gbrain/CHANGELOG.md

Changelog

All notable changes to GBrain will be documented in this file.

[0.12.2] - 2026-04-19

Postgres frontmatter queries actually work now.

Wiki articles stop disappearing when you import them.

This is a data-correctness hotfix for the v0.12.0-and-earlier Postgres-backed brains. If you run gbrain on Postgres or Supabase, you've been losing data without knowing it. PGLite users were unaffected. Upgrade auto-repairs your existing rows. Lands on top of v0.12.1 (extract N+1 fix + migration timeout fix) — pull gbrain upgrade and you get both.

What was broken

Frontmatter columns were silently stored as quoted strings, not JSON. Every put_page wrote frontmatter to Postgres via ${JSON.stringify(value)}::jsonb — postgres.js v3 stringified again on the wire, so the column ended up holding "\"{\\\"author\\\":\\\"garry\\\"}\"" instead of {"author":"garry"}. Every frontmatter->>'key' query returned NULL. GIN indexes on JSONB were inert. Same bug on raw_data.data, ingest_log.pages_updated, files.metadata, and page_versions.frontmatter. PGLite hid this entirely (different driver path) — which is exactly why it slipped past the existing test suite.

Wiki articles got truncated by 83% on import. splitBody treated any standalone --- line in body content as a timeline separator. Discovered by @knee5 migrating a 1,991-article wiki where a 23,887-byte article landed in the DB as 593 bytes (4,856 of 6,680 wikilinks lost).

/wiki/ subdirectories silently typed as concept. Articles under /wiki/analysis/, /wiki/guides/, /wiki/hardware/, /wiki/architecture/, and /writing/ defaulted to type='concept' — type-filtered queries lost everything in those buckets.

pgvector embeddings sometimes returned as strings → NaN search scores. Discovered by @leonardsellem on Supabase, where getEmbeddingsByChunkIds returned "[0.1,0.2,…]" instead of Float32Array, producing [NaN] query scores.

What you can do now that you couldn't before

• frontmatter->>'author' returns garry, not NULL. GIN indexes work. Postgres queries by frontmatter key actually retrieve pages.
• Wiki articles round-trip intact. Markdown horizontal rules in body text are horizontal rules, not timeline separators.
• Recover already-truncated pages with gbrain sync --full. Re-import from your source-of-truth markdown rebuilds compiled_truth correctly.
• Search scores stop going NaN on Supabase. Cosine rescoring sees real Float32Array embeddings.
• Type-filtered queries find your wiki articles. /wiki/analysis/ becomes type analysis, /writing/ becomes writing, etc.

How to upgrade

gbrain upgrade

The v0.12.2 orchestrator runs automatically: applies any schema changes, then gbrain repair-jsonb rewrites every double-encoded row in place using jsonb_typeof = 'string' as the guard. Idempotent — re-running is a no-op. PGLite engines short-circuit cleanly. Batches well on large brains.

If you want to recover pages that were truncated by the splitBody bug:

gbrain sync --full

That re-imports every page from disk, so the new splitBody rebuilds the full compiled_truth correctly.

What's new under the hood

• gbrain repair-jsonb — standalone command for the JSONB fix. Run it manually if needed; the migration runs it automatically. --dry-run shows what would be repaired without touching data. --json for scripting.
• CI grep guard at scripts/check-jsonb-pattern.sh — fails the build if anyone reintroduces the ${JSON.stringify(x)}::jsonb interpolation pattern. Wired into bun test so it runs on every CI invocation.
• New E2E regression test at test/e2e/postgres-jsonb.test.ts — round-trips all four JSONB write sites against real Postgres and asserts jsonb_typeof = 'object' plus ->> returns the expected scalar. The test that should have caught the original bug.
• Wikilink extraction — [[page]] and [[page|Display Text]] syntaxes now extracted alongside standard [text](page.md) markdown links. Includes ancestor-search resolution for wiki KBs where authors omit one or more leading ../.

Migration scope

The repair touches five JSONB columns:

• pages.frontmatter
• raw_data.data
• ingest_log.pages_updated
• files.metadata
• page_versions.frontmatter (downstream of pages.frontmatter via INSERT...SELECT)

Other JSONB columns in the schema (minion_jobs.{data,result,progress,stacktrace}, minion_inbox.payload) were always written via the parameterized $N::jsonb form so they were never affected.

Behavior changes (read this if you upgrade)

splitBody now requires an explicit sentinel for timeline content. Recognized markers (in priority order):

1. <!-- timeline --> (preferred — what serializeMarkdown emits)
2. --- timeline --- (decorated separator)
3. --- directly before ## Timeline or ## History heading (backward-compat fallback)

If you intentionally used a plain --- to mark your timeline section in source markdown, add <!-- timeline --> above it manually. The fallback covers the common case (--- followed by ## Timeline).

Attribution

Built from community PRs #187 (@knee5) and #175 (@leonardsellem). The original PRs reported the bugs and proposed the fixes; this release re-implements them on top of the v0.12.0 knowledge graph release with expanded migration scope, schema audit (all 5 affected columns vs the 3 originally reported), engine-aware behavior, CI grep guard, and an E2E regression test that should have caught this in the first place. Codex outside-voice review during planning surfaced the missed page_versions.frontmatter propagation path and the noisy-truncated-diagnostic anti-pattern that was dropped from this scope. Thanks for finding the bugs and providing the recovery path — both PRs left work to do but the foundation was right.

Co-Authored-By: @knee5 (PR #187 — splitBody, inferType wiki, JSONB triple-fix) Co-Authored-By: @leonardsellem (PR #175 — parseEmbedding, getEmbeddingsByChunkIds fix)

[0.12.1] - 2026-04-19

Extract no longer hangs on large brains.

v0.12.0 upgrade no longer times out on duplicates.

Two production-blocking bugs Garry hit on his 47K-page brain on April 18. gbrain extract was effectively unusable on any brain with 20K+ existing links or timeline entries — it pre-loaded the entire dedup set with one getLinks() call per page over the Supabase pooler, hanging for 10+ minutes producing zero output before any work started. The v0.12.0 schema migration that creates idx_timeline_dedup was failing on brains with pre-existing duplicate timeline rows because the DELETE ... USING self-join was O(n²) without an index, hitting Supabase Management API's 60-second ceiling on 80K+ duplicates. Both bugs end here.

The numbers that matter

Measured on the new test/extract-fs.test.ts and test/migrate.test.ts regression suites, plus 73 E2E tests against real Postgres+pgvector. Reproducible: bun test + bun run test:e2e.

Metric	BEFORE v0.12.1	AFTER v0.12.1	Δ
extract hang on 47K-page brain	10+ min, zero output	immediate work, ~30-60s wall clock	usable
DB round-trips per re-extract	47K reads + 235K writes	0 reads + ~2.4K writes	~99% fewer
v0.12.0 migration on 80K duplicate rows	timed out at 60s	completes <1s	~60x+ faster
Re-run on already-extracted brain	235K row-writes	0 row-writes	true no-op
Tests	1297 unit / 105 E2E	1412 unit / 119 E2E	+115 unit / +14 E2E
created counter on re-runs	"5000 created" (lie)	"0 created" (truth)	accurate

Per-batch round-trip math: a re-extract on a 47K-page brain with ~5 links per page used to do 235K sequential round-trips over the Supabase pooler. With 100-row batched INSERTs it does ~2,400. The hang came from the read pre-load (47K serial getLinks() calls), which is now gone entirely. The DB enforces uniqueness via ON CONFLICT DO NOTHING.

