate, update tracker. data-research.ts: Recipe validation, MRR/ARR/runway/headcount regex extraction (battle-tested patterns), dedup with configurable tolerance, markdown tracker parsing/appending, quarterly/monthly date windowing, 6-phase HTML email stripping with 500KB ReDoS cap. Registers data-research in manifest.json (25th skill) and RESOLVER.md. Fixes backoff test robustness for high-load systems. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: update project documentation for v0.10.0 infrastructure additions CLAUDE.md: added 6 new core files (check-resolvable, backoff, fail-improve, transcription, enrichment-service, data-research), 6 new test files, updated skill count to 25, test file count to 34. README.md: updated skill count to 25, added data-research to skills table. CHANGELOG.md: added Infrastructure section documenting resolver validation, doctor expansion, adaptive throttling, fail-improve loop, voice transcription, enrichment service, and data-research skill. TODOS.md: anonymized personal references. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: doctor.ts use ES module imports, harden backoff test Replace require('fs') with ES module import in doctor.ts for consistency with the rest of the file. Backoff test made resilient to parallel test execution leaking module-level state. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: sync --watch routing, dead_links parity, doctor command, embed --slugs - Move sync to CLI_ONLY so --watch flag reaches runSync() (was routed through operation layer which only calls performSync single-pass) - Hide sync_brain from CLI help (MCP still exposes it) - Fix performFullSync missing sync state persistence (C1) - Align Postgres dead_links query to match PGLite (count dangling links, not empty-content chunks) (C3) - Fix doctor recommending nonexistent 'gbrain embed refresh' (C4) - Refactor doctor outputResults to not call process.exit directly - Add --slugs flag to embed for targeted page embedding - Add sync auto-extract + auto-embed after performSync - Add noExtract to SyncOpts - Route extract, features, autopilot in CLI_ONLY - Update help text with new commands Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: extract, features, and autopilot commands - gbrain extract <links|timeline|all> — batch extraction of links and timeline entries from brain markdown files. Broad regex for all .md links (C7: filters external URLs). Frontmatter field parsing (company, investors, attendees). Directory-based link type inference. JSONL progress on stderr for agents. Sync integration hooks (extractLinksForSlugs, extractTimelineForSlugs). - gbrain features [--json] [--auto-fix] — scan brain usage, pitch unused features with the user's own numbers. Priority 1 (data quality): missing embeddings, dead links. Priority 2 (unused features): zero links, zero timeline, low coverage, unconfigured integrations, no sync. Embedded recipe metadata for binary-safe integration detection. Persistence in ~/.gbrain/feature-offers.json. Doctor teaser hook. Upgrade hook. - gbrain autopilot [--repo] [--interval N] — self-maintaining brain daemon. Pipeline: sync → extract → embed. Health-based adaptive scheduling (brain_score >= 90 doubles interval, < 70 halves it). --install/--uninstall for launchd (macOS) and crontab (Linux). Signal handling. Consecutive error tracking (stops at 5). Log to ~/.gbrain/autopilot.log. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: hook features scan into post-upgrade flow After gbrain post-upgrade completes, automatically run gbrain features to show the user what's new and what to fix. Best-effort (doesn't fail the upgrade). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: brain_score (0-100) in BrainHealth Weighted composite score computed in getHealth() for both Postgres and PGLite: embed_coverage: 0.35, link_density: 0.25, timeline_coverage: 0.15, no_orphans: 0.15, no_dead_links: 0.10 Returns 0 for empty brains. Agents use brain_score as a health gate. Autopilot uses it for adaptive scheduling (>=90 slows down, <70 speeds up). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * test: extract and features unit tests 25 tests covering: - extractMarkdownLinks: relative links, external URL filtering, edge cases - extractLinksFromFile: slug resolution, frontmatter parsing, directory-based type inference (works_at, deal_for, invested_in) - extractTimelineFromContent: bullet format, header format with detail, em/en dash handling, empty content - features: module exports, brain_score calculation weights, CLI routing Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: instruction layer for extract, features, autopilot Agent-facing tools are invisible without instruction-layer coverage. - RESOLVER.md: add routing for extract, features, autopilot - maintain/SKILL.md: add link graph extraction, timeline extraction, autopilot check sections Without these, agents reading skills/ will never discover or run the new commands. This is the #1 DX finding from the devex review. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * chore: bump version and changelog (v0.10.1) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: sync CLAUDE.md with v0.10.1 additions Add extract.ts, features.ts, autopilot.ts to key files. Add extract.test.ts, features.test.ts to test list. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: adversarial review fixes — 7 issues - #3: autopilot extract step was a no-op (imported but never called) - #6: PGLite orphan_pages query aligned with Postgres (check both inbound+outbound) - #8: embedPage throws instead of process.exit (was killing sync/autopilot) - #9: dead-links set auto_fixable=false (needs repo path we may not have) - #10: JSON auto-fix output was dead code (unreachable !jsonMode check) - #14: autopilot lock file prevents concurrent instances - #20: --dir without value no longer crashes extract Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * security: fix command injection + plaintext API key in daemon install - #1: Crontab install used echo pipe with shell-interpolated values. Now uses a temp file via crontab(1) and single-quote escaping on all interpolated paths. No shell expansion possible. - #2: OPENAI_API_KEY was baked as plaintext into the launchd plist (readable by any local process, backed up by Time Machine). Now uses a wrapper script (~/.gbrain/autopilot-run.sh) that sources ~/.zshrc at runtime. No secrets in plist or crontab. - #16: extract.ts used a custom 20-line YAML parser that only handled single-line key:value pairs. Multi-line arrays (attendees list with - items) were silently ignored. Now uses the project's gray-matter parser via parseMarkdown() from src/core/markdown.ts. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * security: fix wave 3 — 9 vulns (file_upload, SSRF, recipe trust, prompt injection) (#174) * feat(engine): add cap parameter to clampSearchLimit (H6) clampSearchLimit(limit, defaultLimit, cap = MAX_SEARCH_LIMIT) — third arg is a caller-specified cap so operation handlers can enforce limits below MAX_SEARCH_LIMIT. Backward compatible: existing two-arg callers still cap at MAX_SEARCH_LIMIT. This fixes a Codex-caught semantics bug: the prior signature took (limit, defaultLimit) where the second arg was misread as a cap. clampSearchLimit(x, 20) was actually allowing values up to 100, not 20. * feat(integrations): SSRF defense + recipe trust boundary (B1, B2, Fix 2, Fix 4, B3, B4) - B1: split loadAllRecipes into trusted (package-bundled) and untrusted (cwd/recipes, $GBRAIN_RECIPES_DIR) tiers. Only package-bundled recipes get embedded=true. Closes the fake trust boundary that let any cwd-local recipe bypass health-check gates. - B2: hard-block string health_checks for non-embedded recipes (was previously only blocked when isUnsafeHealthCheck regex matched, which the cwd recipe exploit bypassed). Embedded recipes still get the regex defense. - Fix 2: gate command DSL health_checks on isEmbedded. Non-embedded recipes cannot spawnSync. - Fix 4 + B3 + B4: gate http DSL health_checks on isEmbedded; for embedded recipes, validate URLs via new isInternalUrl() before fetch: - Scheme allowlist (http/https only): blocks file:, data:, blob:, ftp:, javascript: - IPv4 range check covering hex/octal/decimal/single-integer bypass forms - IPv6 loopback ::1 + IPv4-mapped ::ffff: (canonicalized hex hextets handled) - Metadata hostnames (AWS, GCP, instance-data) blocked - fetch with redirect: 'manual' + per-hop re-validation up to 3 hops Original PRs #105-109 by @garagon. Wave 3 collector branch reimplemented the fixes after Codex outside-voice review found that PRs #106/#108 alone did not actually gate cwd-local recipes (B1) and that PR #108 missed redirect-following SSRF (B3) and non-http schemes (B4). * feat(file_upload): path/slug/filename validation + remote-caller confinement (Fix 1, B5, H5, M4, Fix 5) - Fix 1 + B5 + H1: validateUploadPath uses realpathSync + path.relative to defeat symlink-parent traversal. lstatSync alone (the original PR #105 approach) only catches final-component symlinks; a symlinked parent dir still followed to /etc/passwd. Now the entire path chain is resolved. - H5: validatePageSlug uses an allowlist regex (alphanumeric + hyphens, slash-separated segments). Closes URL-encoded traversal (%2e%2e%2f), Unicode lookalikes, backslashes, control chars implicitly. - M4: validateFilename allowlist regex. Rejects control chars, backslash, RTL override (\u202E), leading dot/dash. Filename flows into storage_path so this matters for every storage backend. - Fix 5: clamp list_pages and get_ingest_log limits at the operation layer via new clampSearchLimit cap parameter (list_pages caps at 100, get_ingest_log at 50). Internal bulk commands bypass the operation layer and remain uncapped. - New OperationContext.remote flag distinguishes trusted local CLI from untrusted MCP callers. file_upload uses strict cwd confinement when remote=true (default), loose mode when remote=false (CLI). MCP stdio server sets remote=true; cli.ts and handleToolCall (gbrain call) set remote=false. Original PR #105 by @garagon. Issue #139 reported by @Hybirdss. * feat(search): query sanitization + structural prompt boundary (Fix 3, M1, M2, M3) - M1: restructure callHaikuForExpansion to use a system message that declares the user query as untrusted data, plus an XML-tagged <user_query> boundary in the user message. Layered defense with the existing tool_choice constraint (3 layers vs 1). - Fix 3 (regex sanitizer, defense-in-depth): sanitizeQueryForPrompt strips triple-backtick code fences, XML/HTML tags, leading injection prefixes, and caps at 500 chars. Original query is still used for downstream search; only the LLM-facing copy is sanitized. - M2: sanitizeExpansionOutput validates the model's alternative_queries array before it flows into search. Strips control chars, caps length, dedupes case-insensitively, drops empty/non-string items, caps to 2 items. - M3: console.warn on stripped content NEVER logs the query text — privacy-safe debug signal only. Original PR #107 by @garagon. M1/M2/M3 are wave 3 hardening per Codex review. * chore: bump version and changelog (v0.10.2) Security wave 3: 9 vulnerabilities closed across file_upload, recipe trust boundary, SSRF defense, prompt injection, and limit clamping. See CHANGELOG for full details. Contributors: - @garagon (PRs #105-109) - @Hybirdss (Issue #139) Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * docs: sync documentation with v0.10.2 security wave 3 - CLAUDE.md: document OperationContext.remote, new security helpers (validateUploadPath, validatePageSlug, validateFilename, isInternalUrl, parseOctet, hostnameToOctets, isPrivateIpv4, getRecipeDirs, sanitizeQueryForPrompt, sanitizeExpansionOutput), updated clampSearchLimit signature, recipe trust boundary, new test files - docs/integrations/README.md: replace string-form health_check example with typed DSL (string checks now hard-block for non-embedded recipes); add recipe trust boundary subsection - docs/mcp/DEPLOY.md: document file_upload remote-caller cwd confinement, symlink rejection, slug/filename allowlists Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * Minions v7 + v0.11.1 canonical migration + skillify (#130) * feat: add minion_jobs schema, migration v5, and executeRaw to BrainEngine Foundation for the Minions job queue system. Adds: - minion_jobs table (20 columns) with CHECK constraints, partial indexes, and RLS. Inspired by BullMQ's job model, adapted for Postgres. - Migration v5 creates the table for existing databases. - executeRaw<T>() method on BrainEngine interface for raw SQL access, needed by the Minions module for claim queries (FOR UPDATE SKIP LOCKED), token-fenced writes, and atomic stall detection. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: Minions job queue — queue, worker, backoff, types BullMQ-inspired Postgres-native job queue built into GBrain. No Redis. No external dependencies. Postgres transactions replace Lua scripts. - MinionQueue: submit, claim (FOR UPDATE SKIP LOCKED), complete/fail (token-fenced), atomic stall detection (CTE), delayed promotion, parent-child resolution, prune, stats - MinionWorker: handler registry, lock renewal, graceful SIGTERM, exponential backoff with jitter, UnrecoverableError bypass - MinionJobContext: updateProgress(), log(), isActive() for handlers - 8-state machine: waiting/active/completed/failed/delayed/dead/ cancelled/waiting-children Patterns stolen from: BullMQ (lock tokens, stall detection, flows), Sidekiq (dead set, backoff formula), Inngest (checkpoint/resume). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * test: 43 tests for Minions job queue Full coverage of the Minions module against PGLite in-memory: - Queue CRUD (9): submit, get, list, remove, cancel, retry, duplicate - State machine (6): waiting→active→completed/failed, retry→delayed→waiting - Backoff (4): exponential, fixed, jitter range, attempts_made=0 edge - Stall detection (3): detect stalled, counter increment, max→dead - Dependencies (5): parent waits, fail_parent, continue, remove_dep, orphan - Worker lifecycle (5): register, start-without-handlers, claim+execute, non-Error throws, UnrecoverableError bypass - Lock management (3): renewal, token mismatch, claim sets lock fields - Claim mechanics (4): empty queue, priority ordering, name filtering, delayed promotion timing - Cancel & retry (2): cancel active, retry dead Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: Minions CLI commands and MCP operations Wire Minions into the GBrain CLI and MCP layer: CLI (gbrain jobs): submit <name> [--params JSON] [--follow] [--dry-run] list [--status S] [--queue Q] [--limit N] get <id> — detailed view with attempt history cancel/retry/delete <id> prune [--older-than 30d] stats — job health dashboard work [--queue Q] [--concurrency N] — Postgres-only worker daemon 6 MCP operations (contract-first, auto-exposed via MCP server): submit_job, get_job, list_jobs, cancel_job, retry_job, get_job_progress Built-in handlers: sync, embed, lint, import. --follow runs inline. Worker daemon blocked on PGLite (exclusive file lock). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: update project documentation for Minions job queue CLAUDE.md: added Minions files to key files, updated operation count (36), BrainEngine method count (38), test file count (45), added jobs CLI commands. CHANGELOG.md: added Minions entry to v0.10.0 (background jobs, retry, stall detection, worker daemon). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: Minions v2 — agent orchestration primitives (pause/resume, inbox, tokens, replay) Adds the foundation for Minions as universal agent orchestration infrastructure. GBrain's Postgres-native job queue now supports durable, observable, steerable background agents. The OpenClaw plugin (separate repo) will consume these via library import, not MCP, for zero-latency local integration. ## New capabilities - **Concurrent worker** — Promise pool replaces sequential loop. Per-job AbortController for cooperative cancellation. Graceful shutdown waits for all in-flight jobs via Promise.allSettled. - **Pause/resume** — pauseJob clears the lock and fires AbortSignal on active jobs. Handlers check ctx.signal.aborted and exit cleanly. resumeJob returns paused jobs to waiting. Catch block skips failJob when signal.aborted. - **Inbox (separate table)** — minion_inbox table for sidechannel messages. sendMessage with sender validation (parent job or admin). readInbox is token-fenced and marks read_at atomically. Separate table avoids row bloat from rewriting JSONB on every send. - **Token accounting** — tokens_input/tokens_output/tokens_cache_read columns. updateTokens accumulates; completeJob rolls child tokens up to parent. USD cost computed at read time (no cost_usd column — pricing too volatile). - **Job replay** — replayJob clones a terminal job with optional data overrides. New job, fresh attempts, no parent link. ## Handler contract additions MinionJobContext now provides: - `signal: AbortSignal` — cooperative cancellation - `updateTokens(tokens)` — accumulate token usage - `readInbox()` — check for sidechannel messages - `log()` — now accepts string or TranscriptEntry ## MCP operations added pause_job, resume_job, replay_job, send_job_message — all auto-generate CLI commands and MCP server endpoints. ## Library exports package.json exports map adds ./minions and ./engine-factory paths so plugins can `import { MinionQueue } from 'gbrain/minions'` for direct library use. ## Instruction layer (the teaching) - skills/minion-orchestrator/SKILL.md — when/how to use Minions, decision matrix, lifecycle management, anti-patterns - skills/conventions/subagent-routing.md — cross-cutting rule: all background work goes through Minions - RESOLVER.md — trigger entries for agent orchestration - manifest.json — registered ## Schema migration v6 Additive: 3 token columns, paused status, minion_inbox table with unread index. Full Postgres + PGLite support. No backfill needed. ## Tests 65 tests (was 43): pause/resume (5), inbox (6), tokens (4), replay (4), concurrent worker context (3), plus all existing coverage. ## What's NOT in this commit Deferred to follow-up PRs: - LISTEN/NOTIFY subscribe (needs real Postgres E2E) - Resource governor (depends on concurrent worker stress testing) - Routing eval harness (needs API keys + benchmark data) - OpenClaw plugin (separate @gbrain/openclaw-minions-plugin repo) See docs/designs/MINIONS_AGENT_ORCHESTRATION.md for full CEO-approved design. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat(minions): migration v7 — agent_parity_layer schema Adds columns on minion_jobs (depth, max_children, timeout_ms, timeout_at, remove_on_complete, remove_on_fail, idempotency_key) plus the new minion_attachments table. Three partial indexes for bounded scans: idx_minion_jobs_timeout, idx_minion_jobs_parent_status, and uniq_minion_jobs_idempotency. Check constraints enforce non-negative depth and positive child cap / timeout. Additive migration — existing installs pick it up via ensureSchema on next use. No user action required. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * feat(minions): extend types for v7 parity layer Extends MinionJob with depth/max_children/timeout_ms/timeout_at/ remove_on_complete/remove_on_fail/idempotency_key. Extends MinionJobInput with the same options plus max_spawn_depth override. Adds MinionQueueOpts (maxSpawnDepth default 5, maxAttachmentBytes default 5 MiB). Adds AttachmentInput/Attachment shapes and ChildDoneMessage in the InboxMessage union. rowToMinionJob updated to pick up the new columns. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * feat(minions): attachments validator New module validateAttachment() gates every attachment write. Rejects empty filenames, path traversal (.., /, \), null bytes, oversized content (5 MiB default, per-queue override), invalid base64, and implausible content_type headers. Returns normalized { filename, content_type, content (Buffer), sha256, size } on success. The DB also enforces UNIQUE (job_id, filename) as defense-in-depth for concurrent addAttachment races — JS-only checks are not sufficient. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * feat(minions): queue v7 — depth, child cap, timeouts, cascade, idempotency, child_done Wraps completeJob and failJob in engine.transaction() so parent hook invocations (resolveParent, failParent, removeChildDependency) fold into the same transaction as the child update. A process crash between child and parent can't strand the parent in waiting-children anymore. Adds v7 behaviors: - Depth tracking. add() computes depth = parent.depth + 1 and rejects past maxSpawnDepth (default 5). - Per-parent child cap. add() takes SELECT ... FOR UPDATE on the parent, counts non-terminal children, rejects when count >= max_children. NULL max_children = no cap. - Per-job wall-clock timeout. claim() populates timeout_at when timeout_ms is set. New handleTimeouts() dead-letters expired rows with error_text='timeout exceeded'. Terminal — no retry. - Cascade cancel. cancelJob() walks descendants via recursive CTE with depth-100 runaway cap. Returns the root row. Re-parented descendants (parent_job_id NULL) are naturally excluded. - Idempotency. add() uses INSERT ... ON CONFLICT (idempotency_key) DO NOTHING RETURNING; falls back to SELECT when RETURNING is empty. Same key always yields the same job id. - child_done inbox. completeJob inserts {type:'child_done', child_id, job_name, result} into the parent's inbox in the same transaction as the token rollup, guarded by EXISTS so terminal/deleted parents skip without FK violation. New readChildCompletions(parent_id, lock_token, since?) helper; token-fenced like readInbox. - removeOnComplete / removeOnFail. Deletes the row after the parent hook fires, so parent policy sees consistent state. - Attachment methods. addAttachment validates via validateAttachment then INSERTs; UNIQUE (job_id, filename) backs the JS dup check. listAttachments, getAttachment, deleteAttachment round out the API. Fixes pre-existing inverted status bug: add() now puts children in waiting/delayed (not waiting-children) and atomically flips the parent to waiting-children in the same transaction. Tests no longer need manual UPDATE workarounds. Two correctness fixes: - Sibling completion race. Under READ COMMITTED, two grandchildren completing concurrently each saw the other as still-active in the pre-commit snapshot and neither flipped the parent. Fixed by taking SELECT ... FOR UPDATE on the parent row at the start of completeJob and failJob transactions, serializing siblings on the parent lock. - JSONB double-encode. postgres.js conn.unsafe(sql, params) auto- JSON-encodes parameters. Calling JSON.stringify(obj) first stored a JSON string literal (jsonb_typeof=string) and broke payload->>'key' queries silently. Removed JSON.stringify from three call sites (child_done inbox post, updateProgress, sendMessage). PGLite tolerated both forms so unit tests missed it — real-PG E2E caught it. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * feat(minions): worker — timeout safety net + handleTimeouts tick Worker tick now calls handleStalled() first, then handleTimeouts() — stall requeue wins over timeout dead-letter when both could fire in the same cycle. handleTimeouts() guards on lock_until > now() so stalled jobs take the retryable path. launchJob schedules a per-job setTimeout(timeout_ms) that fires ctx.signal as a best-effort handler interrupt. The timer is always cleared in .finally so process exit isn't delayed by a dangling timer. Handlers that respect AbortSignal stop cleanly; handlers that ignore it still get dead-lettered by the DB-side handleTimeouts. Removed post-completeJob and post-failJob parent-hook calls from the worker — those are now inside the queue method transactions. Worker becomes simpler and crash-safer. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * test(minions): 33 new unit tests for v7 parity layer Covers depth cap, per-parent child cap, timeout dead-letter, cascade cancel (including the re-parent edge case), removeOnComplete / removeOnFail, idempotency (single + concurrent), child_done inbox (posted in txn + survives child removeOnComplete + since cursor), attachment validation (oversize, path traversal, null byte, duplicates, base64), AbortSignal firing on pause mid-handler, catch-block skipping failJob when aborted, worker in-flight bookkeeping, token-rollup guard when parent already terminal, and setTimeout safety-net cleanup. Existing tests updated to remove the inverted-status manual UPDATE workarounds that the add() fix made obsolete. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * test(e2e): Minions v7 concurrency + OpenClaw resilience coverage minions-concurrency.test.ts spins two MinionWorker instances against the test Postgres, submits 20 jobs, and asserts zero double-claims (every job runs exactly once). This is the only test that actually proves FOR UPDATE SKIP LOCKED under real concurrency — PGLite runs on a single connection and can't exercise the race. minions-resilience.test.ts covers the six OpenClaw daily pains: 1. Spawn storm caps enforce under concurrent submit. 2. Agent stall → handleStalled() requeues; handleTimeouts() skips (lock_until guard). 3. Forgotten dispatches recoverable via child_done inbox. 4. Cascade cancel stops grandchildren mid-flight. 5. Deep tree fan-in (parent → 3 children → 2 grandchildren each) completes with the full inbox chain. 6. Parent crash/recovery resumes from persisted state. helpers.ts extends ALL_TABLES with minion_attachments, minion_inbox, and minion_jobs (FK dependents first) so E2E teardown doesn't leak rows between runs. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * chore: release v0.11.0 — Minions v7 agent orchestration primitives Bumps VERSION / package.json to 0.11.0. Adds CHANGELOG entry covering depth tracking, max_children, per-job timeouts, cascade cancel, idempotency keys, child_done inbox, removeOnComplete/Fail, attachments, migration v7, plus the two correctness fixes (sibling completion race and JSONB double-encode). TODOS.md captures the four v7 follow-ups: per-queue rate limiting, repeat/cron scheduler, worker event emitter, and waitForChildren convenience helpers. 1066 unit + 105 E2E = 1171 tests passing. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * fix(minions): unify JSONB inserts, tighten nullish coalescing Three non-blocker cleanups from post-ship review of v0.11.0: - queue.ts add() and completeJob(): pre-stringifying with JSON.stringify while other sites pass raw objects with $n::jsonb casts. postgres.js double-encodes if you stringify first — works on PGLite (text→JSONB auto-cast), fails silently on real PG. Unify on raw object + explicit $n::jsonb cast. - queue.ts readChildCompletions: since clause used sent_at > $2 relying on PG's implicit text→TIMESTAMPTZ coercion. Explicit $2::timestamptz is safer and clearer. - types.ts rowToMinionJob: parent_job_id used || which coerces 0 to null. Harmless today (SERIAL IDs start at 1) but ?? is semantically correct. All 110 unit tests pass. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * fix(minions): updateProgress missed $1::jsonb cast in unification Residual from c502b7e — updateProgress was the only remaining JSONB write without the explicit ::jsonb cast. Not broken (implicit cast works) but breaks the convention the prior commit unified everywhere else. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * doc: Minions v7 skill count + jobs subcommands (26 skills) README: bump skill count 25 → 26, add minion-orchestrator row, add `gbrain jobs` command family block so v0.11.0's headline feature is actually discoverable from the top-level commands reference. CLAUDE.md: unit test count 48 → 49 (minions.test.ts expanded), skill count 25 → 26, add minion-orchestrator to Key files + skills categorization, expand MinionQueue one-liner to cover v7 primitives (depth/child-cap, timeouts, idempotency, child_done inbox, removeOnComplete/Fail). 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * feat: Minions adoption UX — smoke test + migration + pain-triggered routing Teach OpenClaw when to reach for Minions vs native subagents. Ship three pieces so upgrading from v0.10.x actually lands for real users: - `gbrain jobs smoke` — one-command health check that submits a `noop` job, runs a worker, verifies completion, and prints engine-aware guidance (PGLite installs get the "daemon needs Postgres, use --follow" note). Fails loud if schema's below v7 so the user knows to `gbrain init`. - `skills/migrations/v0.11.0.md` — post-upgrade migration file the auto-update agent reads. Six steps: apply schema, run smoke, ask user via AskUserQuestion which mode they want (always / pain_triggered / off), write to `~/.gbrain/preferences.json`, sanity-check handlers, mark done. Completeness scores on each option so the recommendation is explicit. - `skills/conventions/subagent-routing.md` rewritten — was a "MUST use Minions for ALL background work" mandate, now reads preferences.json on every routing decision and branches on three modes. Mode B (pain_triggered) is the default: keep subagents until gateway drops state, parallel > 3, runtime > 5min, or user expresses frustration. Then pitch the switch in-session with a specific script. Rename pass: "Minions v7" → "Minions" in README (JOBS block), TODOS.md (P1 section header + depends-on), CHANGELOG.md v0.11.0 entry. v7 stays as the internal schema version in code/migration contexts. The product name is just Minions. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * doc(readme): promote Minions — 6 OpenClaw pains + how each is fixed The one-line mention in the skills table wasn't doing the work. Added a dedicated section between "How It Works" and "Getting Data In" that leads with the six multi-agent failures every OpenClaw user hits daily (spawn storms, hung handlers, forgotten dispatches, unstructured debugging, gateway crashes, runaway grandchildren) and maps each pain to the specific Minions primitive that fixes it. Includes the smoke test command, the adoption default (pain_triggered), and a pointer to skills/minion-orchestrator for the full patterns. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * test(bench): add harness for Minions vs OpenClaw subagent dispatch Shared harness (openclawDispatch + minionsHandler) using matching claude-haiku-4-5 calls on both sides so the delta measures queue+ dispatch overhead on top of identical LLM work. Includes statsFromResults (p50/p95/p99) and formatStats helpers. Uses `openclaw agent --local` embedded mode; does not test gateway multi-agent fan-out (documented in the harness header). * test(bench): durability under SIGKILL — Minions vs OpenClaw --local Headline bench for the claim: when the orchestrator dies mid-dispatch, Minions rescues via PG state + stall detection; OpenClaw --local loses in-flight work outright. Minions side: seed 10 active+expired-lock rows (exact state a SIGKILLed worker leaves) then run a rescue worker. Expect 10/10 completed. OpenClaw side: spawn 10 `openclaw agent --local` in parallel, SIGKILL each at 500ms, count pre-kill delivered output. Expect 0/10 — no persistence layer, nothing to recover. Budget: ~$0 (Minions handlers sleep 10ms; OC calls die at 500ms so partial LLM billing is negligible). * test(bench): per-dispatch throughput — Minions vs OpenClaw --local 20 serial dispatches each side, identical claude-haiku-4-5 call with the same trivial prompt. p50/p95/p99 reported via statsFromResults. Serial (not parallel) so the per-dispatch cost is measured honestly and LLM token spend stays bounded (~$0.08 total). Minions: one queue, one worker, one concurrency. Submit → poll to completion before next submit. OpenClaw: N sequential `openclaw agent --local` spawns. * test(bench): fan-out — Minions 10-wide concurrency vs 10 parallel OC spawns Parent dispatches 10 children, waits for all to return. Minions uses worker concurrency=10 sharing one warm process; OpenClaw parallel `openclaw agent --local` spawns, each boots its own runtime. 3 runs × 10 children per run. Reports ok count and wall time per run plus summary. Honest caveat documented: does not test OC gateway multi-agent fan-out — that needs a custom WS client and LLM-backed parent agent. This measures what users script today. Budget: ~$0.12 LLM spend. * test(bench): memory — 10 in-flight subagents, single-proc vs 10-proc cost Measures resident memory for keeping 10 subagents in flight. Minions: one worker process, concurrency=10 with handlers that park on a promise — sample RSS of the test process via process.memoryUsage(). OpenClaw: 10 parallel `openclaw agent --local` processes, sum their RSS via `ps -o rss=`. Handlers are cheap sleeps, no LLM — we want harness memory, not LLM client state. Budget: $0. * test(bench): fan-out — don't gate on OC success rate, report numbers Initial run showed OC parallel `--local` at 10-wide hits 40% failure rate (17/30 across 3 runs). That's the finding, not a test bug — process startup stampede + LLM rate limits. Bench now prints error samples and reports the numbers instead of gating. Minions side still gates at 90% (30/30 observed in practice). * doc(benchmarks): Minions vs OpenClaw --local subagent dispatch Real numbers on four claims: durability, throughput, fan-out, memory. Same claude-haiku-4-5 call on both sides so the delta is queue+dispatch+ process cost on top of identical LLM work. Headline: Minions rescues 10/10 from a SIGKILLed worker in 458ms while OpenClaw --local loses all 10; ~10× faster per dispatch (778ms p50 vs 8086ms p50); ~21× faster at 10-wide fan-out AND 100% reliable vs OC's 43% failure rate; 2 MB vs 814 MB to keep 10 subagents in flight. Honest caveats section covers what this doesn't test (OC gateway multi-agent, load tests, other models). Fully reproducible via test/e2e/bench-vs-openclaw/. * doc(readme): inject Minions vs OpenClaw bench numbers Headline deltas now in the Minions section: 10/10 vs 0/10 on crash, ~10× faster per dispatch, ~21× faster fan-out at 10-wide with 0% failure vs 43%, ~400× less memory. Links to the full bench doc. Prose first said Minions "fixes all six pains." Now it shows the numbers that prove it. * bench: production Wintermute benchmark — Minions 753ms vs sub-agent timeout Real deployment: 45K-page brain on Render+Supabase. Task: pull 99 tweets, write brain page, commit, sync. Minions: 753ms, $0. Sub-agent: gateway timeout (>10s, couldn't even spawn under production load). Also: 19,240 tweets backfilled across 36 months in 15 min at $0. Sub-agents would cost $1.08 and fail 40% of spawns. * bench: tweet ingestion — Minions 719ms vs OpenClaw 12.5s (17×) Production benchmark with runnable test code: - test/e2e/bench-vs-openclaw/tweet-ingest.bench.ts (reusable) - docs/benchmarks/2026-04-18-tweet-ingestion.md (publishable) Task: pull 100 tweets from X API, write brain page, commit, sync. Minions: 719ms mean, $0, 100% success. OpenClaw: 12,480ms mean, $0.03/run, 60% success (gateway timeouts). At scale: 36-month backfill, 19K tweets, 15 min, $0 vs est. $1.08. * doc(benchmarks): Wintermute production data point for Minions vs OpenClaw Adds a production-environment data point to the Minions README section: one month of tweet ingest on Wintermute (Render + Supabase + 45K-page brain) ran end-to-end in 753ms for \$0.00 via Minions, while the equivalent sessions_spawn hit the 10s gateway timeout and produced nothing. Full methodology + logs in docs/benchmarks/2026-04-18-minions-vs-openclaw-production.md. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat(core): preferences.ts + cli-util.ts — foundations for v0.11.1 Adds two foundational modules that apply-migrations (Lane A-4), the v0.11.0 orchestrator (Lane C-1), and the stopgap script (Lane C-4) all depend on. - src/core/preferences.ts: atomic-write ~/.gbrain/preferences.json (mktemp + rename, 0o600, forward-compatible for unknown keys) with validateMinionMode, loadPreferences, savePreferences. Plus appendCompletedMigration + loadCompletedMigrations for the ~/.gbrain/migrations/completed.jsonl log (tolerates malformed lines). Uses process.env.HOME || homedir() so $HOME overrides work in CI and tests; Bun's os.homedir() caches the initial value and ignores later mutations. - src/core/cli-util.ts: promptLine(prompt) helper, extracted from src/commands/init.ts:212-224. Shared so init, apply-migrations, and the v0.11.0 orchestrator's mode prompt don't each reinvent it. test/preferences.test.ts: 21 unit tests covering load/save atomicity, 0o600 perms, forward-compat for unknown keys, minion_mode validation, completed.jsonl JSONL append idempotence, auto-ts population, malformed- line tolerance in loadCompletedMigrations. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat(init): add --migrate-only flag (schema-only, no saveConfig) Context: v0.11.0 migration orchestrators need a safe way to re-apply the schema against an existing brain without risking a config flip. Today running bare `gbrain init` with no flags defaults to PGLite and calls saveConfig, which would silently overwrite an existing Postgres database_url — caught by Codex in the v0.11.1 plan review as a show-stopper data-loss bug. The new --migrate-only path: - loadConfig() reads the existing config (does NOT call saveConfig) - errors out with a clear "run gbrain init first" if no config exists - connects via the already-configured engine, calls engine.initSchema(), disconnects - --json emits structured success/error payloads Everything downstream in the v0.11.1 migration chain (apply-migrations, the stopgap bash script, the package.json postinstall hook) will invoke this flag rather than bare gbrain init. test/init-migrate-only.test.ts: 4 tests covering the no-config error path, --json error payload shape, happy-path with a PGLite fixture (verifies config.json content is byte-identical after the call — the real invariant), and idempotent rerun. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat(migrations): TS registry replaces filesystem migration scan Context: Codex flagged that bun build --compile produces a self-contained binary, and the existing findMigrationsDir() in upgrade.ts:145 walks skills/migrations/v*.md on disk — which fails on a compiled install because the markdown files aren't bundled. The plan's fix is a TS registry: migrations are code, imported directly, visible to both source installs and compiled binaries. - src/commands/migrations/types.ts: shared Migration, OrchestratorOpts, OrchestratorResult types. - src/commands/migrations/index.ts: exports the migrations[] array, getMigration(version), and compareVersions() (semver comparator). The feature_pitch data that lived in the MD file frontmatter now lives here as a code constant on each Migration, so runPostUpgrade's post-upgrade pitch printer can consume it without a filesystem read. - src/commands/migrations/v0_11_0.ts: stub orchestrator + pitch. The full phase implementation lands in Lane C-1; for now the stub throws a clear "not yet implemented" so apply-migrations --list (Lane A-4) can still enumerate the migration. test/migrations-registry.test.ts: 9 tests covering ascending-semver ordering, feature_pitch shape invariants, getMigration lookup, and compareVersions edge cases (equal / newer / older / single-digit across major bumps). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat(cli): gbrain apply-migrations — migration runner CLI Reads ~/.gbrain/migrations/completed.jsonl, diffs against the TS migration registry, runs pending orchestrators. Resumes status:"partial" entries (the stopgap bash script writes these so v0.11.1 apply-migrations can pick up where it left off). Idempotent: rerunning when up-to-date exits 0. Flags: --list Show applied + partial + pending + future. --dry-run Print the plan; take no action. --yes / --non-interactive Skip prompts (used by runPostUpgrade + postinstall). --mode <a|p|o> Preset minion_mode (bypasses the Phase C TTY prompt). --migration vX.Y.Z Force-run one specific version. --host-dir <path> Include $PWD in host-file walk (default is $HOME/.claude + $HOME/.openclaw only). --no-autopilot-install Skip Phase F. Diff rule (Codex H9): apply when no status:"complete" entry exists AND migration.version ≤ installed VERSION. Previously proposed rule was "version > currentVersion", which would SKIP v0.11.0 when running v0.11.1; regression test in apply-migrations.test.ts pins the correct semantics. Registered in src/cli.ts CLI_ONLY Set; dispatched before connectEngine so each phase owns its own engine/subprocess lifecycle (no double-connect when the orchestrator shells out to init --migrate-only or jobs smoke). test/apply-migrations.test.ts: 18 unit tests covering parseArgs for every flag, indexCompleted/statusForVersion correctness (including stopgap-then- complete transition), and buildPlan's four buckets (applied / par…

* fix(link-extraction): v0.10.5 drive works_at + advises accuracy on rich prose Extends inferLinkType patterns to cover rich-prose phrasings that miss with v0.10.4 regexes. Targets the residuals called out in TODOS.md: works_at at 58% type accuracy, advises at 41%. WORKS_AT_RE additions: - Rank-prefixed: "senior engineer at", "staff engineer at", "principal/lead" - Discipline-prefixed: "backend/frontend/full-stack/ML/data/security engineer at" - Possessive time: "his/her/their/my time at" - Leadership beyond "leads engineering": "heads up X at", "manages engineering at", "runs product at", "leads the [team] at" - Role nouns: "role at", "position at", "tenure as", "stint as" - Promotion patterns: "promoted to staff/senior/principal at" ADVISES_RE additions: - Advisory capacity: "in an advisory capacity", "advisory engagement/partnership/contract" - "as an advisor": "joined as an advisor", "serves as technical advisor" - Prefixed advisor nouns: "strategic/technical/security/product/industry advisor to|at" - Consulting: "consults for", "consulting role at|with" New EMPLOYEE_ROLE_RE page-level prior: fires when the page describes the subject as an employee (senior/staff/principal engineer, director, VP, CTO/CEO/CFO) at some company. Biases outbound company refs toward works_at when per-edge context is possessive or narrative without an explicit work verb. Scoped to person -> company links only. Precedence: investor > advisor > employee (investors often hold board seats which would otherwise mis-classify as advise/works_at). ADVISOR_ROLE_RE broadened from "full-time/professional/advises multiple" to catch any page that self-identifies the subject as an advisor ("is an advisor", "serves as advisor", possessive "her advisory work/role/engagement"). Tests: 65 pass (16 new v0.10.5 coverage tests + 4 regression guards against v0.10.4 tightenings). Templated benchmark still 88.9% type_accuracy (10/10 on works_at and advises). Rich-prose measurement requires the multi-axis report upgrade (next commit) to validate retroactively. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat(eval): type-accuracy runner on rich-prose corpus + wire into all.ts New Category 2 in BrainBench: per-link-type accuracy measured directly on the 240-page rich-prose world-v1 corpus. Distinct from Cat 1's retrieval metrics, this measures whether inferLinkType() correctly classifies extracted edges when the prose varies (the 58% works_at and 41% advises residuals that v0.10.5 regexes targeted). How it works: 1. Loads all pages from eval/data/world-v1/ 2. Derives GOLD expected edges from each page's _facts metadata (founders → founded, investors → invested_in, advisors → advises, employees → works_at, attendees → attended, primary_affiliation + role drives person-page outbound type) 3. Runs extractPageLinks() on each page → INFERRED edges 4. Per (from, to) pair, compares inferred type vs gold type 5. Emits per-link-type table: correct / mistyped / missed / spurious + type accuracy + recall + precision + strict F1 (triple match) 6. Full confusion matrix rows=gold, cols=inferred v0.10.5 validation on 240-page corpus (up from pre-v0.10.5 baselines): - works_at: 58% → 100.0% (+42 pts) — 10/10 correct, 0 mistyped - advises: 41% → 88.2% (+47 pts) — 15/17 correct - attended: — → 100.0% 131/134 recall - founded: 100% → 100.0% 40/40 - invested_in: 89% → 92.0% 69/75 - Overall: 88.5% → 95.7% type accuracy (conditional on edge found) Strict F1 overall: 53.7%. Lower because the _facts-based gold set only captures core relationships; rich prose extracts many peripheral mentions (190 spurious "mentions" edges) that aren't bugs but are correctly-typed prose references without a _facts counterpart. Spurious counts are signal for future type-precision tuning, not failure. Wired into eval/runner/all.ts as Cat 2 so every full benchmark run includes the rich-prose type accuracy table alongside retrieval metrics. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat(eval): Phase 2 adapter interface + EXT-1 ripgrep+BM25 baseline Phase 2 credibility unlock: BrainBench now compares gbrain to external baselines on the same corpus and queries. Transforms the benchmark from internal ablation ("gbrain-graph beats gbrain-grep") to category comparison ("gbrain-graph beats classic BM25 by 32 pts P@5"). This is the #1 fix from the 4-review arc — addresses Codex's core critique that v1's before/after was self-referential. Added: eval/runner/types.ts — Adapter interface (v1.1 spec) eval/runner/adapters/ripgrep-bm25.ts — EXT-1 classic IR baseline eval/runner/adapters/ripgrep-bm25.test.ts — 11 unit tests, all pass eval/runner/multi-adapter.ts — side-by-side scorer Adapter interface (eng pass 2 spec): - Thin 3-method Strategy: init(rawPages, config), query(q, state), snapshot(state) - BrainState is opaque to runner (never inspected) - Raw pages passed in-memory; gold/ never crosses adapter boundary (structural ingestion-boundary enforcement) - PoisonDisposition enum reserved for future poison-resistance scoring EXT-1 ripgrep+BM25: - Classic Lucene-variant IDF + k1/b tuned at standard 1.5/0.75 - Title tokens double-weighted for entity-page slug-match bias - Stopword filter, alphanumeric tokenization, stable lexicographic tie-break - Pure in-memory inverted index — no external deps, ~100 LOC core First side-by-side results on 240-page rich-prose corpus, 145 relational queries: | Adapter | P@5 | R@5 | Correct top-5 | |---------------|--------|--------|---------------| | gbrain-after | 49.1% | 97.9% | 248/261 | | ripgrep-bm25 | 17.1% | 62.4% | 124/261 | | Delta | +32.0 | +35.5 | +124 | gbrain-after is the hybrid graph+grep config from PR #188. Ripgrep+BM25 is a genuinely strong classic-IR baseline (BM25 is what Lucene/Elasticsearch ship). gbrain's ~+32-point lead on relational queries reflects real work by the knowledge graph layer: typed links + traversePaths surface the correct answers in top-K that BM25 only pulls in via partial-text overlap. Next in Phase 2: EXT-2 vector-only RAG + EXT-3 hybrid-without-graph adapters. Both plug into the same Adapter interface. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat(eval): Phase 2 EXT-2 vector-only RAG adapter Second external baseline for BrainBench. Pure cosine-similarity ranking using the SAME text-embedding-3-large model gbrain uses internally — apples-to-apples on the embedding layer so any gbrain lead reflects the graph + hybrid fusion, not a better embedder. Files: eval/runner/adapters/vector-only.ts ~130 LOC eval/runner/adapters/vector-only.test.ts 6 unit tests (cosine math) Design: - One vector per page (title + compiled_truth + timeline, capped 8K chars). - No chunking (intentional; chunked vector RAG would be EXT-2b later). - No keyword fallback (that's EXT-3 hybrid-without-graph). - Embeddings in batches of 50 via existing src/core/embedding.ts (retry+backoff). - Cost on 240 pages: ~$0.02/run. Three-adapter side-by-side on 240-page rich-prose corpus, 145 relational queries: | Adapter | P@5 | R@5 | Correct top-5 | |---------------|--------|--------|---------------| | gbrain-after | 49.1% | 97.9% | 248/261 | | ripgrep-bm25 | 17.1% | 62.4% | 124/261 | | vector-only | 10.8% | 40.7% | 78/261 | Interesting finding: vector-only scores WORSE than BM25 on relational queries like "Who invested in X?" — exact entity match matters more than semantic similarity for these templates. BM25 nails the entity-name term; vector-only returns topically-similar-but-not-mentioning pages. This is the known failure mode of pure-vector RAG on precise relational/identity queries. Real-world vector RAG systems always add keyword fallback; EXT-3 (hybrid-without-graph) will be that fairer comparator. gbrain's lead widens in vector-only comparison: +38.4 pts P@5, +57.2 pts R@5. The graph layer is doing the heavy lifting for relational traversal; pure vector RAG can't express "traverse 'attended' edges from this meeting page." Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat(eval): Phase 2 EXT-3 hybrid-without-graph adapter — graph isolated Third and closest-to-gbrain external baseline. Runs gbrain's full hybrid search (vector + keyword + RRF fusion + dedup) WITHOUT the knowledge-graph layer. Same engine, same embedder, same chunking, same hybrid fusion — only traversePaths + typed-link extraction turned off. This is the decisive comparator for "does the knowledge graph do useful work?" Same everything-else, only graph differs. Any lead gbrain-after has over EXT-3 is 100% attributable to the graph layer. Files: eval/runner/adapters/hybrid-nograph.ts — ~110 LOC Implementation: - New PGLiteEngine per run; auto_link set to 'false' (belt). - importFromContent() used instead of bare putPage() so chunks + embeddings get populated (hybridSearch needs them). - NO runExtract() call — typed links/timeline stay empty (suspenders). - hybridSearch(engine, q.text) answers every query. Aggregate chunks to page-level by best chunk score. FOUR-adapter side-by-side on 240-page rich-prose corpus, 145 relational queries: | Adapter | P@5 | R@5 | Correct/Gold | |-----------------|--------|--------|--------------| | gbrain-after | 49.1% | 97.9% | 248/261 | | hybrid-nograph | 17.8% | 65.1% | 129/261 | | ripgrep-bm25 | 17.1% | 62.4% | 124/261 | | vector-only | 10.8% | 40.7% | 78/261 | The headline delta nobody can hand-wave away: gbrain-after → hybrid-nograph = +31.4 P@5, +32.9 R@5 hybrid-nograph → ripgrep-bm25 = +0.7 P@5, +2.7 R@5 Hybrid search (vector+keyword+RRF) over pure BM25 gains ~1 point. The knowledge graph layer over hybrid gains ~31 points. The graph is doing the work; adding it to a retrieval stack is what actually moves the needle on relational queries. The vector/keyword/BM25 debate is a footnote. Timing: hybrid-nograph init is ~2 min (embeds 240 pages once); query loop is fast. gbrain-after is ~1.5s total because traversePaths doesn't need embeddings. Runs at ~$0.02 Opus-equivalent in embedding cost. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat(eval): Phase 2 query validator + Tier 5 Fuzzy + Tier 5.5 synthetic + N=5 tolerance bands Closes multiple Phase 2 items in one commit since they form a cohesive package: query schema enforcement + new query tiers + per-query-set statistical rigor. Added: eval/runner/queries/validator.ts — hand-rolled Query schema validator eval/runner/queries/validator.test.ts — 24 unit tests, all pass eval/runner/queries/tier5-fuzzy.ts — 30 hand-authored Tier 5 Fuzzy/Vibe queries eval/runner/queries/tier5_5-synthetic.ts — 50 SYNTHETIC-labeled outsider-style queries (author: "synthetic-outsider-v1") eval/runner/queries/index.ts — aggregator + validateAll() Modified: eval/runner/multi-adapter.ts — N=5 runs per adapter (BRAINBENCH_N override), page-order shuffle, mean±stddev reporting Query validator (hand-rolled, no zod dep to match gbrain codebase style): - Temporal verb regex enforces as_of_date (per eng pass 2 spec): /\\b(is|was|were|current|now|at the time|during|as of|when did)\\b/i - Validates tier enum, expected_output_type enum, gold shape per type - gold.relevant must be non-empty slug[] for cited-source-pages queries - abstention requires gold.expected_abstention === true - externally-authored tier requires author field - batch validation catches duplicate IDs Tier 5 Fuzzy/Vibe (30 queries, hand-authored): - Vague recall: "Someone who was a senior engineer at a biotech company..." - Trait-based: "The engineer who pushed back on microservices" - Cultural/epithet: "Who is known as a 'systems builder' in security?" - Abstention bait: "Which Layer 1 project did the crypto guy leave?" (prose mentions but never names; good systems abstain) - Addresses Codex's circularity critique — vague queries where graph-heavy systems shouldn't inherently win. Tier 5.5 Synthetic Outsider (50 queries, AI-authored placeholder): - Clearly labeled author: "synthetic-outsider-v1" - Phrasing variety not in the 4 template families: * fragment style ("crypto founder Goldman Sachs background") * polite/natural ("Can you pull up what we have on...") * comparison ("What is the difference between X and Y?") * follow-up ("And who else advises Orbit Labs?") * typos/misspellings ("adam lopez bioinformatcis") * similarity ("Find me someone like Alice Davis...") * imperative ("Pull up Alice Davis") - Real Tier 5.5 from outside researchers supersedes synthetic via PRs to eval/external-authors/ (docs ship in follow-up commit). N=5 tolerance bands: - Default N=5, override via BRAINBENCH_N env var (e.g. BRAINBENCH_N=1 for dev loops) - Per-run seeded Fisher-Yates shuffle of page ingest order (LCG seed = run_idx+1) - Surfaces order-dependent adapter bugs (tie-break-by-first-seen etc.) - Reports mean ± sample-stddev per metric - "stddev = 0" is honest signal that the adapter is deterministic, not a bug. LLM-judge metrics (future) will naturally produce non-zero stddev. Validation: all 80 Tier 5 + 5.5 queries pass validateAll(). 24 validator unit tests pass. Next commit: world.html contributor explorer (Phase 3). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat(eval): Phase 3 world.html explorer + eval:* CLI surface Contributor DX magical moment. Static HTML explorer renders the full canonical world (240 entities) as an explorable tree, opens in any browser, zero install. Every string HTML-entity-encoded (XSS-safe — direct vuln class per eng pass 2, confidence 9/10). Added: eval/generators/world-html.ts — renderer (~240 LOC; single-file HTML with inline CSS + minimal JS) eval/generators/world-html.test.ts — 16 tests (XSS + rendering correctness) eval/cli/world-view.ts — render + open in default browser eval/cli/query-validate.ts — CLI wrapper for queries/validator eval/cli/query-new.ts — scaffold a query template Modified: package.json — 7 new eval:* scripts .gitignore — ignore generated world.html package.json scripts shipped: bun run test:eval all eval unit tests (57 pass) bun run eval:run full 4-adapter N=5 side-by-side bun run eval:run:dev N=1 fast dev iteration bun run eval:world:view render world.html + open in browser bun run eval:world:render render only (CI-friendly, --no-open) bun run eval:query:validate validate built-in T5+T5.5 (or a file path) bun run eval:query:new scaffold a new Query JSON template bun run eval:type-accuracy per-link-type accuracy report XSS safety: escapeHtml() encodes the 5 critical chars (& < > " '). Tested directly with representative Opus-generated attacks: <img src=x onerror=alert('xss')> → <img src=x onerror=alert('xss')> <script>fetch('/steal')</script> → <script>fetch('/steal')</script> Ledger metadata (generated_at, model) also escaped — covers the less obvious attack surface where Opus could emit tag-like content into the metadata file. world.html structure: - Left rail: entities grouped by type with counts (companies, people, meetings, concepts), alphabetical within type - Right pane: per-entity cards with title + slug + compiled_truth + timeline + canonical _facts as collapsed JSON - URL fragment deep-links (#people/alice-chen) - Sticky rail on desktop; responsive stack on mobile - Vanilla JS for active-link highlighting on scroll (no framework) Generated file: ~1MB for 240 entities (full prose). Gitignored; rebuild with `bun run eval:world:view`. Regeneration is ~50ms. Contributor TTHW (Tier 5.5 query authoring): 1. bun run eval:world:view # see entities 2. bun run eval:query:new --tier externally-authored --author "@me" 3. edit template with real slug + query text 4. bun run eval:query:validate path/to/file.json 5. submit PR Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * docs(eval): Phase 3 contributor docs + CI workflow for eval/ tests Ships the contributor-onboarding surface promised in the plan. With this commit, external researchers have a self-serve path from clone to PR in under 5 minutes. Added: eval/README.md — 5-minute quickstart, directory map, methodology one-pager, adapter scorecard eval/CONTRIBUTING.md — three contributor paths: 1. Write Tier 5.5 queries 2. Submit an external adapter 3. Reproduce a scorecard eval/RUNBOOK.md — operational troubleshooting: generation failures, runner failures, query validation, world.html rendering, CI eval/CREDITS.md — contributor attribution (synthetic-outsider-v1 labeled as placeholder; real submissions land here) .github/PULL_REQUEST_TEMPLATE/tier5-queries.md — structured PR template for Tier 5.5 submissions .github/workflows/eval-tests.yml — CI: validates queries, runs all eval unit tests, renders world.html on every PR touching eval/** or src/core/link-extraction.ts CI scope (intentionally narrow): - Triggers on paths: eval/**, src/core/link-extraction.ts, src/core/search/** - Runs: bun run eval:query:validate (80 queries), test:eval (57 tests), eval:world:render (smoke-test the HTML renderer) - Pinned actions by commit SHA (matches existing .github/workflows/test.yml) - Zero API calls — all Opus/OpenAI paths stubbed or skipped in unit tests - Fast: ~30s total wall clock Contributor TTHW (clone → first merged PR): - Path 1 (Tier 5.5 queries): ~5 min - Path 2 (external adapter): ~30 min for a simple adapter - Path 3 (reproduce scorecard): ~15 min wall clock (N=5 run) Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(eval): teardown PGLite engines so bun run eval:run exits 0 The multi-adapter runner left PGLite engines alive after each run. GbrainAfterAdapter and HybridNoGraphAdapter both instantiate a PGLiteEngine in init() but never disconnect it; Bun's shutdown path exits with code 99 when embedded-Postgres workers outlive main(). Added optional `teardown?(state)` to the Adapter interface, implemented it on both engine-backed adapters, and call it from scoreOneRun after the N=5 loop. ripgrep-bm25 and vector-only hold no DB resources and don't need a teardown. Verified: gbrain-after, hybrid-nograph, ripgrep-bm25, vector-only all exit 0 at N=1. Full test:eval passes (57 tests). No metric change. * docs(bench): 2026-04-19 multi-adapter scorecard Reproducibility run of the 4-adapter side-by-side at commit b81373d (branch garrytan/gbrain-evals). N=5, 240-page corpus, 145 relational queries from world-v1. Headline: gbrain-after 49.1% P@5 / 97.9% R@5. hybrid-nograph 17.8% / 65.1%. ripgrep-bm25 17.1% / 62.4%. vector-only 10.8% / 40.7%. All adapters deterministic (stddev = 0 across the 5 runs per adapter). Matches the scorecard in eval/README.md byte-for-byte for the three deterministic adapters; hybrid-nograph matches within tolerance bands. * docs(bench): 2026-04-19 gbrain v0.11.1 vs v0.12.1 regression comparison Runs the same eval harness against two gbrain src/ trees on the same 240-page corpus and 145 queries. Patches the v0.11 copy's gbrain-after adapter to use getLinks/getBacklinks (v0.11 has no traversePaths) with identical direction+linkType semantics. gbrain-after P@5 22.1% -> 49.1% (+27 pts); R@5 54.6% -> 97.9% (+43 pts); correct-in-top-5 99 -> 248 (+149). hybrid-nograph flat at 17.8% / 65.1% on both (v0.12 didn't touch hybridSearch / chunking). Driver is extraction quality, not graph presence: v0.12 emits 499 typed links (v0.11: 136, x3.7) and 2,208 timeline entries (v0.11: 27, x82) on the same 240 pages. Sharpens the April-18 "graph layer does the work" claim -- on v0.11 that architecture only beat hybrid-nograph by 4.3 points; the 31-point lead in the multi-adapter scorecard comes from graph + high-quality extract in combination. * feat(eval): BrainBench v1 portable JSON schemas + gold templates Adds the v1→v2 contract boundary for BrainBench. 6 JSON schemas at eval/schemas/ pin the shape of every artifact a stack must emit to be scorable: corpus-manifest, public-probe (PublicQuery with gold stripped), tool-schema (12 read + 3 dry_run tools, 32K tool-output cap), transcript, scorecard (N ∈ {1, 5, 10}), evidence-contract (structured judge input). 8 gold file templates at eval/data/gold/ scaffold the sealed qrels, contradictions, poison items, and citation labels. Empty-but-valid skeletons; Day 3b fills them with real content once the amara-life-v1 corpus generates. 48 tests validate schema syntax, $schema/$id/title/type headers, round-trip stability, and cross-schema coherence (new Page types in manifest enum, tool counts, token cap, N enum). When v2 ports to Python + Inspect AI + Docker, these schemas are the boundary. Same fixtures, same tool contracts, zero rework. * feat(eval): amara-life-v1 skeleton + Page.type enum for email/slack/cal/note Deterministic procedural generator for the twin-amara-lite fictional-life corpus (BrainBench v1 Cat 5/8/9/11 target). 15 contacts picked from world-v1, 50 emails + 300 Slack messages across 4 channels + 20 calendar events + 8 meeting transcripts + 40 first-person notes. Mulberry32 PRNG gives byte-identical output under reseed. Plants 10 contradictions + 5 stale facts + 5 poison items + 3 implicit preferences at deterministic positions. Fixture_ids are unique across the corpus so gold/contradictions.json + gold/poison.json + gold/implicit- preferences.json can cross-reference by stable ID. PageType extended in both src/core/types.ts and eval/runner/types.ts to include email | slack | calendar-event | note (+ meeting on the production side). src/core/markdown.ts inferType() heuristics updated for the new one-slash slug prefixes (emails/em-NNNN, slack/sl-NNNN, cal/evt-NNNN, notes/YYYY-MM-DD-topic, meeting/mtg-NNNN). 17 tests cover counts (50/300/20/8/40), perturbation counts (exact 10/5/5/3), seed determinism + divergence, slug regex conformance (matches eval/runner/queries/validator.ts:131 one-slash rule), unique fixture_ids, amara-in-every-email invariant, calendar dtstart < dtend, and Amara-is- attendee on every meeting. * feat(eval): amara-life-gen.ts with structured cache key + $20 cost gate Opus prose expansion of the amara-life-v1 skeleton. Per-item structured cache key = sha256({schema_version, template_id, template_hash, model_id, model_params, seed, item_spec_hash}). Prompt-template tweak changes template_hash; only those items regenerate. Schema bump changes schema_version; everything invalidates cleanly. Interrupted runs resume from the last cached item; zero re-spend. Cost-gated at $20 hard-stop with Anthropic input/output pricing tracking. Dry-run mode (--dry-run) executes the full pipeline with stub bodies for smoke-testing the I/O layout without LLM spend. --max N caps items per type for debugging. --force ignores cache. Writes per-format outputs under eval/data/amara-life-v1/: inbox/emails.jsonl (one email per line with body_text appended) slack/messages.jsonl (one message per line with text appended) calendar.ics (RFC-5545 VEVENT format, templated — no LLM) meetings/<id>.md (transcript with YAML frontmatter) notes/<YYYY-MM-DD-topic>.md (first-person journal) docs/*.md (6 reference docs, templated — no LLM) corpus-manifest.json (per eval/schemas/corpus-manifest.schema.json, including per-item content_sha256 and generator_cache_key) Perturbation hints (contradiction, stale-fact, poison, implicit- preference) flow through the prompt so Opus weaves the specific claim into each item's body. Poison items are hand-crafted to include paraphrased prompt-injection attempts (not literal 'IGNORE ALL PREVIOUS' — defense is the structured-evidence judge contract at Day 5, not regex redaction). New package.json scripts: eval:generate-amara-life # real run (~$12 Opus estimated) eval:generate-amara-life:dry # smoke test, zero spend test:eval extended to include test/eval/. 10 cache-key tests cover determinism, invalidation across every field of the key, canonical JSON stability under object-key reorder, and per-skeleton-item spec-hash uniqueness (50 distinct hashes for 50 distinct emails). * chore: bump version and changelog (v0.15.0) Resets package.json from stale 0.13.1 to 0.15.0 (matches VERSION). v0.14.0 shipped with the stale package.json version; this sync catches that up and moves to v0.15.0 in one step. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * docs: update CLAUDE.md + README + eval/README for v0.15.0 BrainBench CLAUDE.md: adds a full BrainBench section to the Key Files list — 14 new entries covering eval/README.md, multi-adapter.ts, types.ts (with new PublicPage/PublicQuery), adapters/, queries/, type-accuracy.ts, adversarial.ts, all.ts, world.ts/gen.ts, world-html.ts, amara-life.ts, amara-life-gen.ts, schemas/, data/world-v1/, data/gold/, data/amara-life-v1/, docs/benchmarks/, and test/eval/. Adds 3 new test/eval/ lines to the unit-tests catalog. eval/README.md: file tree updated to reflect v0.15 additions — data/amara-life-v1/, data/gold/, schemas/, generators/amara-life.ts + amara-life-gen.ts, runner/all.ts + adversarial.ts. README.md: updates hero benchmark numbers (L7 intro + L353 mid-page) from v0.10.5 PR #188 numbers (R@5 83→95, P@5 39→45) to current v0.12.1 4-adapter numbers (P@5 49.1% · R@5 97.9% · +31.4 pts vs hybrid-nograph). Adds the v0.11→v0.12 regression comparison as the secondary reference. Deeper-section tables (L422+) labeled "BrainBench v1 (PR #188)" are preserved as historical data. CHANGELOG is untouched — /ship already wrote the v0.15.0 entry. TODOS.md is untouched — Cat 5/6/8/9/11 remain open (only foundations shipped in v0.15.0; Cat runners ship in v1 Complete follow-ups). Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat(eval): Day 4 — pdf-parse + flight-recorder + tool-bridge (dry_run + expand:false) Three infrastructure modules for BrainBench v1 Complete Cats 5/8/9/11. **eval/runner/loaders/pdf.ts** — Thin pdf-parse wrapper. Lazy import keeps pdf-parse out of the module-load path (avoids library debug-mode side effects). Size cap (50MB default), encryption detection, structured error classes (PdfEncryptedError, PdfTooLargeError, PdfParseError). Only Cat 11 multimodal will import this; production bundle never sees pdf-parse. **eval/runner/tool-bridge.ts** — Maps 12 read-only operations from src/core/operations.ts to Anthropic tool definitions + adds 3 dry_run write tools. Three structural invariants enforced: 1. No hidden LLM calls. `operations.query` defaults expand=true which routes through expansion.ts → Haiku. Bridge strips `expand` from the query tool's input schema AND executor hard-sets expand:false. Zero nested Haiku calls in any agent trace. 2. Mutating ops throw ForbiddenOpError. put_page, add_link, delete_page, etc. are rejected by name. Agents record intent via dry_run_put_page / dry_run_add_link / dry_run_add_timeline_entry which persist to the flight-recorder without mutating the engine. This is how Cat 8's back_link_compliance + citation_format metrics measure anything with a read-only tool surface. 3. Poison tagged by the bridge, not the judge. Every tool result is scanned for slugs matching gold/poison.json fixtures. Matched fixture_ids flow into tool_call_summary.saw_poison_items for the structured-evidence judge contract. Judge never reads raw tool output — Section-3 defense against paraphrased prompt injections (poison payloads never reach the judge model at all). 32K-token cap (~128K chars) with "…[truncated]" suffix. **eval/runner/recorder.ts** — Per-run flight-recorder bundle emitter. Full 6-artifact bundle (transcript.md, brain-export.json, entity-graph.json, citations.json, scorecard.json, judge-notes.md) when the adapter provides an AdapterExport; 3-artifact fallback (transcript + scorecard + judge-notes) otherwise. Atomic writes via tmp+rename. Collision-safe: duplicate directory names get incremental -2, -3 suffix. `safeStringify` handles circular references without throwing and JSON-serializes Float32Array embeddings. **package.json:** adds pdf-parse@2.4.5 as a devDependency. Scoped to eval/ use only; production gbrain binary unaffected. **Tests:** 63 new — 30 tool-bridge, 21 recorder, 12 pdf-loader. All pass. Fake engine uses a Proxy with `__default__` fallback so poison-matching tests don't have to mock the exact engine method name that each operation calls (some route via searchKeyword, others via getPage — proxy handles both uniformly). Total eval suite now: 132 pass, 0 fail, 923 expect() calls. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat(eval): Day 5 — agent adapter + judge with structured evidence contract Two modules that together wire Cat 8 / Cat 9 / Cat 5 end-to-end scoring. **eval/runner/judge.ts** — Haiku 4.5 via tool-use `score_answer`. Input is the structured JudgeEvidence contract (fix #16 from the plan's codex review): probe + final_answer_text + evidence_refs + tool_call_summary + ground_truth_pages + rubric. Raw tool output NEVER reaches the judge — that's the Section-3 defense against paraphrased prompt-injection payloads in gold/poison.json. Retry policy: one retry on malformed tool_use response. If the second attempt is still malformed, score the probe as `judge_failed` (all scores 0, verdict=fail) so the run still completes. Aggregation: weighted mean across rubric criteria. Canonical thresholds (pass ≥3.5, partial 2.5-3.5, fail <2.5) — judge can propose a verdict but the computed verdict from the weighted mean is what the scorecard records. This prevents the model from inflating or deflating its own verdict. Score values are clamped to 0-5 on parse even if the model returns out of range. `assertNoRawToolOutput(evidence)` is a regression guard that returns the list of forbidden fields (tool_result, raw_transcript, etc.) if any leak into the evidence contract. **eval/runner/adapters/claude-sonnet-with-tools.ts** — The agent adapter. Implements `Adapter` interface minimally: `init()` spins up PGLite and seeds it, `query()` throws because the adapter is Cat 8/9-only and emits a final-answer text, not a RankedDoc[]. Retrieval scorecard stays at 4 adapters. `runAgentLoop(probeId, text, state, config)` drives the multi-turn loop: Sonnet → tool_use → tool-bridge.executeTool → tool_result → back to Sonnet. Turn cap 10. max_tokens 1024. System prompt (brain-first iron law, citation format, amara context) is cached via cache_control. Exponential backoff on rate-limit errors (1s, 2s, 4s). Emits a `Transcript` per eval/schemas/transcript.schema.json — consumed directly by recorder.ts for the flight-recorder bundle. `brain_first_ordering` classifies Cat 8's flagship metric: did the agent call search/get_page BEFORE producing the final answer? The `no_brain_calls` case (agent answers from general knowledge without ever hitting the brain) is the compliance failure to surface. ForbiddenOpError + UnknownToolError from the bridge are caught in the agent loop and surfaced as tool_result with is_error=true — keeps the loop going and preserves full audit trail for the judge. **Tests (35 new):** judge (23) — happy path, retry, fallback, evidence contract sanitization, rendered prompt does not contain raw tool_result text, verdict thresholds, score clamping, weighted mean with mixed weights, parseToolUse rejects malformed input. agent-adapter (12) — Adapter.query() throws, init() seeds PGLite, end-to-end tool loop with stubbed Sonnet, turn cap exhaustion, mutating-op rejection surfaces as tool_result error, extractSlugs regex. All 12 agent tests take ~23s because PGLite runs 13 schema migrations per test; the alternative of shared-engine-across-tests was rejected so each test is isolated. Total eval suite now: 167 pass, 0 fail. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat(eval): Day 6 — adversarial-injections + Cat 6 prose-scale + Cat 11 multi-modal Three modules that together cover BrainBench v1 Cat 6 (prose-scale extraction fidelity) and Cat 11 (multi-modal ingest fidelity). **eval/runner/adversarial-injections.ts** — 6 deterministic content transforms shared by Cat 10 (adversarial.ts, 22 hand-crafted cases) and Cat 6 (prose-scale variants). Each injection produces a modified content string + a structured GoldDelta describing what the extractor MUST and MUST NOT produce. Kinds: - code_fence_leak — fake [X](people/fake) inside ``` fence, must NOT extract - inline_code_slug — `people/fake` in backticks, must NOT extract - substring_collision — "SamAI" near real `people/sam`, exactly one link - ambiguous_role — "works with" vs "works at", downgrade type to mentions - prose_only_mention — strip markdown link syntax, bare name → mentions only - multi_entity_sentence — pack 4+ entities into one clause, extract all Mulberry32 PRNG keeps variant generation deterministic under fixed seed. Codex flagged the original plan's wording ("extract injection engine from adversarial.ts") as overstated — adversarial.ts is a static case list, not a reusable engine. This module is NEW code. **eval/runner/cat6-prose-scale.ts** — Runner. Loads world-v1, applies all 6 injection kinds to sampled base pages (default 50 variants per kind × 6 kinds = 300 variants), runs extractPageLinks on each, compares to gold delta. Emits per-kind + overall metrics (precision, recall, F1, code_fence_leak_rate, substring_fp_rate, pages_with_links_coverage, mean_links_per_page). **v1 verdict is always "baseline_only"** — no gating threshold per codex fix #9 (current extractor residuals make >0.80 unreachable; v1 records a baseline, regression guard triggers on drop below it). **eval/runner/cat11-multimodal.ts** — PDF + HTML + audio runners. Fixtures load from eval/data/multimodal/<modality>/fixtures.json manifests; each modality skips gracefully when manifest missing or (audio) when neither GROQ_API_KEY nor OPENAI_API_KEY is set. Metrics: - PDF: char-level similarity via Levenshtein + optional entity_recall - HTML: word-recall over normalized tokens (multiset semantics) - Audio: WER (word error rate) via Levenshtein on word sequences Fixtures are NOT committed; a future eval:fetch-multimodal script will download them hash-verified from public sources (arXiv CC-licensed papers, Wikipedia CC-BY-SA, Common Voice CC0). Injectable audio transcriber (`opts.transcribe`) means tests don't need GROQ/OpenAI keys — stubbed transcriptions exercise the WER math path directly. **Tests (60 new):** adversarial-injections (19) — per-kind assertions + dispatcher coverage + slug regex conformance; cat6 (12) — variant determinism, scoreVariant shape, aggregate per-kind + overall metrics, corpus resolver slug rules; cat11 (29) — charSimilarity / wordRecall / wer math, htmlToText strips scripts + decodes entities, HTML modality with real fixtures, audio modality gracefully skips without key + uses stub transcriber correctly. All 60 tests pass in 48ms + 41ms. Total eval suite now: 227 pass, 0 fail. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat(eval): Day 7 — Cat 5 provenance runner + structured classify_claim judge **eval/runner/cat5-provenance.ts** — BrainBench Cat 5 scoring. Samples claims from gbrain brain-export and classifies each against its source material via a dedicated Haiku judge (classify_claim tool with a three-label enum: supported | unsupported | over-generalized). Separate from judge.ts by design: Cat 5 is a single three-way classification per claim, not a weighted rubric. Rather than overload judge.ts with a mode switch, Cat 5 has its own tool definition (CLASSIFY_CLAIM_TOOL) and prompt. The retry-once pattern, $20 cost gate semantics, and structured parsing are mirrored from judge.ts so failures look the same across Cats. Metric: `citation_accuracy` = fraction where predicted label equals gold expected_label. Threshold (informational): >0.90 per design-doc METRICS.md. v1 ships with `enableThreshold: false` so the verdict is always baseline_only — we don't have hand-authored gold claims yet, and codex flagged that threshold gating should wait until the amara-life-v1 corpus + gold file authoring lands in Day 3b. runCat5 uses a bounded-concurrency worker pool (default 4) to respect Haiku rate limits across 100+ claim batches. Evidence pages are looked up by slug from a caller-provided pagesBySlug map — missing pages don't crash, they just pass an empty source list to the judge (correct behavior for genuinely unsupported claims). **Tests (23):** classifyClaim happy/retry/fallback paths with stubbed Haiku, aggregate accuracy math, threshold gating (pass/fail vs baseline_only), runCat5 concurrency + missing-page handling, renderClaimPrompt embeds claim + sources correctly, parseClassification rejects invalid enum values + plain-text responses. Total eval suite now: 250 pass, 0 fail. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat(eval): Day 8 — Cat 8 skill compliance + Cat 9 end-to-end workflows **eval/runner/cat8-skill-compliance.ts** — Deterministic, judge-free Cat 8 scoring. Replays inbound signals through the agent adapter (Day 5) and extracts four iron-law metrics directly from the tool-bridge state: - brain_first_compliance: agent called search/get_page BEFORE producing its final answer. Non-compliance = hallucinating from general knowledge. - back_link_compliance: every dry_run_put_page intent has at least one markdown [Name](slug) back-link in its compiled_truth. - citation_format: timeline entries use canonical `- **YYYY-MM-DD** | Source — Summary`; long final answers cite at least one slug. - tier_escalation: simple probes use light tooling (≥1 brain call); complex probes require ≥2 brain calls or a dry_run write when expects_dry_run_write is set. No judge call required — everything is computable from `tool_bridge_state.made_dry_run_writes` + `count_by_tool` + final_answer regex. Fast, deterministic, reproducible. Bounded concurrency (p-limit style) worker pool at default 4 to keep Sonnet rate limits comfortable across 100-probe batches. **eval/runner/cat9-workflows.ts** — Rubric-graded Cat 9. 5 canonical workflows (meeting_ingestion, email_to_brain, daily_task_prep, briefing, sync) × ~10 scenarios each. Each scenario runs through the agent adapter, then judge.ts scores the answer against a per-scenario rubric. `buildEvidence(scenario, agentResult, pagesBySlug)` composes the JudgeEvidence contract: resolves ground_truth_slugs to full GroundTruthPage[] from a slug-map, pulls tool_call_summary directly from tool_bridge_state (no raw tool_result content — Section-3 defense), attaches rubric from the scenario. Per-workflow rollup: each workflow gets its own pass_rate so the verdict can fail one workflow without failing the whole Cat. Overall verdict requires every populated workflow's pass_rate ≥ threshold (default 0.80) when enableThreshold=true. Both Cats default to verdict=baseline_only in v1 per codex fix #9: real thresholds return after 10-probe Haiku-vs-hand-score calibration (κ > 0.7) runs against the Day 3b amara-life-v1 corpus. **Tests (23):** Cat 8 per-metric scorer unit tests covering every branch (brain_first ordering, back-link compliance on mixed writes, long vs short answer citation requirement, tier escalation for simple/complex/ writey probes, finalAnswerCiteCount dedups across syntaxes). Cat 9 buildEvidence contract shape — evidence_refs flow from agent, missing slugs skip gracefully, no raw_transcript/tool_result leakage to judge. Cat 9 runCat9 integration with stubbed agent + mixed-verdict judge produces fractional pass rates correctly. Total eval suite now: 273 pass, 0 fail. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat(eval): Day 9 — sealed qrels via PublicPage + PublicQuery at adapter boundary Codex fixes #1, #2, #3 from the plan's outside-voice review. Enforcement shifts from SOFT-VIA-TYPE-COMMENT to SOFT-VIA-SANITIZED-OBJECT. Hard enforcement via process isolation waits for BrainBench v2 Docker sandbox. **eval/runner/types.ts** additions: - `PublicPage = Pick<Page, 'slug' | 'type' | 'title' | 'compiled_truth' | 'timeline'>` — the exact 5 fields adapters should see. No _facts. No frontmatter (a known hiding spot for accidental gold leaks). - `sanitizePage(p: Page): PublicPage` — returns a NEW object with the 5 fields only. Cannot be bypassed by `(page as any)._facts` because the field does not exist on the sanitized object. - `PublicQuery = Omit<Query, 'gold'>` — strips the gold field. - `sanitizeQuery(q: Query): PublicQuery` — enumerates public fields explicitly (not spread+delete) so no prototype weirdness leaves gold reachable. **eval/runner/multi-adapter.ts** — scoreOneRun now calls sanitizePage / sanitizeQuery before passing to adapter.init / adapter.query. The scorer retains the full Query shape (including gold.relevant) for precision / recall computation. Adapter signatures unchanged — the sealing is at the OBJECT level, not the type level. This keeps existing adapters (ripgrep-bm25, vector-only, hybrid-nograph, gbrain-after) binary-compatible. Verified: no existing adapter reads q.gold or page._facts, so the change is safe without further adapter updates. **test/eval/sealed-qrels.test.ts** (17 tests): - sanitizePage strips _facts + frontmatter + arbitrary hidden keys - Output has exactly the 5 public keys (deep introspection) - Proxy tripwire simulates a malicious adapter: any access to _facts or gold throws `sealed-qrels violation` - sanitizeQuery retains optional fields (as_of_date, tags, author, acceptable_variants, known_failure_modes) but omits undefined ones - Honest documentation of the seal's limits: filesystem bypass and Proxy attacks would still work in v1; Docker isolation (v2) is the real enforcement Every existing eval test still passes (273 before + 17 sealed-qrels = 290). Total eval suite now: 290 pass, 0 fail. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat(eval): Day 10 — all.ts rewrite + llm-budget + BrainBench N tiers Final wiring of BrainBench v1 Complete. all.ts now orchestrates the full Cat catalog (1-12) via a mix of subprocess dispatch (Cats 1, 2, 3, 4, 6, 7, 10, 11, 12 — standalone runners with CLI entry points) and programmatic invocation (Cats 5, 8, 9 — require runtime inputs that can't come via CLI flags). Subprocess Cats run concurrently under a p-limit(2) bound to cap peak memory around ~800MB (two PGLite instances at ~400MB each). Cats 5/8/9 show as "programmatic" in the report with a one-line reference to their `runCatN({...})` harness API. They're deliberately skipped from the master runner because their inputs (claim catalog, probe catalog, scenario catalog, pre-seeded agent state, evidence pagesBySlug) are task-specific and assembled at the caller. **eval/runner/all.ts** — rewritten: - CATEGORIES is a tagged union of SubprocessCategory | ProgrammaticCategory - runCatSubprocess spawns Bun with pipe'd stdout/stderr, 10-min timeout per Cat (124 exit + SIGTERM on timeout; no hung subprocesses) - runConcurrently is a bounded worker pool preserving input order - buildReport emits the full markdown with per-Cat elapsed times, migration-noise filter, and a separate programmatic-only section - Honors BRAINBENCH_N (1/5/10 for smoke/iteration/published), BRAINBENCH_CONCURRENCY (default 2), BRAINBENCH_LLM_CONCURRENCY (default 4, consumed by llm-budget) **eval/runner/llm-budget.ts** — shared LLM rate-limit semaphore. A full N=10 published scorecard makes ~900 Anthropic calls (150 Cat 8/9 probes × N=10 + 100 Cat 5 claims × N=10). Without coordination, concurrent adapters trigger 429s on per-minute limits. - LlmBudget class: acquireSlot/releaseSlot + withLlmSlot(fn) wrapper that releases on success AND throw (try/finally) - getDefaultLlmBudget() singleton reads BRAINBENCH_LLM_CONCURRENCY, falls back to 4 on missing/garbage values - capacity enforced ≥1 (rejects 0/negative) - Double-release is a no-op (guards against upstream double-call bugs) - Active + waiting counts exposed for observability / tests **package.json** scripts: - eval:brainbench — default N=5 iteration - eval:brainbench:smoke — N=1 for fast iteration - eval:brainbench:published — N=10 for committed baselines - eval:cat6 / eval:cat11 — individual new subprocess Cats **Tests (24):** CATEGORIES catalog enforces the exact Cat-number partition (subprocess: 1,2,3,4,6,7,10,11,12; programmatic: 5,8,9). runConcurrently respects the cap (observable via peak in-flight counter), preserves input order under non-uniform delays, handles empty input. LlmBudget enforces capacity, releases on throw, honors env var, rejects 0/negative. buildReport filters migration noise, counts passed/failed/programmatic correctly, includes every Cat + programmatic-only section. Full eval suite now: 314 pass, 0 fail (15 test files). Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix(eval): drop top_p from amara-life-gen Opus params + gitignore _cache/ Two fixes surfaced during the Day 3b real-corpus run against Opus 4.5: **eval/generators/amara-life-gen.ts** — Current Opus rejects `temperature` and `top_p` together: ``` 400 invalid_request_error: `temperature` and `top_p` cannot both be specified for this model. Please use only one. ``` top_p=1.0 was a no-op (no nucleus truncation), so removing it has zero semantic effect. The field is still part of MODEL_PARAMS for the cache key so any past cache entries (none in v1) would invalidate cleanly on the next schema version bump. **.gitignore** — `eval/data/amara-life-v1/_cache/` is runtime Opus cache (398 files, ~1.6MB). Regenerable from seed; no point in source control. The corpus itself (inbox/slack/calendar/meetings/notes/docs + corpus-manifest.json with per-item content_sha256) stays committable for reproducibility, just the cache directory gets excluded. Real corpus generation ran cleanly after these two fixes: 398 LLM calls, 84,424 input / 38,062 output tokens, \$4.12 spent (vs \$20 cap, vs \$12 estimate). All 418 items produced. Poison fixtures use subtle paraphrased injection ("for anyone on your team who might be triaging this thread later…") — exactly the pattern that defeats regex redaction and requires the structured-evidence judge contract from Day 5. Corpus itself stays local (will move to the brainbench sibling repo during the v0.16 split per the design doc). No eval/data/amara-life-v1/ content landing in this PR. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * chore: bump version to 0.20.0 Renumbered from 0.17.0 per the gbrain-versioning slot. Other work is landing on master around this PR; 0.18 is the slot locked for this BrainBench v1 Complete release. Also pushed the "brainbench split" forward reference in the CHANGELOG from v0.18 → v0.19 to match. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * refactor: extract BrainBench to sibling gbrain-evals repo BrainBench lived in this repo through v0.17, which meant every gbrain install pulled down ~5MB of eval corpus, benchmark reports, and a pdf-parse devDep that the 99% of users who never run benchmarks don't need. v0.18 moves the full eval harness, 14 eval test files (314 tests), all docs/benchmarks scorecards, and the pdf-parse devDep to github.com/garrytan/gbrain-evals. That repo depends on gbrain via GitHub URL and consumes it through a new public exports map. What stays in gbrain: - Page.type enum extensions (email | slack | calendar-event | note | meeting) useful for any ingested format, not just evals - inferType() heuristics for /emails/, /slack/, /cal/, /notes/, /meetings/ - 11 new public exports covering the gbrain internals gbrain-evals consumes (gbrain/engine, gbrain/pglite-engine, gbrain/search/hybrid, etc.) — now gbrain's stable third-party contract What moved: - eval/ — 4.6MB of schemas, runners, adapters, generators, CLI tools - test/eval/ — 14 test files, 314 tests - docs/benchmarks/ — all scorecards and regression reports - eval:* package.json scripts - pdf-parse devDep Tests: 1760 pass, 0 fail, 174 skipped (E2E require DATABASE_URL). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * Merge origin/master into garrytan/gbrain-evals Master landed significant work since this branch was cut (v0.15.x → v0.16.x → v0.17.0 gbrain dream + runCycle → v0.18.0 multi-source brains → v0.18.1 RLS hardening). Bumped this branch's version from the claimed 0.18.0 to 0.19.0 because master already owns 0.18.x. Conflicts resolved: - VERSION: 0.19.0 (was 0.18.0 on HEAD vs 0.18.1 on master) - package.json: 0.19.0, kept all 11 eval-facing exports, merged master's typescript devDep + postinstall script + test script (typecheck added) - src/core/types.ts: union of both PageType additions. Master had added `meeting | note`; this branch added `email | slack | calendar-event` for inbox/chat/calendar ingest. Final enum carries all five. - CHANGELOG.md: renumbered the BrainBench-extraction entry to 0.19.0 and placed it above master's 0.18.1 RLS entry. Tweaked copy ("In v0.17 it lived inside this repo" → "Previously it lived inside this repo") to stop implying a specific version that never shipped. - CLAUDE.md: adjusted "BrainBench in a sibling repo" heading from (v0.18+) → (v0.19+). - docs/benchmarks/2026-04-18-minions-vs-openclaw-production.md: resolved modify-vs-delete conflict in favor of delete (the extraction). - scripts/llms-config.ts: dropped the docs/benchmarks/ entry (directory no longer exists here; lives in gbrain-evals). - llms.txt / llms-full.txt: regenerated after the config change. - bun.lock: accepted master's (master already dropped pdf-parse as a drive-by; aligned with our removal). Tests: 2094 pass, 236 skip, 18 fail. Spot-checked failures — build-llms, dream, orphans tests all pass in isolation. Failures reproduce only under full-suite parallel load and are pre-existing master flakiness (matches the graph-quality flake noted in the earlier summary). Not merge-introduced. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * chore: bump to v0.20.0 Master is now at v0.18.2 (migration hardening + RLS + multi-source brains). BrainBench extraction ships as v0.20.0 to leave v0.19 free for any in-flight work on other branches. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * ci: remove eval-tests workflow (moved to gbrain-evals) The Eval tests workflow ran `bun run eval:query:validate`, `test:eval`, and `eval:world:render` — all three scripts moved to the gbrain-evals repo when BrainBench was extracted in v0.20.0. The workflow has been failing on master since the split because the scripts no longer exist here. Eval CI now runs from gbrain-evals's own workflows. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(tests): bump PGLite hook timeouts to 60s for parallel-load stability Six test files spin up PGLite + 20 migrations + git repos in beforeEach/ beforeAll hooks. Under 136-way parallel test file execution, bun's default 5s hook timeout wasn't enough, producing 18 flaky failures that only reproduced under full-suite parallel load (all 6 files passed in isolation). Root cause: PGLite.create() + initSchema() takes ~3-5s under idle load, but under 136 concurrent WASM instantiations the OS thrashes and hooks stall well past 5s. The bunfig.toml `timeout = 60_000` applies to TESTS, not HOOKS — bun requires per-hook timeouts as the third beforeEach/beforeAll argument. Files touched (hook timeouts added, no test logic changed): - test/dream.test.ts — 5 describe blocks × before/afterEach - test/orphans.test.ts — 1 beforeEach + afterEach - test/core/cycle.test.ts — shared beforeAll + afterAll - test/brain-allowlist.test.ts — beforeAll + afterAll - test/extract-db.test.ts — beforeAll + afterAll - test/multi-source-integration.test.ts — beforeAll + afterAll Results: 2317 pass / 0 fail (was 2253 pass / 18 fail). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * test: coverage for inferType() BrainBench corpus dirs Closes the 1 gap surfaced by Step 7 coverage audit. 9 table-driven assertions covering the new Page.type branches: emails/*.md, email/*.md -> 'email' slack/*.md -> 'slack' cal/*.md, calendar/*.md -> 'calendar-event' notes/*.md, note/*.md -> 'note' meetings/*.md, meeting/*.md -> 'meeting' The fixtures use realistic paths from the amara-life-v1 corpus in the sibling gbrain-evals repo (em-0001, sl-0037, evt-0042, mtg-0003) so the test doubles as a contract check between the two repos. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * docs(TODOS): mark BrainBench Cats 5/6/8/9/11 + v0.10.5 inferLinkType as completed All five BrainBench categories shipped in v0.20.0 (to the gbrain-evals sibling repo). v0.10.5 inferLinkType regex expansion shipped in-tree. Remaining P1 BrainBench work: Cat 1+2 at full scale (2-3K pages) — currently 240 pages in world-v1 corpus. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * docs: sync CLAUDE.md + polish CHANGELOG voice for v0.20.0 CLAUDE.md: add v0.19 commands to key-files list (skillify, skillpack, routing-eval, filing-audit, skill-manifest, resolver-filenames); add 8 new test files + openclaw-reference-compat E2E to test index; repoint the release-summary template's benchmark source from `docs/benchmarks/[latest].md` to `gbrain-evals/docs/benchmarks/` since those files now live in the sibling repo. CHANGELOG voice polish for v0.20.0: replace em dashes with periods, parens, or ellipses per project style guide. No content changes. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * docs: regenerate llms-full.txt after CLAUDE.md + CHANGELOG edits (fixes CI) The v0.20.0 doc-sync commit (9e567bb) added 7 new v0.19 modules to the CLAUDE.md Key Files index and polished CHANGELOG voice. Both are includeInFull: true inputs to llms-full.txt but the generator wasn't re-run, so the drift-detection guard (test/build-llms.test.ts) failed CI. One-line fix: regenerate. No content changes beyond what the two source docs already carry. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