What this means for GBrain users

If you've been afraid to re-run gbrain extract because it might never finish, that's over. The command starts producing output immediately, batch-writes 100 rows per round-trip, and reports a truthful insert count even on re-runs. If your v0.12.0 upgrade got stuck on the timeline migration (or you had to manually run CREATE TABLE ... AS SELECT DISTINCT ON ... to unblock it), the next gbrain init --migrate-only is sub-second. Run gbrain extract all on your largest brain and watch it actually work.

Itemized changes

Performance

• gbrain extract no longer pre-loads the dedup set. Removed the N+1 read loop in extractLinksFromDir, extractTimelineFromDir, extractLinksFromDB, and extractTimelineFromDB that called engine.getLinks(slug) (or getTimeline) once per page across engine.listPages({ limit: 100000 }). On a 47K-page brain that was 47K serial network round-trips before the first file was even read. Both engines already enforced uniqueness at the SQL layer (UNIQUE(from_page_id, to_page_id, link_type) on links, idx_timeline_dedup on timeline_entries); the in-memory dedup Set was redundant insurance that turned into the bottleneck.
• Batched multi-row INSERTs replace per-row writes. All four extract paths now buffer 100 candidates and flush via new addLinksBatch / addTimelineEntriesBatch engine methods. Round-trips drop ~100x: ~235K → ~2,400 per full re-extract. Each batch uses INSERT ... SELECT FROM unnest($1::text[], $2::text[], ...) JOIN pages ON CONFLICT DO NOTHING RETURNING 1 — 4 (links) or 5 (timeline) array-typed bound parameters regardless of batch size, sidestepping Postgres's 65535-parameter cap entirely. PGLite uses the same SQL shape with manual $N placeholders.

Correctness

• created counter is now truthful on re-runs. Returns count of rows actually inserted (via RETURNING 1 row count), not "calls that didn't throw." A re-run on a fully-extracted brain prints Done: 0 links, 0 timeline entries from 47000 pages. Before this release it would print Done: 5000 links while inserting zero new rows.
• --dry-run deduplicates candidates across files. A link extracted from 3 different markdown files now prints exactly once in --dry-run output, matching what the batch insert would actually create. Before this release the dedup was tied to the now-deleted DB pre-load, so dry-run would over-print.
• Whole-batch errors are visible in both JSON and human modes. When a batch flush fails (DB connection drop, malformed row), the error prints to stderr in JSON mode AND to console in human mode, with the lost-row count. No more silent loss of 100 rows because of one bad row.

Schema migrations — v0.12.0 upgrade is now sub-second on duplicate-heavy brains

• Migration v9 (timeline_entries) and v8 (links) pre-create a btree helper index on the dedup columns before the DELETE ... USING self-join runs. Turns the O(n²) sequential-scan dedup into O(n log n) index-backed dedup. On 80K+ duplicate rows the migration completes in well under a second instead of timing out at 60s. The helper index is dropped after dedup, leaving the original schema unchanged. Same fix applied defensively to migration v8 — Garry's brain didn't trip it (links had fewer duplicates) but the same trap was loaded.
• phaseASchema timeout in the v0.12.0 orchestrator bumped 60s → 600s. Belt-and-suspenders: the helper-index fix should make dedup sub-second on most brains, but the outer wall-clock budget shouldn't be the failure mode for unforeseen slowness.

New engine API

• addLinksBatch(LinkBatchInput[]) → Promise<number> and addTimelineEntriesBatch(TimelineBatchInput[]) → Promise<number> on both PostgresEngine and PGLiteEngine. Returns count of actually-inserted rows (excluding ON CONFLICT no-ops and JOIN-dropped rows whose slugs don't exist). Per-row addLink / addTimelineEntry are unchanged — all 10 existing call sites compile and behave identically. Plugin authors building agent integrations on BrainEngine can adopt the batch methods at their own pace.

Tests

• Migration regression tests guard the fix structurally + behaviorally. New test/migrate.test.ts cases assert the v8 + v9 SQL literally contains the helper CREATE INDEX IF NOT EXISTS ... DROP INDEX IF EXISTS sequence in the right order (deterministic, fast, catches a regression even at 0-row scale where wall-clock can't distinguish O(n²) from O(1)) AND that the migration completes under wall-clock cap on 1000-row fixtures.
• test/extract-fs.test.ts (new file) covers the FS-source extract path end-to-end on PGLite: first-run inserts, second-run reports zero, dry-run dedups duplicate candidates across 3 files into one printed line, second-run perf regression guard.
• 9 new E2E tests for the postgres-engine batch methods in test/e2e/mechanical.test.ts. The postgres-js bind path is structurally different from PGLite's (array params via unnest() vs manual $N placeholders) and gets its own coverage against real Postgres+pgvector.
• 11 new PGLite batch method tests in test/pglite-engine.test.ts (empty batch, missing optionals normalize to empty strings, within-batch dedup via ON CONFLICT, missing-slug rows dropped by JOIN, half-existing batch returns count of new only, batch of 100).

Pre-ship review

This release was reviewed by /plan-eng-review (5 issues, all addressed including a P0 plan reshape that dropped a redundant orchestrator phase in favor of fixing migration v9 directly), /codex outside-voice review on the plan (15 findings, all P1 + P2 incorporated — most consequential: forced a cleaner separation between per-row API stability and new batch APIs so all 10 existing addLink callers stay untouched), and 5 specialist subagents (testing, maintainability, performance, security, data-migration) at ship time. The testing specialist caught a real bug in the postgres-engine batch SQL: postgres-js's sql(rows, ...) helper doesn't compose with (VALUES) AS v(...) JOIN syntax the way originally written. Switched to the cleaner unnest() array-parameter pattern in both engines, verified end-to-end against a real Postgres+pgvector container.

[0.12.0] - 2026-04-18

The graph wires itself.

Your brain stops being grep.

GBrain v0.12.0 ships a self-wiring knowledge graph. Every put_page extracts entity references and creates typed links automatically (attended, works_at, invested_in, founded, advises) with zero LLM calls. New gbrain graph-query for typed-edge traversal. Backlink-boosted hybrid search. Auto-link reconciliation on every edit. The brain stops being a text store you grep through and starts being a knowledge graph you query.

The benchmark numbers that matter

Headline from BrainBench v1, a 240-page rich-prose corpus generated by Claude Opus, run on PGLite in-memory. Same data, same queries, before vs after PR #188. No API keys at run time. Reproducible: bun run eval/runner/all.ts, ~3 min.