#696) * feat: recency boost for search (v0.27.0) — temporal intent auto-detection, date filters, configurable decay New search pipeline stage: keyword + vector → RRF → cosine re-score → backlink boost → recency boost → dedup - applyRecencyBoost: hyperbolic decay, two strengths (moderate 30-day halflife, aggressive 7-day halflife) - Auto-enabled when intent.ts detects temporal/event queries (detail='high') - Manual override via SearchOpts.recencyBoost (0/1/2) - Date filtering: afterDate/beforeDate on all three search paths (keyword, keywordChunks, vector) - getPageTimestamps on both Postgres and PGLite engines - 15 tests passing (boost math + intent classification) * v0.29.1 schema: pages.{effective_date, effective_date_source, import_filename, salience_touched_at} + expression index Migration v38 adds 4 nullable columns to pages and an expression index on COALESCE(effective_date, updated_at) to support the new since/until date filters. All additive — no behavior change in the default search path; only consulted when callers opt into the new salience='on' / recency='on' axes or pass since/until. effective_date — content date (event_date / date / published / filename-date / fallback). Read by recency boost and date-filter paths only. Auto-link doesn't touch it (immune to updated_at churn). effective_date_source — sentinel for the doctor's effective_date_health check ('event_date' | 'date' | 'published' | 'filename' | 'fallback'). import_filename — basename without extension, captured at import. Used for filename-date precedence on daily/, meetings/. Older rows leave it NULL. salience_touched_at — bumped by recompute_emotional_weight when emotional_weight changes. Salience window uses GREATEST(updated_at, salience_touched_at) so newly-salient old pages enter the recent salience query. Index strategy: a partial index on effective_date alone wouldn't help the COALESCE expression in since/until filters (planner can't use it for the negative side). The expression index ((COALESCE(effective_date, updated_at))) is what actually accelerates the filter. Postgres uses CONCURRENTLY + v14-style pg_index.indisvalid pre-drop guard for prior failed CONCURRENTLY runs; PGLite uses plain CREATE INDEX. Mirror of v34's pattern. src/schema.sql + src/core/pglite-schema.ts updated for fresh installs; src/core/schema-embedded.ts regenerated via bun run build:schema. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: computeEffectiveDate helper + putPage integration Pure helper computing a page's effective_date from frontmatter precedence: 1. event_date (meeting/event pages) 2. date (dated essays) 3. published (writing/) 4. filename-date (leading YYYY-MM-DD in basename) 5. updated_at (fallback) 6. created_at (last resort) Per-prefix override: for daily/ and meetings/ slugs, filename-date jumps to position 1 — the filename is the user's primary signal there. Returns {date, source}. The source label powers the doctor's effective_date_health check to detect "fell back to updated_at" rows that look populated but are functionally a NULL. Range validation: parsed value must be in [1990-01-01, NOW + 1 year]. Out-of-range values drop to the next chain element. Wired into importFromContent + importFromFile. The put_page MCP op derives filename from slug-tail when no caller-supplied filename is available. putPage SQL on both engines extended to write the new columns. ON CONFLICT uses COALESCE(EXCLUDED.x, pages.x) so callers that don't know about the new columns (auto-link, code reindex) preserve existing values rather than blanking them. SELECT projection extended to return them; rowToPage threads them through. 21 unit tests covering: precedence chain default order, per-prefix override, parse failure fall-through, range validation [1990, NOW+1y], parseDateLoose shape variants. All pass; typecheck clean. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: backfill orchestrator + library function for existing pages src/core/backfill-effective-date.ts is the shared library function. Walks pages in keyset-paginated batches (id > last_id ORDER BY id LIMIT 1000), runs computeEffectiveDate per row, UPDATEs effective_date + effective_date_source. Resumable via the `backfill.effective_date.last_id` checkpoint key in the config table — a killed process can re-run and pick up without re-doing rows. Idempotent: a full re-walk produces the same writes. Postgres-only: SET LOCAL statement_timeout = '600s' per batch. Doesn't refuse the migration on low session settings (codex pass-2 #16). src/commands/migrations/v0_29_1.ts is the orchestrator (4 phases mirroring v0_12_2). Phase A schema (gbrain init --migrate-only), Phase B backfill (via the library function), Phase C verify (count NULL effective_date), Phase D record (handled by runner). The library function is reusable from the gbrain reindex-frontmatter CLI command in the next commit. import_filename stays NULL for backfilled rows — pre-v0.29.1 imports didn't capture it. computeEffectiveDate uses the slug-tail when filename is NULL; daily/2024-03-15 backfilled gets effective_date from the slug. Registered in src/commands/migrations/index.ts. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: gbrain reindex-frontmatter CLI command Recovery / explicit-rebuild path for pages.effective_date. Used when: - User edited frontmatter dates after import - Post-upgrade backfill orchestrator finished but the user wants to re-walk a subset (e.g. just meetings/) after fixing some frontmatter - Precedence rules change between releases Thin wrapper over backfillEffectiveDate from commit 3 — same code path the v0_29_1 orchestrator uses; one source of truth. Flags mirror reindex-code: --source <id> Scope to one sources row (placeholder; library library doesn't filter by source today, tracked v0.30+) --slug-prefix P Scope to slugs starting with P (e.g. 'meetings/') --dry-run Print what WOULD change, no DB writes --yes Skip confirmation prompt (required for non-TTY non-JSON) --json Machine-readable result envelope --force Re-apply even when computed value matches existing Wired into src/cli.ts. CLI handles its own engine lifecycle (creates + disconnects). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: recency-decay map + buildRecencyComponentSql (pure, unused) src/core/search/recency-decay.ts mirrors source-boost.ts in shape but drives RECENCY ONLY (per D9 codex resolution). Salience is a separate orthogonal axis; this map does not feed it. DEFAULT_RECENCY_DECAY: 10 generic prefixes (no fork-specific names). - concepts/ evergreen (halflifeDays=0) - originals/ 180d × 0.5 (long-tail decay; new essays nudged) - writing/ 365d × 0.4 - daily/ 14d × 1.5 (aggressive — freshness IS the signal) - meetings/ 60d × 1.0 - chat/ 7d × 1.0 - media/x/ 7d × 1.5 - media/articles/ 90d × 0.5 - people/companies/ 365d × 0.3 - deals/ 180d × 0.5 DEFAULT_FALLBACK: 90d × 0.5 for unmatched slugs. Override priority: defaults < gbrain.yml recency: < env (GBRAIN_RECENCY_DECAY) < per-call SearchOpts.recency_decay. parseRecencyDecayEnv format: comma-separated prefix:halflifeDays:coefficient triples. Refuses LOUD on parse error (RecencyDecayParseError) — codex pass-2 #M3 finding. No silent fallback like source-boost's parser. parseRecencyDecayYaml takes already-parsed YAML; throws on bad shape. buildRecencyComponentSql in sql-ranking.ts emits a CASE expression with longest-prefix-first ordering, evergreen short-circuit (literal 0 when halflifeDays=0 or coefficient=0), and EXTRACT(EPOCH ...) for non-zero branches. Output: ((CASE WHEN p.slug LIKE 'daily/%' THEN 1.5 * 14.0 / (14.0 + EXTRACT(EPOCH FROM (NOW() - <dateExpr>))/86400.0) ... END)) Typed NowExpr enum prevents SQL injection (codex pass-1 #5). Tests pass { kind: 'fixed', isoUtc } for deterministic output; production NOW(). The 'fixed' branch escapes single quotes via escapeSqlLiteral. 25 unit tests covering: env parser shape, env error cases, yaml parser shape, merge precedence (defaults < yaml < env < caller), CASE longest- prefix-first ordering, evergreen short-circuit, NowExpr fixed/now, single-quote injection defense, empty decayMap fallback path, default map composition (no fork names, concepts/ evergreen, daily/ aggressive). Pure module. Zero consumers in this commit; commit 6 wires it into getRecentSalience, commit 10 wires it into the post-fusion stage. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: refactor getRecentSalience to consume buildRecencyComponentSql Both engines (Postgres + PGLite) now build the salience formula's third term via buildRecencyComponentSql instead of inlining 1.0 / (1 + days_old). Parameters: empty decayMap + fallback { halflifeDays: 1, coefficient: 1.0 }. Math expands to 1 * 1.0 / (1.0 + days_old) = 1 / (1 + days_old) — same numeric output as v0.29.0. This is a no-behavior-change refactor preparing for commit 7's recency_bias param. recency_bias='flat' (default) reproduces v0.29.0 exactly; 'on' swaps in DEFAULT_RECENCY_DECAY for per-prefix decay. Single source of truth for the recency math: same builder feeds the salience query AND (in commit 10) the post-fusion applyRecencyBoost stage. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: get_recent_salience gains recency_bias param (default 'flat') SalienceOpts.recency_bias: 'flat' | 'on' added; default 'flat' preserves v0.29.0 ranking verbatim. Pass 'on' to opt into per-prefix decay map (concepts/originals/writing/ evergreen; daily/, media/x/, chat/ aggressive decay). When recency_bias='on', the salience query reads COALESCE(p.effective_date, p.updated_at) instead of bare p.updated_at, so the recency component is immune to auto-link updated_at churn — old concepts/ pages just-touched by auto-link don't suddenly look fresh. Both engines (Postgres + PGLite) wire the param through. resolveRecencyDecayMap() honors gbrain.yml + GBRAIN_RECENCY_DECAY env at runtime. MCP op surface: get_recent_salience gains the param with a load-bearing description teaching the agent when to use 'on' vs 'flat' (current state → on; mattering across all time → flat). No silent v0.29.0 behavior change — opt-in only (per D11 codex resolution). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: recompute_emotional_weight writes salience_touched_at; window picks up newly-salient pages setEmotionalWeightBatch on both engines now bumps salience_touched_at to NOW() ONLY when the new emotional_weight differs from the existing one (IS DISTINCT FROM, NULL-safe). No-op writes (same weight) leave the column alone — preserves "actual change" semantics. getRecentSalience window changes from WHERE p.updated_at >= boundary to WHERE GREATEST(p.updated_at, COALESCE(p.salience_touched_at, p.updated_at)) >= boundary Closes codex pass-1 finding #4: pages whose emotional_weight just changed in the dream cycle (because tags or takes shifted) but whose updated_at is older than the salience window now correctly enter the recent-salience results. Without this, "Garry just added a take to a 6-month-old page" stayed invisible to get_recent_salience until the next content edit. COALESCE(salience_touched_at, p.updated_at) handles pre-v0.29.1 rows where salience_touched_at is NULL — they fall back to p.updated_at and behave identically to v0.29.0. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: merge intent.ts → query-intent.ts; emit 3 suggestions per query D1 + D4 + D6 + D8: single regex-pass classifier returning {intent, suggestedDetail, suggestedSalience, suggestedRecency}. intent + suggestedDetail are v0.29.0 behavior verbatim (legacy intent.ts deleted; classifyQueryIntent + autoDetectDetail compat shims preserved). NEW for v0.29.1 — two orthogonal recency-axis suggestions: suggestedSalience: 'off' | 'on' | 'strong' suggestedRecency: 'off' | 'on' | 'strong' Resolution rules (per D6 narrow temporal-bound exception): - CANONICAL patterns (who is X / what is Y / code / graph) → both off - UNLESS an EXPLICIT_TEMPORAL_BOUND also matches (today / right now / this week / since X / last N days), in which case temporal-bound wins - STRONG_RECENCY (today / right now / this morning / just now) → strong - RECENCY_ON (latest / recent / this week / meeting prep / catch up / remind me / status update) → on - SALIENCE_ON (catch up / remind me / status update / prep me / what's going on / what matters) → on - default → off for both axes (v0.29.1 prime-directive: pure opt-in) Salience and recency are TRULY orthogonal (per D9). A query like "latest news on AI" → recency='on' but salience='off' (the user wants fresh, not emotionally-weighted). "What's going on with widget-co" → both on. "Who is X right now" → both 'strong'/'on' (temporal bound beats canonical 'who is'). intent.ts deleted; test/intent.test.ts renamed → test/query-intent-legacy.test.ts (unchanged behavior coverage). New test/query-intent.test.ts adds 21 cases covering all three axes' interactions: canonical wins on bare 'who is', temporal bound overrides, "catch me up" matches with up to 15 chars between, "today" → strong, intent vs recency independence. Updated callers: - src/core/search/hybrid.ts (autoDetectDetail import) - test/recency-boost.test.ts (classifyQueryIntent import) - test/benchmark-search-quality.ts (autoDetectDetail import) Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: applySalienceBoost + applyRecencyBoost + runPostFusionStages wrapper D9 + codex pass-1 #2 + #3 + pass-2 #4: salience and recency are TRULY ORTHOGONAL post-fusion stages, both running from ALL THREE hybridSearch return paths (keyword-only, embed-failure-fallback, full-hybrid). NEW src/core/search/hybrid.ts exports: - applySalienceBoost(results, scores, strength) score *= 1 + k * log(1 + score) where k = 0.15 (on) or 0.30 (strong) No time component. Pure mattering signal. - applyRecencyBoost(results, dates, strength, decayMap, fallback, nowMs?) Per-prefix decay factor: 1 + strengthMul * coefficient * halflife / (halflife + days_old) strengthMul: 1.0 (on) or 1.5 (strong) Evergreen prefixes (halflifeDays=0) skipped (factor 1.0). Pure recency signal. Independent of mattering. - runPostFusionStages(engine, results, opts) Wraps backlink + salience + recency. Called from EACH return path so keyless installs and embed failures get the same boost surface as the full hybrid path. NEW engine methods (composite-keyed for multi-source isolation): - getEffectiveDates(refs: Array<{slug, source_id}>): Map<key, Date> Returns COALESCE(effective_date, updated_at, created_at). Key format: `${source_id}::${slug}`. Mirror of getBacklinkCounts shape. - getSalienceScores(refs: Array<{slug, source_id}>): Map<key, number> Returns emotional_weight × 5 + ln(1 + take_count). Composite key. Deprecated (kept for back-compat through v0.29.x): - SearchOpts.afterDate / beforeDate (alias for since/until) - SearchOpts.recencyBoost: 0|1|2 (alias for recency: 'off'|'on'|'strong') - getPageTimestamps (use getEffectiveDates instead) NEW SearchOpts fields: - salience: 'off' | 'on' | 'strong' - recency: 'off' | 'on' | 'strong' - since: string (ISO-8601 or relative, replaces afterDate) - until: string (replaces beforeDate) Resolution: caller-explicit > legacy alias (recencyBoost) > heuristic (classifyQuery's suggestedSalience / suggestedRecency). Deleted: src/core/search/recency.ts (PR #618's, replaced) + test/recency-boost.test.ts (its scope is replaced by query-intent.test.ts + future post-fusion tests). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> Co-Authored-By: Wintermute <wintermute@garrytan.com> * v0.29.1: query op gains salience + recency + since + until params; PGLite since/until parity Combines commits 12 + 13 of the plan. Query op surface (src/core/operations.ts): - salience: 'off' | 'on' | 'strong' (with load-bearing description) - recency: 'off' | 'on' | 'strong' - since: string (ISO-8601 or relative; replaces deprecated afterDate) - until: string (replaces deprecated beforeDate) Tool descriptions teach the calling agent: - salience axis = mattering, no time component - recency axis = age decay, no mattering signal - omit either to let gbrain auto-detect from query text via classifyQuery hybrid.ts maps since/until → afterDate/beforeDate at the engine call boundary so PR #618's existing engine plumbing keeps working without rename. Codex pass-1 #10 finding closed. PGLite engine (codex pass-1 #10): since/until parity added to all three search methods (searchKeyword, searchKeywordChunks, searchVector). SQL filter against COALESCE(p.effective_date, p.updated_at, p.created_at) so date filtering matches user content-date intent (a meeting was on event_date, not when it got reimported). Filter is applied INSIDE the HNSW inner CTE in searchVector so HNSW's candidate pool already excludes out-of-range pages — preserves pagination contract. This also closes existing cross-engine drift: pre-v0.29.1 Postgres had afterDate/beforeDate from PR #618; PGLite had nothing. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: migration v39 — eval_candidates capture columns for replay reproducibility D11 codex pass-2 resolution: extend eval_candidates with 7 new nullable columns so `gbrain eval replay` can reproduce captured runs of agent-explicit salience + recency choices. Without these columns, replays of the new axis params drift. The live behavior depends on the resolved {salience, recency} values; v0.29.0's schema doesn't capture them. as_of_ts TIMESTAMPTZ — brain's logical NOW at capture (replay uses this instead of wall-clock) salience_param TEXT — what the caller passed (NULL if omitted) recency_param TEXT — same salience_resolved TEXT — final value applied recency_resolved TEXT — same salience_source TEXT — 'caller' or 'auto_heuristic' recency_source TEXT — same All nullable + additive. Pre-v0.29.1 rows stay valid. NDJSON schema_version STAYS at 1 — consumers ignore unknown fields (codex pass-1 #C2 dissolves; no cross-repo coordination needed). ADD COLUMN with no DEFAULT is metadata-only on PG 11+ and PGLite — instant on tables of any size. src/schema.sql + src/core/pglite-schema.ts mirror the additions for fresh installs; src/core/schema-embedded.ts regenerated. eval_capture.ts populates the new fields in commit 16 (docs + ship). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: doctor checks — effective_date_health + salience_health effective_date_health: sample-1000 scan detects three classes of problems (codex pass-1 #5 resolution via the effective_date_source sentinel column added in commit 1): fallback_with_fm_date — page fell back to updated_at even though frontmatter has parseable event_date / date / published. The "wrong but populated" residual that earlier review iterations missed. future_dated — effective_date > NOW() + 1 year (corrupt or typo'd century). pre_1990 — effective_date < 1990-01-01 (epoch math gone wrong, bad parse). Sample of last 1000 pages by default — fast on 200K-page brains. Fix hint: gbrain reindex-frontmatter. salience_health: detects pages with active takes whose emotional_weight is still 0 (recompute_emotional_weight phase hasn't run since the take landed). Reports the brain's non-zero emotional_weight count as an informational baseline. Fix hint: gbrain dream --phase recompute_emotional_weight. Both checks gracefully skip on pre-v0.29.1 brains (column doesn't exist → 42703) without surfacing as warnings. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: docs + skills convention + CHANGELOG + version bump - VERSION 0.29.0 → 0.29.1 - package.json version bump - CHANGELOG.md: full release-summary + itemized + "To take advantage" block per the project's voice rules. Two-line headline + concrete pathology framing (existing callers unchanged; new axes opt-in; agent in charge per the prime directive). - skills/conventions/salience-and-recency.md: agent-readable decision rules. "Current state → on. Canonical truth → off." plus the narrow temporal-bound exception. Cross-cutting convention propagates to brain skills via RESOLVER.md. - skills/migrations/v0.29.1.md: agent-readable upgrade instructions. Verify steps + behavior-change reference + recovery commands. The build-time tool-description generator from D2 (extract decision tables from skills/conventions/salience-and-recency.md, embed into operations.ts at build time) is deferred to a follow-up commit. The tool descriptions on the query op + get_recent_salience are inline in operations.ts for v0.29.1; the auto-gen + CI staleness gate land in v0.29.2 if drift becomes a problem in practice. 148 unit tests pass across the v0.29.1 surface (effective-date, recency-decay, query-intent, migrate, salience, recompute-emotional-weight). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> Co-Authored-By: Wintermute <wintermute@garrytan.com> --------- Co-authored-by: Wintermute <wintermute@garrytan.com> Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