Metric	BEFORE PR #188	AFTER PR #188	Δ
Precision@5 (top-5 hits)	39.2%	44.7%	+5.4 pts
Recall@5 (correct in top-5)	83.1%	94.6%	+11.5 pts
Correct in top-5 (total)	217	247	+30
Graph-only F1 (ablation)	57.8% (grep)	86.6%	+28.8 pts

Per-link-type precision (graph-only, where the typed graph is the answer):

Link type	Expected	BEFORE precision	AFTER precision	Δ
works_at	120	21%	94%	+73 pts
invested_in	79	32%	90%	+58 pts
advises	61	10%	78%	+68 pts
attended	153	75%	72%	-3 pts

30 more correct answers in the top-5 the agent actually reads. 53% fewer total results to wade through. "Who works at Acme?" jumps from 21% precision (grep returns every page mentioning Acme: investors, advisors, concept pages, other companies) to 94% (graph returns just the employees).

What this means for GBrain users

The brain is no longer a text store with hybrid search bolted on. It's a queryable knowledge graph that ALSO has hybrid search. Six categories of orthogonal capability (identity resolution, temporal queries, performance at 10K-page scale, robustness to malformed input, MCP operation contract) all pass. Every page write is a graph mutation. Every query gets graph-first ranking. Auto-wire on upgrade ... gbrain post-upgrade runs the v0_12_0 orchestrator (schema, config check, backfill links, backfill timeline, verify), idempotent, ~30s on a 30K-page brain. Plus the v0.11 Minions runtime is fully merged: durable background agents + the graph layer in one release.

Itemized changes

Knowledge Graph Layer

Your brain now wires itself. Every page write automatically extracts entity references and creates typed links between pages. The links table goes from a manually-populated convention to a real, queryable knowledge graph that compounds over time.

• Auto-link on every page write. When you gbrain put a page that mentions [Alice](people/alice) or [Acme](companies/acme), those links land in the graph automatically. Stale links (refs no longer in the page text) are removed in the same call. Run a quick gbrain put and the brain knows who's connected to whom. To opt out: gbrain config set auto_link false.
• Typed relationships. Inferred from context using deterministic regex (zero LLM calls): attended (meeting -> person), works_at (CEO of, VP at, joined as), invested_in (invested in, backed by), founded (founded, co-founded), advises (advises, board member), source (frontmatter), mentions (default). On a 80-page benchmark brain: 94% type accuracy.
• gbrain extract --source db. New mode for the existing gbrain extract <links|timeline|all> command that walks pages from the engine instead of from disk. Works for live brains backed by Postgres or PGLite without a local markdown checkout — exactly what an MCP-driven Wintermute or OpenClaw setup needs. Filesystem mode (--source fs) is unchanged and still the default.
• gbrain graph-query <slug> for relationship traversal. "Who works at Acme?" → gbrain graph-query companies/acme --type works_at --direction in. "Who attended meetings with Alice?" → gbrain graph-query people/alice --type attended --depth 2. Returns typed edges with depth, not just nodes. Backed by a new traversePaths() engine method on both PGLite and Postgres with cycle prevention (no exponential blowup on cyclic subgraphs).
• Graph-powered search ranking. Hybrid search now applies a small backlink boost after cosine re-scoring (score *= 1 + 0.05 * log(1 + backlink_count)). Well-connected entities surface higher in results. Works in both keyword-only and full hybrid paths. Tested on the new test/benchmark-graph-quality.ts (80 pages, 35 queries, A/B/C comparison) — relational query recall jumps from ~30% (search alone) to 100% (graph traversal).
• Graph health metrics in gbrain health. New link_coverage and timeline_coverage percentages on entity pages (person/company), plus most_connected top-5 list. The dead_links field is dropped (always 0 under ON DELETE CASCADE — was a phantom metric). The brain_score composite formula stays but now reflects a sharper graph signal.

Schema migrations

Three new migrations apply automatically on gbrain init:

• v5 widens the links UNIQUE constraint to (from, to, link_type). The same person can now both works_at AND advises the same company as separate rows, instead of one type clobbering the other.
• v6 adds a UNIQUE index on timeline_entries(page_id, date, summary) plus ON CONFLICT DO NOTHING in addTimelineEntry. Idempotent inserts at the DB level — running gbrain extract timeline --source db twice is safe.
• v7 drops the trg_timeline_search_vector trigger that updated pages.updated_at on every timeline insert. Structured timeline entries are now graph data only, not search text. The markdown timeline section in pages.timeline still feeds search via the pages trigger. Side benefit: extraction pagination is no longer self-invalidating.

Security hardening (caught during pre-ship review)

• traverse_graph MCP depth is hard-capped at 10. Without this, a remote MCP caller could pass depth=1e6 and burn database memory/CPU on the recursive CTE.
• Auto-link is disabled for remote MCP callers (ctx.remote=true). Bare-slug regex matches people/X anywhere in page text including code fences and quoted strings. Without this gate, an untrusted MCP caller could plant arbitrary outbound links by writing pages with intentional slug references; combined with the new backlink boost, attacker-placed targets would surface higher in search.
• runAutoLink reconciliation runs inside a transaction. Without it, two concurrent put_page calls on the same slug would race: each reads stale existingKeys and recreates links the other side just removed.
• --since validates date format upfront. Invalid dates (--since yesterday) used to silently no-op the filter and reprocess the whole brain. Now: hard error with a clear message.

Tests

• 1151 unit tests pass (was 891 → +260 new)
• 105 E2E tests pass against PostgreSQL
• New test/benchmark-graph-quality.ts runs the 80-page A/B/C comparison and gates on real thresholds (link_recall > 90%, type_accuracy > 80%, idempotency true). Currently passing all 9 thresholds.
• BrainBench v1 (Cat 1+2 + 3, 4, 7, 10, 12) at 240-page Opus rich-prose corpus: Recall@5 83% → 95%, Precision@5 39% → 45%, +30 correct in top-5. Graph-only F1 86.6% vs grep 57.8%. See docs/benchmarks/2026-04-18-brainbench-v1.md.

Schema migration renumber

The graph layer migrations (originally v5/v6/v7 on the link-timeline-extract branch) were renumbered to v8/v9/v10 to land cleanly on top of master's v5/v6/v7 (Minions: minion_jobs_table, agent_orchestration_primitives, agent_parity_layer). All v8/v9/v10 SQL is idempotent — fresh installs apply the full sequence cleanly; existing v0.11.x installs apply only the new v8/v9/v10. Branch installs that pre-dated this merge (very rare) need to drop and re-init their PGLite db to pick up master's v5/v6/v7 minion_jobs schema.

[0.11.1] - 2026-04-18

Fixed — the v0.11.0 migration mega-bug

Your v0.11.0 upgrade shipped the Minions schema, worker, queue, and migration skill. It didn't ship the actual migration running on upgrade. If you upgraded and ended up with no ~/.gbrain/preferences.json, autopilot still running inline, and cron jobs still hitting agentTurn's 300s timeout — that's the bug. This release fixes it and auto-repairs on your next gbrain upgrade.

• gbrain apply-migrations is the canonical repair. Reads ~/.gbrain/migrations/completed.jsonl, diffs against the TS migration registry, runs any pending orchestrators. Idempotent: rerunning on a healthy install is cheap and silent.
• gbrain upgrade and postinstall now invoke it. runPostUpgrade tail-calls apply-migrations --yes unconditionally (Codex caught that the earlier early-return on missing upgrade-state.json left broken-v0.11.0 installs broken forever). package.json's new postinstall hook runs it after bun update gbrain / npm i gbrain. First-install guard keeps postinstall silent when no brain is configured yet.
• Stopgap for v0.11.0 binaries without this release: paste curl -fsSL https://raw.githubusercontent.com/garrytan/gbrain/v0.11.1/scripts/fix-v0.11.0.sh | bash. It writes preferences.json + a status: "partial" record so the eventual apply-migrations --yes run picks up where it left off — the stopgap does not poison the permanent migration path.

Added — autopilot supervises Minions itself, one install step

Before this release, autopilot + gbrain jobs work were two separate processes you had to manage. Now autopilot is the one install step, and it forks the Minions worker as a child with 10s-backoff restart + 5-crash cap + async SIGTERM drain that waits up to 35s for the worker to commit in-flight work before SIGKILL.

• Autopilot dispatches each cycle as a single autopilot-cycle Minion job with idempotency_key: autopilot-cycle:<slot>. A 5-min autopilot + 8-min embed no longer stacks 4 overlapping runs — the queue's unique partial index dedupes at the DB layer. Codex caught that the earlier "parent/child DAG" plan was a category error (parent/child in Minions flips the parent to waiting-children, not the child to waiting-for-parent, so extract would have run before sync).
• Per-step partial-failure handling. Each of sync / extract / embed / backlinks is wrapped in its own try/catch. Handler returns { partial: true, failed_steps: [...] } when any step fails; never throws. An intermittent extract bug no longer blocks every future cycle via Minion retry.
• Env-aware gbrain autopilot --install picks the right supervisor: launchd on macOS, systemd user unit on Linux-with-systemd (with a stricter systemctl --user is-system-running probe — the naive /run/systemd/system check was a false-positive magnet), bootstrap hook on ephemeral containers (Render / Railway / Fly / Docker — auto-injects into OpenClaw's hooks/bootstrap/ensure-services.sh when detected, use --no-inject to opt out), crontab otherwise. --target overrides detection. Uninstall mirrors all four targets.
• Worker child spawn uses resolveGbrainCliPath() — never blindly uses process.execPath (on source installs that's the Bun runtime, not gbrain). Resolution tries argv[1], then execPath ending /gbrain, then which gbrain.

Added — library-level Core fns so handlers don't kill workers

Reusing CLI entry-point functions (runExtract, runEmbed, etc.) as Minion handler bodies was wrong — any process.exit(1) on bad args would kill the entire worker process and every in-flight job. New Core fns throw instead:

• runExtractCore(engine, opts) — wraps extract-links + extract-timeline.
• runEmbedCore(engine, opts) — accepts { slug, slugs, all, stale }.
• runBacklinksCore(opts) — { action: 'check' | 'fix', dir, dryRun }.
• runLintCore(opts) — returns counts, doesn't print human detail (CLI wrapper does that).

CLI wrappers (runExtract, runEmbed, etc.) stay as thin arg-parsers that catch + process.exit(1). Handlers in jobs.ts import the Core fns directly.

Added — skillify ships as a first-class gbrain skill

Ported from Wintermute, proven in production. Paired with gbrain check-resolvable gives a user-controllable equivalent of Hermes' auto-skill-creation — you decide when and what, the tooling keeps the 10-item checklist honest.

• skills/skillify/SKILL.md — the meta skill. Triggers: "skillify this", "is this a skill?", "make this proper".
• scripts/skillify-check.ts — machine-readable audit. --json for CI, --recent to check files modified in the last 7 days.
• README now has a short section explaining the Skillify + check-resolvable pair and why user-controlled beats auto-generated.

Added — host-agnostic plugin contract (replaces handlers.json)

An earlier design draft shipped ~/.claude/gbrain-handlers.json where each entry was a shell command the worker would exec. Codex flagged this as a durable RCE surface. Dropped in favor of a code-level plugin contract:

• docs/guides/plugin-handlers.md — the full contract. Host imports gbrain/minions, constructs a MinionWorker, calls worker.register(name, fn) for every custom handler, calls worker.start(). Ships the bootstrap as code in the host repo, same trust model as any other code.
• skills/conventions/cron-via-minions.md — the rewrite convention for cron manifests. PGLite branch keeps --follow (inline); Postgres branch drops --follow + uses --idempotency-key on the cycle slot.
• skills/migrations/v0.11.0.md — body restored as the host-agent instruction manual. Walks the host through every JSONL TODO using the 10-item skillify checklist.

Added — gbrain init --migrate-only (the Codex H1 fix)

Running bare gbrain init with no flags defaulted to PGLite and called saveConfig — silently clobbering any existing Postgres config. The migration orchestrator now calls gbrain init --migrate-only which only applies the schema against the configured engine and NEVER writes a new config. Apply-migrations + stopgap + postinstall all use this flag. Bare gbrain init still exists and still defaults to PGLite when you want a fresh install.

Changed

• runPostUpgrade is now async + runs apply-migrations --yes unconditionally (Codex H8).
• gbrain upgrade's subprocess timeout for post-upgrade bumped 30s → 300s so the migration has room to do real work like autopilot install (Codex H7).
• Migration enumeration uses a TS registry at src/commands/migrations/index.ts instead of walking skills/migrations/*.md on disk — compiled binaries see the same set source installs do (Codex K).
• Migration diff rule: apply when no status: "complete" entry exists in completed.jsonl AND version ≤ installed VERSION. Earlier proposed "version > currentVersion" would have SKIPPED v0.11.0 when running v0.11.1 (Codex H9).
• Autopilot refreshes its lock-file mtime every cycle so a long-lived autopilot doesn't get declared "stale" by the next cron-fired invocation after 10 minutes (Codex C).
• CLAUDE.md gained a new "Migration is canonical, not advisory" section pinning the design principle.

Tests

34 new unit tests across preferences, init-migrate-only, apply-migrations, v0.11.0 orchestrator, handlers, autopilot-resolve-cli, autopilot-install, skillify-check. All 1177 existing tests still green.

[0.11.0] - 2026-04-18

Added — Minions (agent orchestration primitives)

Minions was a job queue. Now it's an agent runtime. Everything your orchestrator needs to fan out work across sub-agents without turning them into orphans or rate-limit disasters.

• Depth tracking and max_spawn_depth. Runaway recursion is a real prod failure. Children inherit depth = parent.depth + 1 and submit rejects past a configurable cap (default 5). Your orchestrator can no longer spawn itself into an infinite tree by accident.

• Per-parent child cap (max_children). Stop spawn storms before they hit OpenAI's rate limit. Set max_children: 10 on a parent job and the 11th submit throws. Enforced via SELECT ... FOR UPDATE on the parent row so concurrent submits can't both slip through.