…t without being asked (#592) * v0.29 foundation: emotional_weight column + formula + anomaly stats Migration v34 adds pages.emotional_weight REAL DEFAULT 0.0 (column-only, no index — salience query orders by computed score, not raw weight). Embedded DDL (schema.sql + pglite-schema.ts + schema-embedded.ts) mirrors the column so fresh installs don't need migration replay. types.ts gains: PageFilters.sort enum + PAGE_SORT_SQL whitelist (engines hardcoded ORDER BY updated_at DESC; threading lands in the next commit); SalienceOpts/SalienceResult, AnomaliesOpts/AnomalyResult, EmotionalWeightInputRow/EmotionalWeightWriteRow contracts. cycle/emotional-weight.ts: pure-function score in [0..1] from tags + takes (anglocentric default seed list; user-overridable via config key emotional_weight.high_tags). cycle/anomaly.ts: meanStddev + cohort threshold helpers with zero-stddev fallback (count > mean + 1) so rare cohorts don't produce NaN sigmas. Test coverage: migrate v34 structural assertions + 14-case formula unit + 13-case anomaly stats unit. Codex review fixes baked in: formula clamped to [0,1]; per-take weight clamped to [0,1] before averaging; zero-stddev fallback finite, never NaN. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29 engine: batch emotional-weight methods + listPages sort BrainEngine adds 4 methods, both engines implement: - batchLoadEmotionalInputs(slugs?): CTE-shaped read with per-table pre-aggregates. A page with N tags + M takes never produces N×M rows (codex C4#4) — page_tags + page_takes CTEs aggregate independently, then LEFT JOIN to pages. - setEmotionalWeightBatch(rows): UPDATE FROM unnest($1::text[], $2::text[], $3::real[]) composite-keyed on (slug, source_id). Multi- source brains can't fan out (codex C4#3) — pages.slug is unique only within source_id. Same shape that v0.18 link batches use. - getRecentSalience: time boundary computed in JS, bound as TIMESTAMPTZ. SQL identical across engines (codex C5/D5 — avoids dialect drift on $1::interval binding which has zero current uses on PGLite). - findAnomalies: tag + type cohort baselines via generate_series- densified daily-count CTEs (codex C4#6). Sparse-day rare cohorts get correct (mean, stddev) instead of biased upward by zero-omission. Year cohort deferred to v0.30. listPages threads the new PageFilters.sort enum through both engines. Was hardcoded ORDER BY updated_at DESC; now PAGE_SORT_SQL whitelist maps the 4 enum values to literal SQL fragments — no injection surface. postgres.js uses sql.unsafe; PGLite splices the fragment directly. Regression tests (PGLite, no DATABASE_URL needed): - multi-source-emotional-weight: same slug under two source_ids, setEmotionalWeightBatch on one of them, asserts the other survives untouched. Direct codex C4#3 guard. - list-pages-regression (IRON RULE): old call shape (type, tag, limit) still returns updated_desc default; new sort=updated_asc reverses; sort=created_desc orders by created_at; sort=slug alphabetical; unsupported sort enum falls back to default (defense in depth). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29 cycle: new recompute_emotional_weight phase Adds a 9th cycle phase between extract and embed. Sees the union of syncPagesAffected + synthesizeWrittenSlugs for incremental mode (so synthesize-written pages get their weight computed too — codex C2 caught that the prior plan threaded only sync). Full mode (no incremental anchors) walks every page; users hit this path on first upgrade via gbrain dream --phase recompute_emotional_weight. Phase orchestrator (cycle/recompute-emotional-weight.ts) is two SQL round-trips total regardless of brain size: 1. batchLoadEmotionalInputs(slugs?) → per-page tag/take inputs. 2. computeEmotionalWeight in memory (pure function). 3. setEmotionalWeightBatch(rows) → composite-keyed UPDATE FROM unnest. Empty affectedSlugs short-circuits (no DB read, no write). Dry-run computes weights and reports the would-write count without touching the DB. Engine throw bubbles into status:fail with code RECOMPUTE_EMOTIONAL_WEIGHT_FAIL — cycle continues to the next phase. Plumbing: - CyclePhase type adds 'recompute_emotional_weight'. - ALL_PHASES + NEEDS_LOCK_PHASES include it. - CycleReport.totals adds pages_emotional_weight_recomputed (additive, schema_version stays "1"). - runCycle's totals rollup + status derivation honor the new field. - synthesize.ts emits writtenSlugs in details so cycle.ts can union with syncPagesAffected for incremental backfill. Tests: 7-case unit (fake-engine), 3-case PGLite e2e (full mode + dry- run + ALL_PHASES position), 1000-page perf budget (<5s on PGLite). Codex C2 → A: clean separation. Phase doesn't modify runExtractCore; runs on its own seam after the existing 8 phases plus synthesize. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29 ops: get_recent_salience + find_anomalies + get_recent_transcripts Three new MCP operations + a transcripts library: - get_recent_salience: pages ranked by emotional + activity salience. Subagent-allow-listed. params: days (default 14), limit (default 20, capped 100), slugPrefix (renamed from `kind` per codex C4#10 to avoid collision with PageKind/TakeKind). - find_anomalies: cohort-level activity outliers (tag + type). Subagent-allow-listed. Year cohort deferred to v0.30. - get_recent_transcripts: raw .txt transcripts from the dream-cycle corpus dirs. LOCAL-ONLY: rejects ctx.remote === true with permission_denied (codex C3). NOT in the subagent allow-list — all subagent calls run with remote=true, would always reject (footgun if visible). Cycle's synthesize phase calls discoverTranscripts directly, so subagents that need transcripts go through the library function, not the op. Tool descriptions extracted to src/core/operations-descriptions.ts so they're pinnable in tests and stable for the Tier-2 LLM routing eval. Redirects on query/search/list_pages: personal/emotional questions should reach the new ops, not semantic search. Anti-flattery hint on query: "Do NOT assume words like crazy, notable, or big mean impressive — they often mean difficult or emotionally charged." list_pages gains updated_after (string ISO) and sort enum params, surfacing the engine threading from the prior commit. src/core/transcripts.ts: filesystem walk shared by the gated MCP op and the (commit 5) CLI command. Reuses discoverTranscripts corpus-dir resolution + isDreamOutput from cycle/transcript-discovery.ts. Trust gate lives in the op handler, not the library — the library is trusted by both the gated op and the local CLI. Allow-list: 11 → 13 (add salience + anomalies; transcripts excluded per codex C3, with a comment explaining why). Tests: 21-case description pin (catches accidental edits that change LLM-facing surface); 11-case transcripts unit covering trust gate, mtime window, dream-output skip, summary truncation, no corpus_dir; 2-case salience type-contract smoke (full Garry-test fixture in commit 6's e2e suite). Codex C1: routing-eval fixtures (skills/<x>/routing-eval.jsonl) deliberately NOT shipped — routing-eval.ts is substring-match on resolver triggers, not MCP tool routing. Real coverage lands as test/e2e/salience-llm-routing.test.ts in commit 6. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29 CLI: gbrain salience / anomalies / transcripts Three new CLI commands wired into src/cli.ts dispatch + CLI_ONLY set + help text: - gbrain salience [--days N] [--limit N] [--kind PREFIX] [--json] - gbrain anomalies [--since YYYY-MM-DD] [--lookback-days N] [--sigma N] [--json] - gbrain transcripts recent [--days N] [--full] [--json] Each command file mirrors src/commands/orphans.ts shape: pure data fn + JSON formatter + human formatter. Calls into engine.getRecentSalience / findAnomalies (already shipped) and src/core/transcripts.ts. salience and anomalies show ranked rows with per-cohort mean/stddev/sigma. transcripts honors `--full` (caps at 100KB/file) vs default summary (first non-empty line + ~250 chars). All three emit JSON with --json for agent consumption. `--kind` is accepted as a slug-prefix shorthand on `gbrain salience` even though the underlying op param is `slugPrefix` (kept the CLI flag short; the MCP-facing param uses the more-explicit name to align with PageKind/TakeKind/slugPrefix vocabulary). CLI_ONLY set in src/cli.ts gains the three new command names so they don't get forwarded to MCP-only routing. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29 e2e: Garry-test fixtures + Postgres parity + LLM routing eval PGLite e2e (no DATABASE_URL needed): - salience-pglite: the Garry test. 7 wedding-tagged pages updated today + 100 background pages backdated across 30 days via raw SQL UPDATE (codex C4#7 — engine.putPage stamps updated_at = now(), so seeding via the engine alone can't reproduce historical recency windows). Asserts wedding pages outrank random-tag noise in the 7-day window; slugPrefix filter narrows correctly; days=0 boundary case; limit cap. - anomalies-pglite: same fixture shape (7 wedding pages today, 100 background backdated). findAnomalies with sigma=3 returns the wedding-tag cohort with sigma_observed > 3 vs near-zero baseline; page_slugs sample carries the wedding pages; date with no activity returns []; high sigma threshold suppresses borderline cohorts (zero-stddev fallback stays finite — no NaN sigma). Postgres-gated e2e: - engine-parity-salience: PGLite ↔ Postgres parity for getRecentSalience and findAnomalies. Same fixture into both engines; top-result and cohort-set match. Closes the v0.22.0-style parity gap for the new v0.29 SQL idioms (EXTRACT(EPOCH ...), generate_series, CTE chain). Tier-2 LLM routing eval (ANTHROPIC_API_KEY-gated): - salience-llm-routing: calls Claude with v0.29 tool descriptions and 12 personal-query phrasings ("anything crazy lately", "what's been going on with me", etc.). Asserts the chosen tool is in the v0.29 set, not query() / search(). ~$0.10 per CI run on Haiku. Tests the ACTUAL ship criterion — replaces the discarded fake-coverage routing-eval.jsonl fixtures (codex C1 → B). This is the only test that proves the description edits drive routing. Without it, we'd ship description changes and only learn from production behavior. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.0: ship-prep — VERSION + CHANGELOG + CLAUDE Key Files VERSION + package.json bump 0.28.0 → 0.29.0. CHANGELOG.md adds a v0.29.0 release-summary in the GStack/Garry voice plus the "To take advantage of v0.29.0" block. Headline two-liner: "The brain tells you what's hot without being asked. Salience + anomaly detection ship. Search rewards hypotheses; salience surfaces them." Numbers-that-matter table covers engine surface delta, MCP op delta, allow-list delta, cycle-phase delta, schema migration, list_pages param surface, and test count. Itemized changes section lists the schema migration + new cycle phase + new MCP ops + redirect descriptions + subagent allow-list rules + new tests + a contributor note clarifying that routing-eval.ts is not the right surface for testing MCP tool routing (use the Tier-2 LLM eval pattern instead). CLAUDE.md Key Files updated for the v0.29 surface: - src/core/engine.ts: notes the 4 new methods + PageFilters.sort threading. - src/core/migrate.ts: v34 (pages_emotional_weight) entry. - src/core/cycle.ts: 8 → 9 phases, recompute_emotional_weight inserted between patterns and embed; totals.pages_emotional_weight_recomputed. - src/core/cycle/emotional-weight.ts (NEW): formula + override path. - src/core/cycle/anomaly.ts (NEW): stats helpers + zero-stddev fallback. - src/core/cycle/recompute-emotional-weight.ts (NEW): phase orchestrator. - src/core/transcripts.ts (NEW): library shared by gated MCP op + CLI. - src/core/operations-descriptions.ts (NEW): pinned tool descriptions. - src/core/minions/tools/brain-allowlist.ts: 11 → 13 entries; comment on why get_recent_transcripts is excluded. - src/commands/salience.ts / anomalies.ts / transcripts.ts (NEW): CLI surface. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1 feat: recency + salience as two orthogonal options on query op (#696) * feat: recency boost for search (v0.27.0) — temporal intent auto-detection, date filters, configurable decay New search pipeline stage: keyword + vector → RRF → cosine re-score → backlink boost → recency boost → dedup - applyRecencyBoost: hyperbolic decay, two strengths (moderate 30-day halflife, aggressive 7-day halflife) - Auto-enabled when intent.ts detects temporal/event queries (detail='high') - Manual override via SearchOpts.recencyBoost (0/1/2) - Date filtering: afterDate/beforeDate on all three search paths (keyword, keywordChunks, vector) - getPageTimestamps on both Postgres and PGLite engines - 15 tests passing (boost math + intent classification) * v0.29.1 schema: pages.{effective_date, effective_date_source, import_filename, salience_touched_at} + expression index Migration v38 adds 4 nullable columns to pages and an expression index on COALESCE(effective_date, updated_at) to support the new since/until date filters. All additive — no behavior change in the default search path; only consulted when callers opt into the new salience='on' / recency='on' axes or pass since/until. effective_date — content date (event_date / date / published / filename-date / fallback). Read by recency boost and date-filter paths only. Auto-link doesn't touch it (immune to updated_at churn). effective_date_source — sentinel for the doctor's effective_date_health check ('event_date' | 'date' | 'published' | 'filename' | 'fallback'). import_filename — basename without extension, captured at import. Used for filename-date precedence on daily/, meetings/. Older rows leave it NULL. salience_touched_at — bumped by recompute_emotional_weight when emotional_weight changes. Salience window uses GREATEST(updated_at, salience_touched_at) so newly-salient old pages enter the recent salience query. Index strategy: a partial index on effective_date alone wouldn't help the COALESCE expression in since/until filters (planner can't use it for the negative side). The expression index ((COALESCE(effective_date, updated_at))) is what actually accelerates the filter. Postgres uses CONCURRENTLY + v14-style pg_index.indisvalid pre-drop guard for prior failed CONCURRENTLY runs; PGLite uses plain CREATE INDEX. Mirror of v34's pattern. src/schema.sql + src/core/pglite-schema.ts updated for fresh installs; src/core/schema-embedded.ts regenerated via bun run build:schema. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: computeEffectiveDate helper + putPage integration Pure helper computing a page's effective_date from frontmatter precedence: 1. event_date (meeting/event pages) 2. date (dated essays) 3. published (writing/) 4. filename-date (leading YYYY-MM-DD in basename) 5. updated_at (fallback) 6. created_at (last resort) Per-prefix override: for daily/ and meetings/ slugs, filename-date jumps to position 1 — the filename is the user's primary signal there. Returns {date, source}. The source label powers the doctor's effective_date_health check to detect "fell back to updated_at" rows that look populated but are functionally a NULL. Range validation: parsed value must be in [1990-01-01, NOW + 1 year]. Out-of-range values drop to the next chain element. Wired into importFromContent + importFromFile. The put_page MCP op derives filename from slug-tail when no caller-supplied filename is available. putPage SQL on both engines extended to write the new columns. ON CONFLICT uses COALESCE(EXCLUDED.x, pages.x) so callers that don't know about the new columns (auto-link, code reindex) preserve existing values rather than blanking them. SELECT projection extended to return them; rowToPage threads them through. 21 unit tests covering: precedence chain default order, per-prefix override, parse failure fall-through, range validation [1990, NOW+1y], parseDateLoose shape variants. All pass; typecheck clean. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: backfill orchestrator + library function for existing pages src/core/backfill-effective-date.ts is the shared library function. Walks pages in keyset-paginated batches (id > last_id ORDER BY id LIMIT 1000), runs computeEffectiveDate per row, UPDATEs effective_date + effective_date_source. Resumable via the `backfill.effective_date.last_id` checkpoint key in the config table — a killed process can re-run and pick up without re-doing rows. Idempotent: a full re-walk produces the same writes. Postgres-only: SET LOCAL statement_timeout = '600s' per batch. Doesn't refuse the migration on low session settings (codex pass-2 #16). src/commands/migrations/v0_29_1.ts is the orchestrator (4 phases mirroring v0_12_2). Phase A schema (gbrain init --migrate-only), Phase B backfill (via the library function), Phase C verify (count NULL effective_date), Phase D record (handled by runner). The library function is reusable from the gbrain reindex-frontmatter CLI command in the next commit. import_filename stays NULL for backfilled rows — pre-v0.29.1 imports didn't capture it. computeEffectiveDate uses the slug-tail when filename is NULL; daily/2024-03-15 backfilled gets effective_date from the slug. Registered in src/commands/migrations/index.ts. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: gbrain reindex-frontmatter CLI command Recovery / explicit-rebuild path for pages.effective_date. Used when: - User edited frontmatter dates after import - Post-upgrade backfill orchestrator finished but the user wants to re-walk a subset (e.g. just meetings/) after fixing some frontmatter - Precedence rules change between releases Thin wrapper over backfillEffectiveDate from commit 3 — same code path the v0_29_1 orchestrator uses; one source of truth. Flags mirror reindex-code: --source <id> Scope to one sources row (placeholder; library library doesn't filter by source today, tracked v0.30+) --slug-prefix P Scope to slugs starting with P (e.g. 'meetings/') --dry-run Print what WOULD change, no DB writes --yes Skip confirmation prompt (required for non-TTY non-JSON) --json Machine-readable result envelope --force Re-apply even when computed value matches existing Wired into src/cli.ts. CLI handles its own engine lifecycle (creates + disconnects). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: recency-decay map + buildRecencyComponentSql (pure, unused) src/core/search/recency-decay.ts mirrors source-boost.ts in shape but drives RECENCY ONLY (per D9 codex resolution). Salience is a separate orthogonal axis; this map does not feed it. DEFAULT_RECENCY_DECAY: 10 generic prefixes (no fork-specific names). - concepts/ evergreen (halflifeDays=0) - originals/ 180d × 0.5 (long-tail decay; new essays nudged) - writing/ 365d × 0.4 - daily/ 14d × 1.5 (aggressive — freshness IS the signal) - meetings/ 60d × 1.0 - chat/ 7d × 1.0 - media/x/ 7d × 1.5 - media/articles/ 90d × 0.5 - people/companies/ 365d × 0.3 - deals/ 180d × 0.5 DEFAULT_FALLBACK: 90d × 0.5 for unmatched slugs. Override priority: defaults < gbrain.yml recency: < env (GBRAIN_RECENCY_DECAY) < per-call SearchOpts.recency_decay. parseRecencyDecayEnv format: comma-separated prefix:halflifeDays:coefficient triples. Refuses LOUD on parse error (RecencyDecayParseError) — codex pass-2 #M3 finding. No silent fallback like source-boost's parser. parseRecencyDecayYaml takes already-parsed YAML; throws on bad shape. buildRecencyComponentSql in sql-ranking.ts emits a CASE expression with longest-prefix-first ordering, evergreen short-circuit (literal 0 when halflifeDays=0 or coefficient=0), and EXTRACT(EPOCH ...) for non-zero branches. Output: ((CASE WHEN p.slug LIKE 'daily/%' THEN 1.5 * 14.0 / (14.0 + EXTRACT(EPOCH FROM (NOW() - <dateExpr>))/86400.0) ... END)) Typed NowExpr enum prevents SQL injection (codex pass-1 #5). Tests pass { kind: 'fixed', isoUtc } for deterministic output; production NOW(). The 'fixed' branch escapes single quotes via escapeSqlLiteral. 25 unit tests covering: env parser shape, env error cases, yaml parser shape, merge precedence (defaults < yaml < env < caller), CASE longest- prefix-first ordering, evergreen short-circuit, NowExpr fixed/now, single-quote injection defense, empty decayMap fallback path, default map composition (no fork names, concepts/ evergreen, daily/ aggressive). Pure module. Zero consumers in this commit; commit 6 wires it into getRecentSalience, commit 10 wires it into the post-fusion stage. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: refactor getRecentSalience to consume buildRecencyComponentSql Both engines (Postgres + PGLite) now build the salience formula's third term via buildRecencyComponentSql instead of inlining 1.0 / (1 + days_old). Parameters: empty decayMap + fallback { halflifeDays: 1, coefficient: 1.0 }. Math expands to 1 * 1.0 / (1.0 + days_old) = 1 / (1 + days_old) — same numeric output as v0.29.0. This is a no-behavior-change refactor preparing for commit 7's recency_bias param. recency_bias='flat' (default) reproduces v0.29.0 exactly; 'on' swaps in DEFAULT_RECENCY_DECAY for per-prefix decay. Single source of truth for the recency math: same builder feeds the salience query AND (in commit 10) the post-fusion applyRecencyBoost stage. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: get_recent_salience gains recency_bias param (default 'flat') SalienceOpts.recency_bias: 'flat' | 'on' added; default 'flat' preserves v0.29.0 ranking verbatim. Pass 'on' to opt into per-prefix decay map (concepts/originals/writing/ evergreen; daily/, media/x/, chat/ aggressive decay). When recency_bias='on', the salience query reads COALESCE(p.effective_date, p.updated_at) instead of bare p.updated_at, so the recency component is immune to auto-link updated_at churn — old concepts/ pages just-touched by auto-link don't suddenly look fresh. Both engines (Postgres + PGLite) wire the param through. resolveRecencyDecayMap() honors gbrain.yml + GBRAIN_RECENCY_DECAY env at runtime. MCP op surface: get_recent_salience gains the param with a load-bearing description teaching the agent when to use 'on' vs 'flat' (current state → on; mattering across all time → flat). No silent v0.29.0 behavior change — opt-in only (per D11 codex resolution). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: recompute_emotional_weight writes salience_touched_at; window picks up newly-salient pages setEmotionalWeightBatch on both engines now bumps salience_touched_at to NOW() ONLY when the new emotional_weight differs from the existing one (IS DISTINCT FROM, NULL-safe). No-op writes (same weight) leave the column alone — preserves "actual change" semantics. getRecentSalience window changes from WHERE p.updated_at >= boundary to WHERE GREATEST(p.updated_at, COALESCE(p.salience_touched_at, p.updated_at)) >= boundary Closes codex pass-1 finding #4: pages whose emotional_weight just changed in the dream cycle (because tags or takes shifted) but whose updated_at is older than the salience window now correctly enter the recent-salience results. Without this, "Garry just added a take to a 6-month-old page" stayed invisible to get_recent_salience until the next content edit. COALESCE(salience_touched_at, p.updated_at) handles pre-v0.29.1 rows where salience_touched_at is NULL — they fall back to p.updated_at and behave identically to v0.29.0. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: merge intent.ts → query-intent.ts; emit 3 suggestions per query D1 + D4 + D6 + D8: single regex-pass classifier returning {intent, suggestedDetail, suggestedSalience, suggestedRecency}. intent + suggestedDetail are v0.29.0 behavior verbatim (legacy intent.ts deleted; classifyQueryIntent + autoDetectDetail compat shims preserved). NEW for v0.29.1 — two orthogonal recency-axis suggestions: suggestedSalience: 'off' | 'on' | 'strong' suggestedRecency: 'off' | 'on' | 'strong' Resolution rules (per D6 narrow temporal-bound exception): - CANONICAL patterns (who is X / what is Y / code / graph) → both off - UNLESS an EXPLICIT_TEMPORAL_BOUND also matches (today / right now / this week / since X / last N days), in which case temporal-bound wins - STRONG_RECENCY (today / right now / this morning / just now) → strong - RECENCY_ON (latest / recent / this week / meeting prep / catch up / remind me / status update) → on - SALIENCE_ON (catch up / remind me / status update / prep me / what's going on / what matters) → on - default → off for both axes (v0.29.1 prime-directive: pure opt-in) Salience and recency are TRULY orthogonal (per D9). A query like "latest news on AI" → recency='on' but salience='off' (the user wants fresh, not emotionally-weighted). "What's going on with widget-co" → both on. "Who is X right now" → both 'strong'/'on' (temporal bound beats canonical 'who is'). intent.ts deleted; test/intent.test.ts renamed → test/query-intent-legacy.test.ts (unchanged behavior coverage). New test/query-intent.test.ts adds 21 cases covering all three axes' interactions: canonical wins on bare 'who is', temporal bound overrides, "catch me up" matches with up to 15 chars between, "today" → strong, intent vs recency independence. Updated callers: - src/core/search/hybrid.ts (autoDetectDetail import) - test/recency-boost.test.ts (classifyQueryIntent import) - test/benchmark-search-quality.ts (autoDetectDetail import) Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: applySalienceBoost + applyRecencyBoost + runPostFusionStages wrapper D9 + codex pass-1 #2 + #3 + pass-2 #4: salience and recency are TRULY ORTHOGONAL post-fusion stages, both running from ALL THREE hybridSearch return paths (keyword-only, embed-failure-fallback, full-hybrid). NEW src/core/search/hybrid.ts exports: - applySalienceBoost(results, scores, strength) score *= 1 + k * log(1 + score) where k = 0.15 (on) or 0.30 (strong) No time component. Pure mattering signal. - applyRecencyBoost(results, dates, strength, decayMap, fallback, nowMs?) Per-prefix decay factor: 1 + strengthMul * coefficient * halflife / (halflife + days_old) strengthMul: 1.0 (on) or 1.5 (strong) Evergreen prefixes (halflifeDays=0) skipped (factor 1.0). Pure recency signal. Independent of mattering. - runPostFusionStages(engine, results, opts) Wraps backlink + salience + recency. Called from EACH return path so keyless installs and embed failures get the same boost surface as the full hybrid path. NEW engine methods (composite-keyed for multi-source isolation): - getEffectiveDates(refs: Array<{slug, source_id}>): Map<key, Date> Returns COALESCE(effective_date, updated_at, created_at). Key format: `${source_id}::${slug}`. Mirror of getBacklinkCounts shape. - getSalienceScores(refs: Array<{slug, source_id}>): Map<key, number> Returns emotional_weight × 5 + ln(1 + take_count). Composite key. Deprecated (kept for back-compat through v0.29.x): - SearchOpts.afterDate / beforeDate (alias for since/until) - SearchOpts.recencyBoost: 0|1|2 (alias for recency: 'off'|'on'|'strong') - getPageTimestamps (use getEffectiveDates instead) NEW SearchOpts fields: - salience: 'off' | 'on' | 'strong' - recency: 'off' | 'on' | 'strong' - since: string (ISO-8601 or relative, replaces afterDate) - until: string (replaces beforeDate) Resolution: caller-explicit > legacy alias (recencyBoost) > heuristic (classifyQuery's suggestedSalience / suggestedRecency). Deleted: src/core/search/recency.ts (PR #618's, replaced) + test/recency-boost.test.ts (its scope is replaced by query-intent.test.ts + future post-fusion tests). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> Co-Authored-By: Wintermute <wintermute@garrytan.com> * v0.29.1: query op gains salience + recency + since + until params; PGLite since/until parity Combines commits 12 + 13 of the plan. Query op surface (src/core/operations.ts): - salience: 'off' | 'on' | 'strong' (with load-bearing description) - recency: 'off' | 'on' | 'strong' - since: string (ISO-8601 or relative; replaces deprecated afterDate) - until: string (replaces deprecated beforeDate) Tool descriptions teach the calling agent: - salience axis = mattering, no time component - recency axis = age decay, no mattering signal - omit either to let gbrain auto-detect from query text via classifyQuery hybrid.ts maps since/until → afterDate/beforeDate at the engine call boundary so PR #618's existing engine plumbing keeps working without rename. Codex pass-1 #10 finding closed. PGLite engine (codex pass-1 #10): since/until parity added to all three search methods (searchKeyword, searchKeywordChunks, searchVector). SQL filter against COALESCE(p.effective_date, p.updated_at, p.created_at) so date filtering matches user content-date intent (a meeting was on event_date, not when it got reimported). Filter is applied INSIDE the HNSW inner CTE in searchVector so HNSW's candidate pool already excludes out-of-range pages — preserves pagination contract. This also closes existing cross-engine drift: pre-v0.29.1 Postgres had afterDate/beforeDate from PR #618; PGLite had nothing. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: migration v39 — eval_candidates capture columns for replay reproducibility D11 codex pass-2 resolution: extend eval_candidates with 7 new nullable columns so `gbrain eval replay` can reproduce captured runs of agent-explicit salience + recency choices. Without these columns, replays of the new axis params drift. The live behavior depends on the resolved {salience, recency} values; v0.29.0's schema doesn't capture them. as_of_ts TIMESTAMPTZ — brain's logical NOW at capture (replay uses this instead of wall-clock) salience_param TEXT — what the caller passed (NULL if omitted) recency_param TEXT — same salience_resolved TEXT — final value applied recency_resolved TEXT — same salience_source TEXT — 'caller' or 'auto_heuristic' recency_source TEXT — same All nullable + additive. Pre-v0.29.1 rows stay valid. NDJSON schema_version STAYS at 1 — consumers ignore unknown fields (codex pass-1 #C2 dissolves; no cross-repo coordination needed). ADD COLUMN with no DEFAULT is metadata-only on PG 11+ and PGLite — instant on tables of any size. src/schema.sql + src/core/pglite-schema.ts mirror the additions for fresh installs; src/core/schema-embedded.ts regenerated. eval_capture.ts populates the new fields in commit 16 (docs + ship). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: doctor checks — effective_date_health + salience_health effective_date_health: sample-1000 scan detects three classes of problems (codex pass-1 #5 resolution via the effective_date_source sentinel column added in commit 1): fallback_with_fm_date — page fell back to updated_at even though frontmatter has parseable event_date / date / published. The "wrong but populated" residual that earlier review iterations missed. future_dated — effective_date > NOW() + 1 year (corrupt or typo'd century). pre_1990 — effective_date < 1990-01-01 (epoch math gone wrong, bad parse). Sample of last 1000 pages by default — fast on 200K-page brains. Fix hint: gbrain reindex-frontmatter. salience_health: detects pages with active takes whose emotional_weight is still 0 (recompute_emotional_weight phase hasn't run since the take landed). Reports the brain's non-zero emotional_weight count as an informational baseline. Fix hint: gbrain dream --phase recompute_emotional_weight. Both checks gracefully skip on pre-v0.29.1 brains (column doesn't exist → 42703) without surfacing as warnings. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: docs + skills convention + CHANGELOG + version bump - VERSION 0.29.0 → 0.29.1 - package.json version bump - CHANGELOG.md: full release-summary + itemized + "To take advantage" block per the project's voice rules. Two-line headline + concrete pathology framing (existing callers unchanged; new axes opt-in; agent in charge per the prime directive). - skills/conventions/salience-and-recency.md: agent-readable decision rules. "Current state → on. Canonical truth → off." plus the narrow temporal-bound exception. Cross-cutting convention propagates to brain skills via RESOLVER.md. - skills/migrations/v0.29.1.md: agent-readable upgrade instructions. Verify steps + behavior-change reference + recovery commands. The build-time tool-description generator from D2 (extract decision tables from skills/conventions/salience-and-recency.md, embed into operations.ts at build time) is deferred to a follow-up commit. The tool descriptions on the query op + get_recent_salience are inline in operations.ts for v0.29.1; the auto-gen + CI staleness gate land in v0.29.2 if drift becomes a problem in practice. 148 unit tests pass across the v0.29.1 surface (effective-date, recency-decay, query-intent, migrate, salience, recompute-emotional-weight). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> Co-Authored-By: Wintermute <wintermute@garrytan.com> --------- Co-authored-by: Wintermute <wintermute@garrytan.com> Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com> Co-authored-by: Wintermute <wintermute@garrytan.com>

… what's hot without being asked (#730) * v0.29 foundation: emotional_weight column + formula + anomaly stats Migration v34 adds pages.emotional_weight REAL DEFAULT 0.0 (column-only, no index — salience query orders by computed score, not raw weight). Embedded DDL (schema.sql + pglite-schema.ts + schema-embedded.ts) mirrors the column so fresh installs don't need migration replay. types.ts gains: PageFilters.sort enum + PAGE_SORT_SQL whitelist (engines hardcoded ORDER BY updated_at DESC; threading lands in the next commit); SalienceOpts/SalienceResult, AnomaliesOpts/AnomalyResult, EmotionalWeightInputRow/EmotionalWeightWriteRow contracts. cycle/emotional-weight.ts: pure-function score in [0..1] from tags + takes (anglocentric default seed list; user-overridable via config key emotional_weight.high_tags). cycle/anomaly.ts: meanStddev + cohort threshold helpers with zero-stddev fallback (count > mean + 1) so rare cohorts don't produce NaN sigmas. Test coverage: migrate v34 structural assertions + 14-case formula unit + 13-case anomaly stats unit. Codex review fixes baked in: formula clamped to [0,1]; per-take weight clamped to [0,1] before averaging; zero-stddev fallback finite, never NaN. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29 engine: batch emotional-weight methods + listPages sort BrainEngine adds 4 methods, both engines implement: - batchLoadEmotionalInputs(slugs?): CTE-shaped read with per-table pre-aggregates. A page with N tags + M takes never produces N×M rows (codex C4#4) — page_tags + page_takes CTEs aggregate independently, then LEFT JOIN to pages. - setEmotionalWeightBatch(rows): UPDATE FROM unnest($1::text[], $2::text[], $3::real[]) composite-keyed on (slug, source_id). Multi- source brains can't fan out (codex C4#3) — pages.slug is unique only within source_id. Same shape that v0.18 link batches use. - getRecentSalience: time boundary computed in JS, bound as TIMESTAMPTZ. SQL identical across engines (codex C5/D5 — avoids dialect drift on $1::interval binding which has zero current uses on PGLite). - findAnomalies: tag + type cohort baselines via generate_series- densified daily-count CTEs (codex C4#6). Sparse-day rare cohorts get correct (mean, stddev) instead of biased upward by zero-omission. Year cohort deferred to v0.30. listPages threads the new PageFilters.sort enum through both engines. Was hardcoded ORDER BY updated_at DESC; now PAGE_SORT_SQL whitelist maps the 4 enum values to literal SQL fragments — no injection surface. postgres.js uses sql.unsafe; PGLite splices the fragment directly. Regression tests (PGLite, no DATABASE_URL needed): - multi-source-emotional-weight: same slug under two source_ids, setEmotionalWeightBatch on one of them, asserts the other survives untouched. Direct codex C4#3 guard. - list-pages-regression (IRON RULE): old call shape (type, tag, limit) still returns updated_desc default; new sort=updated_asc reverses; sort=created_desc orders by created_at; sort=slug alphabetical; unsupported sort enum falls back to default (defense in depth). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29 cycle: new recompute_emotional_weight phase Adds a 9th cycle phase between extract and embed. Sees the union of syncPagesAffected + synthesizeWrittenSlugs for incremental mode (so synthesize-written pages get their weight computed too — codex C2 caught that the prior plan threaded only sync). Full mode (no incremental anchors) walks every page; users hit this path on first upgrade via gbrain dream --phase recompute_emotional_weight. Phase orchestrator (cycle/recompute-emotional-weight.ts) is two SQL round-trips total regardless of brain size: 1. batchLoadEmotionalInputs(slugs?) → per-page tag/take inputs. 2. computeEmotionalWeight in memory (pure function). 3. setEmotionalWeightBatch(rows) → composite-keyed UPDATE FROM unnest. Empty affectedSlugs short-circuits (no DB read, no write). Dry-run computes weights and reports the would-write count without touching the DB. Engine throw bubbles into status:fail with code RECOMPUTE_EMOTIONAL_WEIGHT_FAIL — cycle continues to the next phase. Plumbing: - CyclePhase type adds 'recompute_emotional_weight'. - ALL_PHASES + NEEDS_LOCK_PHASES include it. - CycleReport.totals adds pages_emotional_weight_recomputed (additive, schema_version stays "1"). - runCycle's totals rollup + status derivation honor the new field. - synthesize.ts emits writtenSlugs in details so cycle.ts can union with syncPagesAffected for incremental backfill. Tests: 7-case unit (fake-engine), 3-case PGLite e2e (full mode + dry- run + ALL_PHASES position), 1000-page perf budget (<5s on PGLite). Codex C2 → A: clean separation. Phase doesn't modify runExtractCore; runs on its own seam after the existing 8 phases plus synthesize. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29 ops: get_recent_salience + find_anomalies + get_recent_transcripts Three new MCP operations + a transcripts library: - get_recent_salience: pages ranked by emotional + activity salience. Subagent-allow-listed. params: days (default 14), limit (default 20, capped 100), slugPrefix (renamed from `kind` per codex C4#10 to avoid collision with PageKind/TakeKind). - find_anomalies: cohort-level activity outliers (tag + type). Subagent-allow-listed. Year cohort deferred to v0.30. - get_recent_transcripts: raw .txt transcripts from the dream-cycle corpus dirs. LOCAL-ONLY: rejects ctx.remote === true with permission_denied (codex C3). NOT in the subagent allow-list — all subagent calls run with remote=true, would always reject (footgun if visible). Cycle's synthesize phase calls discoverTranscripts directly, so subagents that need transcripts go through the library function, not the op. Tool descriptions extracted to src/core/operations-descriptions.ts so they're pinnable in tests and stable for the Tier-2 LLM routing eval. Redirects on query/search/list_pages: personal/emotional questions should reach the new ops, not semantic search. Anti-flattery hint on query: "Do NOT assume words like crazy, notable, or big mean impressive — they often mean difficult or emotionally charged." list_pages gains updated_after (string ISO) and sort enum params, surfacing the engine threading from the prior commit. src/core/transcripts.ts: filesystem walk shared by the gated MCP op and the (commit 5) CLI command. Reuses discoverTranscripts corpus-dir resolution + isDreamOutput from cycle/transcript-discovery.ts. Trust gate lives in the op handler, not the library — the library is trusted by both the gated op and the local CLI. Allow-list: 11 → 13 (add salience + anomalies; transcripts excluded per codex C3, with a comment explaining why). Tests: 21-case description pin (catches accidental edits that change LLM-facing surface); 11-case transcripts unit covering trust gate, mtime window, dream-output skip, summary truncation, no corpus_dir; 2-case salience type-contract smoke (full Garry-test fixture in commit 6's e2e suite). Codex C1: routing-eval fixtures (skills/<x>/routing-eval.jsonl) deliberately NOT shipped — routing-eval.ts is substring-match on resolver triggers, not MCP tool routing. Real coverage lands as test/e2e/salience-llm-routing.test.ts in commit 6. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29 CLI: gbrain salience / anomalies / transcripts Three new CLI commands wired into src/cli.ts dispatch + CLI_ONLY set + help text: - gbrain salience [--days N] [--limit N] [--kind PREFIX] [--json] - gbrain anomalies [--since YYYY-MM-DD] [--lookback-days N] [--sigma N] [--json] - gbrain transcripts recent [--days N] [--full] [--json] Each command file mirrors src/commands/orphans.ts shape: pure data fn + JSON formatter + human formatter. Calls into engine.getRecentSalience / findAnomalies (already shipped) and src/core/transcripts.ts. salience and anomalies show ranked rows with per-cohort mean/stddev/sigma. transcripts honors `--full` (caps at 100KB/file) vs default summary (first non-empty line + ~250 chars). All three emit JSON with --json for agent consumption. `--kind` is accepted as a slug-prefix shorthand on `gbrain salience` even though the underlying op param is `slugPrefix` (kept the CLI flag short; the MCP-facing param uses the more-explicit name to align with PageKind/TakeKind/slugPrefix vocabulary). CLI_ONLY set in src/cli.ts gains the three new command names so they don't get forwarded to MCP-only routing. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29 e2e: Garry-test fixtures + Postgres parity + LLM routing eval PGLite e2e (no DATABASE_URL needed): - salience-pglite: the Garry test. 7 wedding-tagged pages updated today + 100 background pages backdated across 30 days via raw SQL UPDATE (codex C4#7 — engine.putPage stamps updated_at = now(), so seeding via the engine alone can't reproduce historical recency windows). Asserts wedding pages outrank random-tag noise in the 7-day window; slugPrefix filter narrows correctly; days=0 boundary case; limit cap. - anomalies-pglite: same fixture shape (7 wedding pages today, 100 background backdated). findAnomalies with sigma=3 returns the wedding-tag cohort with sigma_observed > 3 vs near-zero baseline; page_slugs sample carries the wedding pages; date with no activity returns []; high sigma threshold suppresses borderline cohorts (zero-stddev fallback stays finite — no NaN sigma). Postgres-gated e2e: - engine-parity-salience: PGLite ↔ Postgres parity for getRecentSalience and findAnomalies. Same fixture into both engines; top-result and cohort-set match. Closes the v0.22.0-style parity gap for the new v0.29 SQL idioms (EXTRACT(EPOCH ...), generate_series, CTE chain). Tier-2 LLM routing eval (ANTHROPIC_API_KEY-gated): - salience-llm-routing: calls Claude with v0.29 tool descriptions and 12 personal-query phrasings ("anything crazy lately", "what's been going on with me", etc.). Asserts the chosen tool is in the v0.29 set, not query() / search(). ~$0.10 per CI run on Haiku. Tests the ACTUAL ship criterion — replaces the discarded fake-coverage routing-eval.jsonl fixtures (codex C1 → B). This is the only test that proves the description edits drive routing. Without it, we'd ship description changes and only learn from production behavior. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.0: ship-prep — VERSION + CHANGELOG + CLAUDE Key Files VERSION + package.json bump 0.28.0 → 0.29.0. CHANGELOG.md adds a v0.29.0 release-summary in the GStack/Garry voice plus the "To take advantage of v0.29.0" block. Headline two-liner: "The brain tells you what's hot without being asked. Salience + anomaly detection ship. Search rewards hypotheses; salience surfaces them." Numbers-that-matter table covers engine surface delta, MCP op delta, allow-list delta, cycle-phase delta, schema migration, list_pages param surface, and test count. Itemized changes section lists the schema migration + new cycle phase + new MCP ops + redirect descriptions + subagent allow-list rules + new tests + a contributor note clarifying that routing-eval.ts is not the right surface for testing MCP tool routing (use the Tier-2 LLM eval pattern instead). CLAUDE.md Key Files updated for the v0.29 surface: - src/core/engine.ts: notes the 4 new methods + PageFilters.sort threading. - src/core/migrate.ts: v34 (pages_emotional_weight) entry. - src/core/cycle.ts: 8 → 9 phases, recompute_emotional_weight inserted between patterns and embed; totals.pages_emotional_weight_recomputed. - src/core/cycle/emotional-weight.ts (NEW): formula + override path. - src/core/cycle/anomaly.ts (NEW): stats helpers + zero-stddev fallback. - src/core/cycle/recompute-emotional-weight.ts (NEW): phase orchestrator. - src/core/transcripts.ts (NEW): library shared by gated MCP op + CLI. - src/core/operations-descriptions.ts (NEW): pinned tool descriptions. - src/core/minions/tools/brain-allowlist.ts: 11 → 13 entries; comment on why get_recent_transcripts is excluded. - src/commands/salience.ts / anomalies.ts / transcripts.ts (NEW): CLI surface. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1 feat: recency + salience as two orthogonal options on query op (#696) * feat: recency boost for search (v0.27.0) — temporal intent auto-detection, date filters, configurable decay New search pipeline stage: keyword + vector → RRF → cosine re-score → backlink boost → recency boost → dedup - applyRecencyBoost: hyperbolic decay, two strengths (moderate 30-day halflife, aggressive 7-day halflife) - Auto-enabled when intent.ts detects temporal/event queries (detail='high') - Manual override via SearchOpts.recencyBoost (0/1/2) - Date filtering: afterDate/beforeDate on all three search paths (keyword, keywordChunks, vector) - getPageTimestamps on both Postgres and PGLite engines - 15 tests passing (boost math + intent classification) * v0.29.1 schema: pages.{effective_date, effective_date_source, import_filename, salience_touched_at} + expression index Migration v38 adds 4 nullable columns to pages and an expression index on COALESCE(effective_date, updated_at) to support the new since/until date filters. All additive — no behavior change in the default search path; only consulted when callers opt into the new salience='on' / recency='on' axes or pass since/until. effective_date — content date (event_date / date / published / filename-date / fallback). Read by recency boost and date-filter paths only. Auto-link doesn't touch it (immune to updated_at churn). effective_date_source — sentinel for the doctor's effective_date_health check ('event_date' | 'date' | 'published' | 'filename' | 'fallback'). import_filename — basename without extension, captured at import. Used for filename-date precedence on daily/, meetings/. Older rows leave it NULL. salience_touched_at — bumped by recompute_emotional_weight when emotional_weight changes. Salience window uses GREATEST(updated_at, salience_touched_at) so newly-salient old pages enter the recent salience query. Index strategy: a partial index on effective_date alone wouldn't help the COALESCE expression in since/until filters (planner can't use it for the negative side). The expression index ((COALESCE(effective_date, updated_at))) is what actually accelerates the filter. Postgres uses CONCURRENTLY + v14-style pg_index.indisvalid pre-drop guard for prior failed CONCURRENTLY runs; PGLite uses plain CREATE INDEX. Mirror of v34's pattern. src/schema.sql + src/core/pglite-schema.ts updated for fresh installs; src/core/schema-embedded.ts regenerated via bun run build:schema. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: computeEffectiveDate helper + putPage integration Pure helper computing a page's effective_date from frontmatter precedence: 1. event_date (meeting/event pages) 2. date (dated essays) 3. published (writing/) 4. filename-date (leading YYYY-MM-DD in basename) 5. updated_at (fallback) 6. created_at (last resort) Per-prefix override: for daily/ and meetings/ slugs, filename-date jumps to position 1 — the filename is the user's primary signal there. Returns {date, source}. The source label powers the doctor's effective_date_health check to detect "fell back to updated_at" rows that look populated but are functionally a NULL. Range validation: parsed value must be in [1990-01-01, NOW + 1 year]. Out-of-range values drop to the next chain element. Wired into importFromContent + importFromFile. The put_page MCP op derives filename from slug-tail when no caller-supplied filename is available. putPage SQL on both engines extended to write the new columns. ON CONFLICT uses COALESCE(EXCLUDED.x, pages.x) so callers that don't know about the new columns (auto-link, code reindex) preserve existing values rather than blanking them. SELECT projection extended to return them; rowToPage threads them through. 21 unit tests covering: precedence chain default order, per-prefix override, parse failure fall-through, range validation [1990, NOW+1y], parseDateLoose shape variants. All pass; typecheck clean. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: backfill orchestrator + library function for existing pages src/core/backfill-effective-date.ts is the shared library function. Walks pages in keyset-paginated batches (id > last_id ORDER BY id LIMIT 1000), runs computeEffectiveDate per row, UPDATEs effective_date + effective_date_source. Resumable via the `backfill.effective_date.last_id` checkpoint key in the config table — a killed process can re-run and pick up without re-doing rows. Idempotent: a full re-walk produces the same writes. Postgres-only: SET LOCAL statement_timeout = '600s' per batch. Doesn't refuse the migration on low session settings (codex pass-2 #16). src/commands/migrations/v0_29_1.ts is the orchestrator (4 phases mirroring v0_12_2). Phase A schema (gbrain init --migrate-only), Phase B backfill (via the library function), Phase C verify (count NULL effective_date), Phase D record (handled by runner). The library function is reusable from the gbrain reindex-frontmatter CLI command in the next commit. import_filename stays NULL for backfilled rows — pre-v0.29.1 imports didn't capture it. computeEffectiveDate uses the slug-tail when filename is NULL; daily/2024-03-15 backfilled gets effective_date from the slug. Registered in src/commands/migrations/index.ts. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: gbrain reindex-frontmatter CLI command Recovery / explicit-rebuild path for pages.effective_date. Used when: - User edited frontmatter dates after import - Post-upgrade backfill orchestrator finished but the user wants to re-walk a subset (e.g. just meetings/) after fixing some frontmatter - Precedence rules change between releases Thin wrapper over backfillEffectiveDate from commit 3 — same code path the v0_29_1 orchestrator uses; one source of truth. Flags mirror reindex-code: --source <id> Scope to one sources row (placeholder; library library doesn't filter by source today, tracked v0.30+) --slug-prefix P Scope to slugs starting with P (e.g. 'meetings/') --dry-run Print what WOULD change, no DB writes --yes Skip confirmation prompt (required for non-TTY non-JSON) --json Machine-readable result envelope --force Re-apply even when computed value matches existing Wired into src/cli.ts. CLI handles its own engine lifecycle (creates + disconnects). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: recency-decay map + buildRecencyComponentSql (pure, unused) src/core/search/recency-decay.ts mirrors source-boost.ts in shape but drives RECENCY ONLY (per D9 codex resolution). Salience is a separate orthogonal axis; this map does not feed it. DEFAULT_RECENCY_DECAY: 10 generic prefixes (no fork-specific names). - concepts/ evergreen (halflifeDays=0) - originals/ 180d × 0.5 (long-tail decay; new essays nudged) - writing/ 365d × 0.4 - daily/ 14d × 1.5 (aggressive — freshness IS the signal) - meetings/ 60d × 1.0 - chat/ 7d × 1.0 - media/x/ 7d × 1.5 - media/articles/ 90d × 0.5 - people/companies/ 365d × 0.3 - deals/ 180d × 0.5 DEFAULT_FALLBACK: 90d × 0.5 for unmatched slugs. Override priority: defaults < gbrain.yml recency: < env (GBRAIN_RECENCY_DECAY) < per-call SearchOpts.recency_decay. parseRecencyDecayEnv format: comma-separated prefix:halflifeDays:coefficient triples. Refuses LOUD on parse error (RecencyDecayParseError) — codex pass-2 #M3 finding. No silent fallback like source-boost's parser. parseRecencyDecayYaml takes already-parsed YAML; throws on bad shape. buildRecencyComponentSql in sql-ranking.ts emits a CASE expression with longest-prefix-first ordering, evergreen short-circuit (literal 0 when halflifeDays=0 or coefficient=0), and EXTRACT(EPOCH ...) for non-zero branches. Output: ((CASE WHEN p.slug LIKE 'daily/%' THEN 1.5 * 14.0 / (14.0 + EXTRACT(EPOCH FROM (NOW() - <dateExpr>))/86400.0) ... END)) Typed NowExpr enum prevents SQL injection (codex pass-1 #5). Tests pass { kind: 'fixed', isoUtc } for deterministic output; production NOW(). The 'fixed' branch escapes single quotes via escapeSqlLiteral. 25 unit tests covering: env parser shape, env error cases, yaml parser shape, merge precedence (defaults < yaml < env < caller), CASE longest- prefix-first ordering, evergreen short-circuit, NowExpr fixed/now, single-quote injection defense, empty decayMap fallback path, default map composition (no fork names, concepts/ evergreen, daily/ aggressive). Pure module. Zero consumers in this commit; commit 6 wires it into getRecentSalience, commit 10 wires it into the post-fusion stage. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: refactor getRecentSalience to consume buildRecencyComponentSql Both engines (Postgres + PGLite) now build the salience formula's third term via buildRecencyComponentSql instead of inlining 1.0 / (1 + days_old). Parameters: empty decayMap + fallback { halflifeDays: 1, coefficient: 1.0 }. Math expands to 1 * 1.0 / (1.0 + days_old) = 1 / (1 + days_old) — same numeric output as v0.29.0. This is a no-behavior-change refactor preparing for commit 7's recency_bias param. recency_bias='flat' (default) reproduces v0.29.0 exactly; 'on' swaps in DEFAULT_RECENCY_DECAY for per-prefix decay. Single source of truth for the recency math: same builder feeds the salience query AND (in commit 10) the post-fusion applyRecencyBoost stage. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: get_recent_salience gains recency_bias param (default 'flat') SalienceOpts.recency_bias: 'flat' | 'on' added; default 'flat' preserves v0.29.0 ranking verbatim. Pass 'on' to opt into per-prefix decay map (concepts/originals/writing/ evergreen; daily/, media/x/, chat/ aggressive decay). When recency_bias='on', the salience query reads COALESCE(p.effective_date, p.updated_at) instead of bare p.updated_at, so the recency component is immune to auto-link updated_at churn — old concepts/ pages just-touched by auto-link don't suddenly look fresh. Both engines (Postgres + PGLite) wire the param through. resolveRecencyDecayMap() honors gbrain.yml + GBRAIN_RECENCY_DECAY env at runtime. MCP op surface: get_recent_salience gains the param with a load-bearing description teaching the agent when to use 'on' vs 'flat' (current state → on; mattering across all time → flat). No silent v0.29.0 behavior change — opt-in only (per D11 codex resolution). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: recompute_emotional_weight writes salience_touched_at; window picks up newly-salient pages setEmotionalWeightBatch on both engines now bumps salience_touched_at to NOW() ONLY when the new emotional_weight differs from the existing one (IS DISTINCT FROM, NULL-safe). No-op writes (same weight) leave the column alone — preserves "actual change" semantics. getRecentSalience window changes from WHERE p.updated_at >= boundary to WHERE GREATEST(p.updated_at, COALESCE(p.salience_touched_at, p.updated_at)) >= boundary Closes codex pass-1 finding #4: pages whose emotional_weight just changed in the dream cycle (because tags or takes shifted) but whose updated_at is older than the salience window now correctly enter the recent-salience results. Without this, "Garry just added a take to a 6-month-old page" stayed invisible to get_recent_salience until the next content edit. COALESCE(salience_touched_at, p.updated_at) handles pre-v0.29.1 rows where salience_touched_at is NULL — they fall back to p.updated_at and behave identically to v0.29.0. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: merge intent.ts → query-intent.ts; emit 3 suggestions per query D1 + D4 + D6 + D8: single regex-pass classifier returning {intent, suggestedDetail, suggestedSalience, suggestedRecency}. intent + suggestedDetail are v0.29.0 behavior verbatim (legacy intent.ts deleted; classifyQueryIntent + autoDetectDetail compat shims preserved). NEW for v0.29.1 — two orthogonal recency-axis suggestions: suggestedSalience: 'off' | 'on' | 'strong' suggestedRecency: 'off' | 'on' | 'strong' Resolution rules (per D6 narrow temporal-bound exception): - CANONICAL patterns (who is X / what is Y / code / graph) → both off - UNLESS an EXPLICIT_TEMPORAL_BOUND also matches (today / right now / this week / since X / last N days), in which case temporal-bound wins - STRONG_RECENCY (today / right now / this morning / just now) → strong - RECENCY_ON (latest / recent / this week / meeting prep / catch up / remind me / status update) → on - SALIENCE_ON (catch up / remind me / status update / prep me / what's going on / what matters) → on - default → off for both axes (v0.29.1 prime-directive: pure opt-in) Salience and recency are TRULY orthogonal (per D9). A query like "latest news on AI" → recency='on' but salience='off' (the user wants fresh, not emotionally-weighted). "What's going on with widget-co" → both on. "Who is X right now" → both 'strong'/'on' (temporal bound beats canonical 'who is'). intent.ts deleted; test/intent.test.ts renamed → test/query-intent-legacy.test.ts (unchanged behavior coverage). New test/query-intent.test.ts adds 21 cases covering all three axes' interactions: canonical wins on bare 'who is', temporal bound overrides, "catch me up" matches with up to 15 chars between, "today" → strong, intent vs recency independence. Updated callers: - src/core/search/hybrid.ts (autoDetectDetail import) - test/recency-boost.test.ts (classifyQueryIntent import) - test/benchmark-search-quality.ts (autoDetectDetail import) Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: applySalienceBoost + applyRecencyBoost + runPostFusionStages wrapper D9 + codex pass-1 #2 + #3 + pass-2 #4: salience and recency are TRULY ORTHOGONAL post-fusion stages, both running from ALL THREE hybridSearch return paths (keyword-only, embed-failure-fallback, full-hybrid). NEW src/core/search/hybrid.ts exports: - applySalienceBoost(results, scores, strength) score *= 1 + k * log(1 + score) where k = 0.15 (on) or 0.30 (strong) No time component. Pure mattering signal. - applyRecencyBoost(results, dates, strength, decayMap, fallback, nowMs?) Per-prefix decay factor: 1 + strengthMul * coefficient * halflife / (halflife + days_old) strengthMul: 1.0 (on) or 1.5 (strong) Evergreen prefixes (halflifeDays=0) skipped (factor 1.0). Pure recency signal. Independent of mattering. - runPostFusionStages(engine, results, opts) Wraps backlink + salience + recency. Called from EACH return path so keyless installs and embed failures get the same boost surface as the full hybrid path. NEW engine methods (composite-keyed for multi-source isolation): - getEffectiveDates(refs: Array<{slug, source_id}>): Map<key, Date> Returns COALESCE(effective_date, updated_at, created_at). Key format: `${source_id}::${slug}`. Mirror of getBacklinkCounts shape. - getSalienceScores(refs: Array<{slug, source_id}>): Map<key, number> Returns emotional_weight × 5 + ln(1 + take_count). Composite key. Deprecated (kept for back-compat through v0.29.x): - SearchOpts.afterDate / beforeDate (alias for since/until) - SearchOpts.recencyBoost: 0|1|2 (alias for recency: 'off'|'on'|'strong') - getPageTimestamps (use getEffectiveDates instead) NEW SearchOpts fields: - salience: 'off' | 'on' | 'strong' - recency: 'off' | 'on' | 'strong' - since: string (ISO-8601 or relative, replaces afterDate) - until: string (replaces beforeDate) Resolution: caller-explicit > legacy alias (recencyBoost) > heuristic (classifyQuery's suggestedSalience / suggestedRecency). Deleted: src/core/search/recency.ts (PR #618's, replaced) + test/recency-boost.test.ts (its scope is replaced by query-intent.test.ts + future post-fusion tests). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> Co-Authored-By: Wintermute <wintermute@garrytan.com> * v0.29.1: query op gains salience + recency + since + until params; PGLite since/until parity Combines commits 12 + 13 of the plan. Query op surface (src/core/operations.ts): - salience: 'off' | 'on' | 'strong' (with load-bearing description) - recency: 'off' | 'on' | 'strong' - since: string (ISO-8601 or relative; replaces deprecated afterDate) - until: string (replaces deprecated beforeDate) Tool descriptions teach the calling agent: - salience axis = mattering, no time component - recency axis = age decay, no mattering signal - omit either to let gbrain auto-detect from query text via classifyQuery hybrid.ts maps since/until → afterDate/beforeDate at the engine call boundary so PR #618's existing engine plumbing keeps working without rename. Codex pass-1 #10 finding closed. PGLite engine (codex pass-1 #10): since/until parity added to all three search methods (searchKeyword, searchKeywordChunks, searchVector). SQL filter against COALESCE(p.effective_date, p.updated_at, p.created_at) so date filtering matches user content-date intent (a meeting was on event_date, not when it got reimported). Filter is applied INSIDE the HNSW inner CTE in searchVector so HNSW's candidate pool already excludes out-of-range pages — preserves pagination contract. This also closes existing cross-engine drift: pre-v0.29.1 Postgres had afterDate/beforeDate from PR #618; PGLite had nothing. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: migration v39 — eval_candidates capture columns for replay reproducibility D11 codex pass-2 resolution: extend eval_candidates with 7 new nullable columns so `gbrain eval replay` can reproduce captured runs of agent-explicit salience + recency choices. Without these columns, replays of the new axis params drift. The live behavior depends on the resolved {salience, recency} values; v0.29.0's schema doesn't capture them. as_of_ts TIMESTAMPTZ — brain's logical NOW at capture (replay uses this instead of wall-clock) salience_param TEXT — what the caller passed (NULL if omitted) recency_param TEXT — same salience_resolved TEXT — final value applied recency_resolved TEXT — same salience_source TEXT — 'caller' or 'auto_heuristic' recency_source TEXT — same All nullable + additive. Pre-v0.29.1 rows stay valid. NDJSON schema_version STAYS at 1 — consumers ignore unknown fields (codex pass-1 #C2 dissolves; no cross-repo coordination needed). ADD COLUMN with no DEFAULT is metadata-only on PG 11+ and PGLite — instant on tables of any size. src/schema.sql + src/core/pglite-schema.ts mirror the additions for fresh installs; src/core/schema-embedded.ts regenerated. eval_capture.ts populates the new fields in commit 16 (docs + ship). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: doctor checks — effective_date_health + salience_health effective_date_health: sample-1000 scan detects three classes of problems (codex pass-1 #5 resolution via the effective_date_source sentinel column added in commit 1): fallback_with_fm_date — page fell back to updated_at even though frontmatter has parseable event_date / date / published. The "wrong but populated" residual that earlier review iterations missed. future_dated — effective_date > NOW() + 1 year (corrupt or typo'd century). pre_1990 — effective_date < 1990-01-01 (epoch math gone wrong, bad parse). Sample of last 1000 pages by default — fast on 200K-page brains. Fix hint: gbrain reindex-frontmatter. salience_health: detects pages with active takes whose emotional_weight is still 0 (recompute_emotional_weight phase hasn't run since the take landed). Reports the brain's non-zero emotional_weight count as an informational baseline. Fix hint: gbrain dream --phase recompute_emotional_weight. Both checks gracefully skip on pre-v0.29.1 brains (column doesn't exist → 42703) without surfacing as warnings. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29.1: docs + skills convention + CHANGELOG + version bump - VERSION 0.29.0 → 0.29.1 - package.json version bump - CHANGELOG.md: full release-summary + itemized + "To take advantage" block per the project's voice rules. Two-line headline + concrete pathology framing (existing callers unchanged; new axes opt-in; agent in charge per the prime directive). - skills/conventions/salience-and-recency.md: agent-readable decision rules. "Current state → on. Canonical truth → off." plus the narrow temporal-bound exception. Cross-cutting convention propagates to brain skills via RESOLVER.md. - skills/migrations/v0.29.1.md: agent-readable upgrade instructions. Verify steps + behavior-change reference + recovery commands. The build-time tool-description generator from D2 (extract decision tables from skills/conventions/salience-and-recency.md, embed into operations.ts at build time) is deferred to a follow-up commit. The tool descriptions on the query op + get_recent_salience are inline in operations.ts for v0.29.1; the auto-gen + CI staleness gate land in v0.29.2 if drift becomes a problem in practice. 148 unit tests pass across the v0.29.1 surface (effective-date, recency-decay, query-intent, migrate, salience, recompute-emotional-weight). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> Co-Authored-By: Wintermute <wintermute@garrytan.com> --------- Co-authored-by: Wintermute <wintermute@garrytan.com> Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29 master-rebase fixups: renumber + drift cleanup - v0.29.1 migrations renumber v38/v39 → v41/v42 (master shipped takes_table at v37 + access_tokens_permissions at v38; v0.27.1 took v39). My v0.29.0 emotional_weight slots in at v40; v0.29.1's pages_recency_columns lands at v41 and eval_candidates_recency_capture at v42. - src/core/utils.ts comment refs updated v37 → v40 (emotional_weight) and v38 → v41 (effective_date/etc). - test/brain-allowlist.test.ts: size assertion 11 → 13 + the new get_recent_salience / find_anomalies positive checks + the explicit get_recent_transcripts negative check (v0.29 added the salience pair to the allow-list; transcripts are deliberately excluded because all subagent calls have remote=true and the v0.29 trust gate rejects them — visibility would be a footgun). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29 CI fixups: privacy allow-list + cycle phase count + migration plan Three CI test failures on PR #730, all caused by master-side state the v0.29 cherry-picks didn't yet account for: 1. scripts/check-privacy.sh allow-lists test/recency-decay.test.ts The v0.29.1 recency-decay test asserts that DEFAULT_RECENCY_DECAY's keys do NOT include fork-specific path prefixes. Because the assertion has to name the banned tokens to assert their absence, the privacy guard flagged the literal occurrence. Same exception class as CHANGELOG.md, CLAUDE.md, and scripts/check-privacy.sh itself — meta-rule enforcement requires mentioning what the rule forbids. 2. test/core/cycle.serial.test.ts: 9 → 10 phases. The yieldBetweenPhases test was written for v0.26.5 (9 phases incl. purge). v0.29 added a 10th phase (recompute_emotional_weight) between patterns and embed; the test's expected hookCalls and report.phases.length needed bumping. 3. test/apply-migrations.test.ts: append '0.29.1' to skippedFuture lists. v0.29.1 added a new entry to src/commands/migrations/index.ts; the buildPlan test snapshots the exact ordered list of versions, so it needs the new entry in both the fresh-install case and the Codex H9 regression case. All three verified locally: - bash scripts/check-privacy.sh → exit 0 - bun test test/apply-migrations.test.ts → 18/18 pass - bun test test/core/cycle.serial.test.ts → 28/28 pass Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29 CI fixup: regenerate llms-full.txt to match CLAUDE.md state build-llms test asserts the committed llms.txt + llms-full.txt match what the generator produces from the current source tree. CLAUDE.md got new v0.29 Key Files entries (recompute_emotional_weight phase, emotional-weight formula, anomaly stats, transcripts library, salience ops, etc.) without a corresponding regen. `bun run build:llms` brings llms-full.txt back in sync; llms.txt is byte-for-byte identical so only the larger inline bundle changed. Verified locally: bun test test/build-llms.test.ts → 7/7 pass. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29 e2e: cover tool-surfaces + MCP dispatch path Two gaps were uncovered when reviewing v0.29 coverage against the new contracts the cherry-picks landed onto master. 1. test/v0_29-tool-surfaces.test.ts (unit, 9 cases) Existing tests pin the description constants module and the BRAIN_TOOL_ALLOWLIST set membership, but nothing checked the two filters that ACT on those constants: - serve-http.ts:745 filters operations by !op.localOnly to build the HTTP MCP tool list. Without a test, anyone removing `localOnly: true` from get_recent_transcripts would silently expose it to remote callers — defense-in-depth on top of the in-handler ctx.remote check would be the only guard. Now pinned: get_recent_transcripts is hidden, salience + anomalies stay visible. - buildBrainTools surfaces the v0.29 ops as `brain_get_recent_salience` and `brain_find_anomalies`, and EXCLUDES `brain_get_recent_transcripts` (codex C3 footgun gate — all subagent calls are remote=true, the op would always reject). Now pinned. Both filters are pure functions; no DB / engine.connect needed. 2. test/e2e/v0_29-mcp-dispatch-pglite.test.ts (e2e, 5 cases) Existing v0.29 e2e tests call engine methods directly. None went through the full dispatchToolCall pipeline that stdio MCP and HTTP MCP both use. The new file covers: - get_recent_salience returns ranked rows via dispatch (top result is the wedding-tagged page from the seeded fixture). - find_anomalies returns the AnomalyResult shape via dispatch. - get_recent_transcripts rejects with permission_denied when ctx.remote === true (the in-handler trust gate is the last line if localOnly ever drops). - get_recent_transcripts succeeds with ctx.remote === false (CLI path) and returns [] when no corpus dir is configured. - Unknown tool name returns the standard isError + "Unknown tool" envelope (regression guard for dispatch shape). Verified locally — all 14 cases pass: bun test test/v0_29-tool-surfaces.test.ts → 9 pass bun test test/e2e/v0_29-mcp-dispatch-pglite.test.ts → 5 pass Re-ran the full v0.29 PGLite e2e suite to confirm no regressions: salience-pglite.test.ts 5 pass anomalies-pglite.test.ts 4 pass cycle-recompute-emotional-weight-pglite.test 3 pass list-pages-regression.test.ts 6 pass multi-source-emotional-weight-pglite.test 4 pass backfill-perf-pglite.test.ts 1 pass v0_29-mcp-dispatch-pglite.test.ts 5 pass ----- Total: 28 pass / 0 fail Postgres parity test (DATABASE_URL gated) 7 skip (correct) LLM routing eval (ANTHROPIC_API_KEY gated) 12 skip (correct) bun run typecheck clean Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * v0.29 CI fixup: drop unused PGLiteEngine in tool-surfaces test scripts/check-test-isolation.sh's R3 + R4 lints flagged the new test/v0_29-tool-surfaces.test.ts for instantiating PGLiteEngine outside a beforeAll() block (R3) and lacking the matching afterAll(disconnect) (R4). The intent of those rules is to prevent engine leaks across the shard process — every PGLiteEngine must follow the canonical beforeAll(connect+initSchema) / afterAll(disconnect) pattern. The fix here is upstream of the rule, not a workaround: this test never needed an engine. buildBrainTools doesn't issue any SQL at registry-build time — it only reads `engine.kind` for the put_page namespace-wrap branch. A `{ kind: 'pglite' } as unknown as BrainEngine` fake-engine literal keeps the test pure-function: no WASM cold-start, no connect lifecycle, no test-isolation rule fired. Verified locally: bash scripts/check-test-isolation.sh → OK (257 non-serial unit files) bun test test/v0_29-tool-surfaces.test.ts → 9 pass bun run typecheck → clean Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com> Co-authored-by: Wintermute <wintermute@garrytan.com>

Update Hermes Agent link in README.md

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vincentamato changed the title ~~Update Hermes Agent link in README.md~~ Correct Hermes Agent link in README.md Apr 10, 2026

garrytan closed this Apr 11, 2026

vincentamato deleted the vincentamato/fix-readme-hermes-link branch April 11, 2026 04:50

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Correct Hermes Agent link in README.md#16

Correct Hermes Agent link in README.md#16
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