• Per-job wall-clock timeout (timeout_ms). The #2 daily OpenClaw pain is "agent stops responding" ... long handler, token bloat, no clock. Now every job can declare a ceiling. handleTimeouts() dead-letters expired rows; a per-job setTimeout fires AbortSignal as a best-effort handler interrupt. No retry on timeout, terminal by design.

• Cascade cancel via recursive CTE. cancelJob() walks the full descendant tree in a single statement and cancels everything. Grandchild orphan bug is gone. Re-parented descendants (via removeChildDependency) are naturally excluded. Depth cap of 100 on the CTE as runaway safety.

• Idempotency keys. Add idempotency_key: 'sync:2026-04-18' to your submit and only one job per key ever runs. PG unique partial index enforces it at the DB layer, two concurrent pods submitting the same key collapse to one row. No more "did my cron fire twice?" anxiety.

• Child to parent child_done inbox. When a child completes, the parent gets {type:'child_done', child_id, job_name, result} posted to its inbox in the same transaction as the token rollup. Fan-in for free. readChildCompletions(parent_id) filters the inbox by message type with an optional since cursor. Works as the primitive for future waitForChildren(n) helpers.

• removeOnComplete / removeOnFail. BullMQ convenience. Completed jobs don't bloat your minion_jobs table forever. Opt in per-job, the child_done message survives because it lives in the parent's inbox, not the child's.

• Attachment manifest. New minion_attachments table for binary payloads attached to jobs. Validation catches path traversal (../, /, \, null byte), oversize (5 MiB default, raiseable), invalid base64, and duplicate filenames per job. DB-level UNIQUE (job_id, filename) defends against concurrent addAttachment races. storage_uri TEXT column forward-compat for future S3 offload.

• Cooperative AbortSignal. Pause or cascade-cancel clears the job's lock_token, the running handler's next lock renewal fails and fires ctx.signal.abort(). Handlers that respect AbortSignal stop cleanly. Handlers that ignore it get dead-lettered by the DB-side handleTimeouts, either way, the row status is correct.

• Transactional correctness fixes. completeJob() and failJob() now wrap in engine.transaction(). Parent hook invocations (resolveParent, failParent, removeChildDependency) fold into the same transaction so a process crash between child-update and parent-update can't strand the parent in waiting-children. Fixed a pre-existing bug where add() was inverting child/parent status (child got waiting-children, parent stayed waiting, making the child unclaimable until a manual UPDATE). Tests that worked around it are now cleaned up.

• Migration v7 (agent_parity_layer). Additive schema: new columns on minion_jobs (all defaulted, nullable where appropriate), new minion_attachments table, 3 partial indexes for bounded scans (idx_minion_jobs_timeout, idx_minion_jobs_parent_status, uniq_minion_jobs_idempotency). Existing installs pick it up on next gbrain init, no manual action required.

Fixed

• JSONB double-encode bug. When writing to JSONB columns via engine.executeRaw(sql, params), postgres.js auto-JSON-encodes parameters. Calling JSON.stringify(obj) first stored a JSON string literal, making jsonb_typeof = string and breaking payload->>'key' queries silently. Fixed in three call sites (child_done inbox post, updateProgress, sendMessage). PGLite tolerated both forms so the unit tests missed it, only a real-Postgres E2E with the payload->> operator caught it.

• Sibling completion race. Under READ COMMITTED, two grandchildren completing concurrently each saw the other as still-active in their pre-commit snapshot, so neither flipped the parent out of waiting-children. Fixed by taking SELECT ... FOR UPDATE on the parent row at the start of completeJob and failJob transactions. Siblings now serialize on the parent lock, second commit sees the first as completed and correctly advances the parent.

Tests

• ~33 new tests in test/minions.test.ts covering 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, setTimeout safety-net cleanup.

• test/e2e/minions-concurrency.test.ts ... two worker instances against real Postgres, 20 jobs, zero double-claims. The only test that actually verifies FOR UPDATE SKIP LOCKED under real concurrency. PGLite can't prove this.

• test/e2e/minions-resilience.test.ts ... 5 tests covering the 6 OpenClaw daily pains: spawn storms, agent stall, forgotten dispatches, cascade cancel, deep tree fan-in with grandchild completions. Every pain has a test that fails if the primitive regresses.

• 1066 unit + 105 E2E = 1171 tests passing before this ship. The parity layer isn't just planned, it's pinned down.

[0.10.2] - 2026-04-17

Security — Wave 3 (9 vulnerabilities closed)

This wave closes a high-severity arbitrary-file-read in file_upload, fixes a fake trust boundary that let any cwd-local recipe execute arbitrary commands, and lays down real SSRF defense for HTTP health checks. If you ran gbrain in a directory where someone could drop a recipes/ folder, this matters.

• Arbitrary file read via file_upload is closed. Remote (MCP) callers were able to read /etc/passwd or any other host file. Path validation now uses realpathSync + path.relative to catch symlinked-parent traversal, plus an allowlist regex for slugs and filenames (control chars, backslashes, RTL-override Unicode all rejected). Local CLI users still upload from anywhere — only remote callers are confined. Fixes Issue #139, contributed by @Hybirdss; original fix #105 by @garagon.
• Recipe trust boundary is real now. loadAllRecipes() previously marked every recipe as embedded=true, including ones from ./recipes/ in your cwd or $GBRAIN_RECIPES_DIR. Anyone who could drop a recipe in cwd could bypass every health-check gate. Now only package-bundled recipes (source install + global install) are trusted. Original fixes #106, #108 by @garagon.
• String health_checks blocked for untrusted recipes. Even with the recipe trust fix, the string health_check path ran execSync before reaching the typed-DSL switch — a malicious "embedded" recipe could curl http://169.254.169.254/metadata and exfiltrate cloud credentials. Non-embedded recipes are now hard-blocked from string health_checks; embedded recipes still get the isUnsafeHealthCheck defense-in-depth guard.
• SSRF defense for HTTP health_checks. New isInternalUrl() blocks loopback, RFC1918, link-local (incl. AWS metadata 169.254.169.254), CGNAT, IPv6 loopback, and IPv4-mapped IPv6 ([::ffff:127.0.0.1] canonicalized to hex hextets — both forms blocked). Bypass encodings handled: hex IPs (0x7f000001), octal (0177.0.0.1), single decimal (2130706433). Scheme allowlist rejects file:, data:, blob:, ftp:, javascript:. fetch runs with redirect: 'manual' and re-validates every Location header up to 3 hops. Original fix #108 by @garagon.
• Prompt injection hardening for query expansion. Restructured the LLM prompt with a system instruction that declares the query as untrusted data, plus an XML-tagged <user_query> boundary. Layered with regex sanitization (strips code fences, tags, injection prefixes) and output-side validation on the model's alternative_queries array (cap length, strip control chars, dedup, drop empties). The console.warn on stripped content never logs the query text itself. Original fix #107 by @garagon.
• list_pages and get_ingest_log actually cap now. Wave 3 found that clampSearchLimit(limit, default) was always allowing up to 100 — the second arg was the default, not the cap. Added a third cap parameter so list_pages caps at 100 and get_ingest_log caps at 50. Internal bulk commands (embed --all, export, migrate-engine) bypass the operation layer entirely and remain uncapped. Original fix #109 by @garagon.

Added

• OperationContext.remote flag distinguishes trusted local CLI callers from untrusted MCP callers. Security-sensitive operations (currently file_upload) tighten their behavior when remote=true. Defaults to strict (treat as remote) when unset.
• Exported security helpers for testing and reuse: validateUploadPath, validatePageSlug, validateFilename, parseOctet, hostnameToOctets, isPrivateIpv4, isInternalUrl, getRecipeDirs, sanitizeQueryForPrompt, sanitizeExpansionOutput.
• 49 new tests covering symlink traversal, scheme allowlist, IPv4 bypass forms, IPv6 mapped addresses, prompt injection patterns, and recipe trust boundaries. Plus an E2E regression proving remote callers can't escape cwd.

Contributors

Wave 3 fixes were contributed by @garagon (PRs #105-#109) and @Hybirdss (Issue #139). The collector branch re-implemented each fix with additional hardening for the residuals Codex caught during outside-voice review (parent-symlink traversal, fake isEmbedded boundary, redirect-following SSRF, scheme bypasses, clampSearchLimit semantics).

[0.10.1] - 2026-04-15

Fixed

• gbrain sync --watch actually works now. The watch loop existed but was never called because the CLI routed sync through the operation layer (single-pass only). Now sync routes through the CLI path that knows about --watch and --interval. Your cron workaround is no longer needed.

• Sync auto-embeds your pages. After syncing, gbrain now embeds the changed pages automatically. No more "I synced but search can't find my new page." Opt out with --no-embed. Large syncs (100+ pages) defer embedding to gbrain embed --stale.

• First sync no longer repeats forever. performFullSync wasn't saving its checkpoint. Fixed: sync state persists after full import so the next sync is incremental.

• dead_links metric is consistent across engines. Postgres was counting empty-content chunks instead of dangling links. Now both engines count the same thing: links pointing to non-existent pages.

• Doctor recommends the right embed command. Was suggesting gbrain embed refresh (doesn't exist). Now correctly says gbrain embed --stale.

Added

• gbrain extract links|timeline|all builds your link graph and structured timeline from existing markdown. Scans for markdown links, frontmatter fields (company, investors, attendees), and See Also sections. Infers link types from directory structure. Parses both bullet (- **YYYY-MM-DD** | Source — Summary) and header (### YYYY-MM-DD — Title) timeline formats. Runs automatically after every sync.

• gbrain features --json --auto-fix scans your brain and tells you what you're not using, with your own numbers. Priority 1 (data quality): missing embeddings, dead links. Priority 2 (unused features): zero links, zero timeline, low coverage, unconfigured integrations. Agents run --auto-fix to handle everything automatically.

• gbrain autopilot --install sets up a persistent daemon that runs sync, extract, and embed in a continuous loop. Health-based scheduling: brain score >= 90 slows down, < 70 speeds up. Installs as a launchd service (macOS) or crontab entry (Linux). One command, brain maintains itself forever.

• Brain health score (0-100) in gbrain health and gbrain doctor. Weighted composite of embed coverage, link density, timeline coverage, orphan pages, and dead links. Agents use it as a health gate.

• gbrain embed --slugs embeds specific pages by slug. Used internally by sync auto-embed to target just the changed pages.

• Instruction layer for agents. RESOLVER.md routing entries, maintain skill sections, and setup skill phase for extract, features, and autopilot. Without these, agents would never discover the new commands.

[0.10.0] - 2026-04-14

Added

• Background jobs that don't die. Minions is a BullMQ-inspired job queue built directly into GBrain. No Redis. No external dependencies. Submit gbrain jobs submit embed --follow and it runs with automatic retry, exponential backoff, and stall detection. Kill the process mid-job? Stall detection catches it and requeues. Run gbrain jobs work to start a persistent worker daemon that processes jobs from the queue. Jobs are first-class: submit, list, cancel, retry, prune, stats, all from the CLI or MCP. Your agent can now run long operations (14K+ page embeds, bulk enrichment) as durable background jobs instead of fragile inline commands.

• Your agent now has 24 skills, not 8. 16 new brain skills generalized from a production deployment with 14,700+ pages. Signal detection, brain-first lookup, content ingestion (articles, video, meetings), entity enrichment, task management, cron scheduling, reports, and cross-modal review. All shipped as fat markdown files your agent reads on demand.

• Signal detector fires on every message. A cheap sub-agent spawns in parallel to capture original thinking and entity mentions. Ideas get preserved with exact phrasing. Entities get brain pages. The brain compounds on autopilot.

• RESOLVER.md routes your agent to the right skill. Modeled on a 215-line production dispatcher. Categorized routing table: always-on, brain ops, ingestion, thinking, operational. Your agent reads it, matches the user's intent, loads the skill. No slash commands needed.

• Soul-audit builds your agent's identity. 6-phase interactive interview generates SOUL.md (who the agent is), USER.md (who you are), ACCESS_POLICY.md (who sees what), and HEARTBEAT.md (operational cadence). Re-runnable anytime. Ships with minimal defaults so first boot is instant.

• Access control out of the box. 4-tier privacy policy (Full/Work/Family/None) enforced by skill instructions before every response. Template-based, configurable per user.

• Conventions directory codifies operational discipline. Brain-first lookup protocol, citation quality standards, model routing table, test-before-bulk rule, and cross-modal review pairs. These are the hard-won patterns that prevent bad bulk runs and silent failures.

• gbrain init detects GStack and reports mod status. After brain setup, init now shows how many skills are loaded, whether GStack is installed, and where to get it. GStack detection uses gstack-global-discover with fallback to known host paths.

• Conformance standard for all skills. Every skill now has YAML frontmatter (name, version, description, triggers, tools, mutating) plus Contract, Anti-Patterns, and Output Format sections. Two new test files validate conformance across all 25 skills.

• Existing 8 skills migrated to conformance format. Frontmatter added, Workflow renamed to Phases, Contract and Anti-Patterns sections added. Ingest becomes a thin router delegating to specialized ingestion skills.

The 16 new skills

Skill	What it does	Why it matters
signal-detector	Fires on every message. Spawns a cheap model in parallel to capture original thinking and entity mentions.	Your brain compounds on autopilot. Every conversation is an ingest event. Miss a signal and the brain never learns it.
brain-ops	Brain-first lookup before any external API. The read-enrich-write loop that makes every response smarter.	Without this, your agent reaches for Google when the answer is already in the brain. Wastes tokens, misses context.
idea-ingest	Links, articles, tweets go into the brain with analysis, author people pages, and cross-linking.	Every article worth reading is worth remembering. The author gets a people page. The ideas get cross-linked to what you already know.
media-ingest	Video, audio, PDF, books, screenshots, GitHub repos. Transcripts, entity extraction, backlink propagation.	One skill handles every media format. Absorbs what used to be 3 separate skills (video-ingest, youtube-ingest, book-ingest).
meeting-ingestion	Transcripts become brain pages. Every attendee gets enriched. Every company discussed gets a timeline entry.	A meeting is NOT fully ingested until every entity is propagated. This is the skill that turns a transcript into 10 updated brain pages.
citation-fixer	Scans brain pages for missing or malformed [Source: ...] citations. Fixes formatting to match the standard.	Without citations, you can't trace facts back to where they came from. Six months later, "who said this?" has an answer.
repo-architecture	Where new brain files go. Decision protocol: primary subject determines directory, not format or source.	Prevents the #1 misfiling pattern: dumping everything in sources/ because it came from a URL.
skill-creator	Create new skills following the conformance standard. MECE check against existing skills. Updates manifest and resolver.	Users who need a capability GBrain doesn't have can create it themselves. The skill teaches the agent how to extend itself.
daily-task-manager	Add, complete, defer, remove, review tasks with priority levels (P0-P3). Stored as a searchable brain page.	Your tasks live in the brain, not a separate app. The agent can cross-reference tasks with meeting notes and people pages.
daily-task-prep	Morning preparation. Calendar lookahead with brain context per attendee, open threads from yesterday, active task review.	Walk into every meeting with full context on every person in the room, automatically.
cross-modal-review	Spawn a different AI model to review the agent's work before committing. Refusal routing: if one model refuses, silently switch.	Two models agreeing is stronger signal than one model being thorough. Refusal routing means the user never sees "I can't do that."
cron-scheduler	Schedule staggering (5-min offsets), quiet hours (timezone-aware with wake-up override), thin job prompts.	21 cron jobs at :00 is a thundering herd. Staggering prevents it. Quiet hours mean no 3 AM notifications. Wake-up override releases the backlog.
reports	Timestamped reports with keyword routing. "What's the latest briefing?" maps to the right report directory.	Cheap replacement for vector search on frequent queries. Don't embed. Load the file.
testing	Validates every skill has SKILL.md with frontmatter, manifest coverage, resolver coverage. The CI for your skill system.	3 skills and you need validation. 24 skills and you need it yesterday. Catches dead references, missing sections, MECE violations.
soul-audit	6-phase interview that generates SOUL.md, USER.md, ACCESS_POLICY.md, HEARTBEAT.md. Your agent's identity, built from your answers.	What makes Wintermute feel like Wintermute. Without personality and access control, every agent feels the same.
webhook-transforms	External events (SMS, meetings, social mentions) converted into brain pages with entity extraction. Dead-letter queue for failures.	Your brain ingests signals from everywhere. Not just conversations, but every webhook, every notification, every external event.

Infrastructure (new in v0.10.0)

• Your brain now self-validates its own skill routing. checkResolvable() verifies every skill is reachable from RESOLVER.md, detects MECE overlaps, flags missing triggers, and catches DRY violations. Runs from bun test, gbrain doctor, and the skill-creator skill. Every issue comes with a machine-readable fix object the agent can act on.

• gbrain doctor got serious. 8 health checks now (up from 5), plus a composite health score (0-100). Filesystem checks (resolver, conformance) run even without a database. --fast skips DB checks. --json output includes structured issues array with action strings so agents can parse and auto-fix.

• Batch operations won't melt your machine anymore. Adaptive load-aware throttling checks CPU and memory before each batch item. Exponential backoff with a 20-attempt safety cap. Active hours multiplier slows batch work during the day. Two concurrent batch process limit.

• Your agent's classifiers get smarter automatically. Fail-improve loop: try deterministic code first, fall back to LLM, log every fallback. Over time, the logs reveal which regex patterns are missing. Auto-generates test cases from successful LLM results. Tracks deterministic hit rate in gbrain doctor output.

• Voice notes just work. Groq Whisper transcription (with OpenAI fallback) via transcribe_audio operation. Files over 25MB get ffmpeg-segmented automatically. Transcripts flow through the standard import pipeline, entities get extracted, back-links get created.

• Enrichment is now a global service, not a per-skill skill. Every ingest pathway can call extractAndEnrich() to detect entities and create/update their brain pages. Tier auto-escalation: entities start at Tier 3, auto-promote to Tier 1 based on mention frequency across sources.

• Data research: one skill for any email-to-tracker pipeline. New data-research skill with parameterized YAML recipes. Extract investor updates (MRR, ARR, runway, headcount), expense receipts, company metrics from email. Battle-tested regex patterns, extraction integrity rule (save first, report second), dedup with configurable tolerance, canonical tracker pages with running totals.

For contributors

• test/skills-conformance.test.ts validates every skill has valid frontmatter and required sections
• test/resolver.test.ts validates RESOLVER.md coverage and routing consistency
• skills/manifest.json now has conformance_version field and lists all 24 skills
• Identity templates in templates/ (SOUL.md, USER.md, ACCESS_POLICY.md, HEARTBEAT.md)

[0.9.3] - 2026-04-12

Added

• Search understands what you're asking. +21% page coverage, +29% signal, 100% source accuracy. A zero-latency intent classifier reads your query and picks the right search mode. "Who is Alice?" surfaces your compiled truth assessment. "When did we last meet?" surfaces timeline entries with dates. No LLM call, just pattern matching. Your agent sees 8.7 relevant pages per query instead of 7.2, and two thirds of returned chunks are now distilled assessments instead of half. Entity lookups always lead with compiled truth. Temporal queries always find the dates. Benchmarked against 29 pages, 20 queries with graded relevance (run bun run test/benchmark-search-quality.ts to reproduce). Inspired by Ramp Labs' "Latent Briefing" paper (April 2026).
• gbrain query --detail low/medium/high. Agents can control how deep search goes. low returns compiled truth only. medium (default) returns everything with dedup. high returns all chunks uncapped. Auto-escalates from low to high if no results found. MCP picks it up automatically.
• gbrain eval measures search quality. Full retrieval evaluation harness with P@k, R@k, MRR, nDCG@k metrics. A/B comparison mode for parameter tuning: gbrain eval --qrels queries.json --config-a baseline.json --config-b boosted.json. Contributed by @4shut0sh.
• CJK queries expand correctly. Chinese, Japanese, and Korean text was silently skipping query expansion because word count used space-delimited splitting. Now counts characters for CJK. Contributed by @YIING99.
• Health checks speak a typed language now. Recipe health_checks use a typed DSL (http, env_exists, command, any_of) instead of raw shell strings. No more execSync(untrustedYAML). Your agent runs gbrain integrations doctor and gets structured results, not shell injection risk. All 7 first-party recipes migrated. String health checks still work (with deprecation warning) for backward compat.

Fixed

• Your storage backend can't be tricked into reading /etc/passwd. LocalStorage now validates every path stays within the storage root. ../../etc/passwd gets "Path traversal blocked" instead of your system files. All 6 methods covered (upload, download, delete, exists, list, getUrl).
• MCP callers can't read arbitrary files via file_url. resolveFile() now validates the requested path stays within the brain root before touching the filesystem. Previously, ../../etc/passwd would read any file the process could access.
• .supabase marker files can't escape their scope. Marker prefix validation now rejects ../, absolute paths, and bare ... A crafted .supabase file in a shared brain repo can't make storage requests outside the intended prefix.
• File queries can't blow up memory. The slug-filtered file_list MCP operation now has the same LIMIT 100 as the unfiltered branch. Also fixed the CLI gbrain files list and gbrain files verify commands.
• Symlinks in brain directories can't exfiltrate files. All 4 file walkers in files.ts plus the init.ts size counter now use lstatSync and skip symlinks. Broken symlinks and node_modules directories are also skipped.
• Recipe health checks can't inject shell commands. Non-embedded (user-created) recipes with shell metacharacters in health_check strings are blocked. First-party recipes are trusted but migrated to the typed DSL.

[0.9.2] - 2026-04-12

Fixed

• Fresh local installs initialize cleanly again. gbrain init now creates the local PGLite data directory before taking its advisory lock, so first-run setup no longer misreports a missing directory as a lock timeout.

[0.9.1] - 2026-04-11

Fixed

• Your brain can't be poisoned by rogue frontmatter anymore. Slug authority is now path-derived. A file at notes/random.md can't declare slug: people/admin and silently overwrite someone else's page. Mismatches are rejected with a clear error telling you exactly what to fix.
• Symlinks in your notes directory can't exfiltrate files. The import walker now uses lstatSync and refuses to follow symlinks, blocking the attack where a contributor plants a link to ~/.zshrc in the brain directory. Defense-in-depth: importFromFile itself also checks.
• Giant payloads through MCP can't rack up your OpenAI bill. importFromContent now checks Buffer.byteLength before any processing. 10 MB of emoji through put_page? Rejected before chunking starts.
• Search can't be weaponized into a DoS. limit is clamped to 100 across all search paths (keyword, vector, hybrid). statement_timeout: 8s on the Postgres connection as defense-in-depth. Requesting limit: 10000000 now gets you 100 results and a warning.
• PGLite stops crashing when two processes touch the same brain. File-based advisory lock using atomic mkdir with PID tracking and 5-minute stale detection. Clear error messages tell you which process holds the lock and how to recover.
• 12 data integrity fixes landed. Orphan chunks cleaned up on empty pages. Write operations (addLink, addTag, addTimelineEntry, putRawData, createVersion) now throw when the target page doesn't exist instead of silently no-opping. Health metrics (stale_pages, dead_links, orphan_pages) now measure real problems instead of always returning 0. Keyword search moved from JS-side sort-and-splice to a SQL CTE with LIMIT. MCP server validates params before dispatch.
• Stale embeddings can't lie to you anymore. When chunk text changes but embedding fails, the old vector is now NULL'd out instead of preserved. Previously, search could return results based on outdated vectors attached to new text.
• Embedding failures are no longer silent. The catch { /* non-fatal */ } is gone. You now get [gbrain] embedding failed for slug (N chunks): error message in stderr. Still non-fatal, but you know what happened.
• O(n^2) chunk lookup in embedPage is gone. Replaced find() + indexOf() with a single Map lookup. Matches the pattern embedAll already uses.
• Stdin bombs blocked. parseOpArgs now caps stdin at 5 MB before the full buffer is consumed.

Added

• gbrain embed --all is 30x faster. Sliding worker pool with 20 concurrent workers (tunable via GBRAIN_EMBED_CONCURRENCY). A 20,000-chunk corpus that took 2.5 hours now finishes in ~8 minutes.
• Search pagination. Both search and query now accept --offset for paginating through results. Combined with the 100-result ceiling, you can now page through large result sets.
• gbrain ask is an alias for gbrain query. CLI-only, doesn't appear in MCP tools-json.
• Content hash now covers all page fields. Title, type, and frontmatter changes trigger re-import. First sync after upgrade will re-import all pages (one-time, expected).
• Migration file for v0.9.1. Auto-update agent knows to expect the full re-import and will run gbrain embed --all afterward.
• pgcrypto extension added to schema. Fallback for gen_random_uuid() on Postgres < 13.

Changed

• Search type and exclude_slugs filters now work. These were advertised in the API but never implemented. Both searchKeyword and searchVector now respect type and exclude_slugs params.
• Hybrid search no longer double-embeds the query. expandQuery already includes the original, so we use it directly instead of prepending.

[0.9.0] - 2026-04-11

Added

• Large files don't bloat your git repo anymore. gbrain files upload-raw auto-routes by size: text and PDFs under 100 MB stay in git, everything larger (or any media file) goes to Supabase Storage with a .redirect.yaml pointer left in the repo. Files over 100 MB use TUS resumable upload (6 MB chunks with retry and backoff) so a flaky connection doesn't lose a 2 GB video upload. gbrain files signed-url generates 1-hour access links for private buckets.

• The full file migration lifecycle works end to end. mirror uploads to cloud and keeps local copies. redirect replaces local files with .redirect.yaml pointers (verifies remote exists first, won't delete data). restore downloads back from cloud. clean removes pointers when you're sure. status shows where you are. Three states, zero data loss risk.

• Your brain now enforces its own graph integrity. The Iron Law of Back-Linking is mandatory across all skills. Every mention of a person or company creates a bidirectional link. This transforms your brain from a flat file store into a traversable knowledge graph.

• Filing rules prevent the #1 brain mistake. New skills/_brain-filing-rules.md stops the most common error: dumping everything into sources/. File by primary subject, not format. Includes notability gate and citation requirements.

• Enrichment protocol that actually works. Rewritten from a 46-line API list to a 7-step pipeline with 3-tier system, person/company page templates, pluggable data sources, validation rules, and bulk enrichment safety.

• Ingest handles everything. Articles, videos, podcasts, PDFs, screenshots, meeting transcripts, social media. Each with a workflow that uses real gbrain commands (upload-raw, signed-url) instead of theoretical patterns.

• Citation requirements across all skills. Every fact needs inline [Source: ...] citations. Three formats, source precedence hierarchy.

• Maintain skill catches what you missed. Back-link enforcement, citation audit, filing violations, file storage health checks, benchmark testing.

• Voice calls don't crash on em dashes anymore. Unicode sanitization for Twilio WebSocket, PII scrub, identity-first prompt, DIY STT+LLM+TTS pipeline option, Smart VAD default, auto-upload call audio via gbrain files upload-raw.

• X-to-Brain gets eyes. Image OCR, Filtered Stream real-time monitoring, 6-dimension tweet rating rubric, outbound tweet monitoring, cron staggering.

• Share brain pages without exposing the brain. gbrain publish generates beautiful, self-contained HTML from any brain page. Strips private data (frontmatter, citations, confirmations, brain links, timeline) automatically. Optional AES-256-GCM password gate with client-side decryption, no server needed. Dark/light mode, mobile-optimized typography. This is the first code+skill pair: deterministic code does the work, the skill tells the agent when and how. See the Thin Harness, Fat Skills thread for the architecture philosophy.

Changed

• Supabase Storage now auto-selects upload method by file size: standard POST for < 100 MB, TUS resumable for >= 100 MB. Signed URL generation for private bucket access (1-hour expiry).

• File resolver supports both .redirect.yaml (v0.9+) and legacy .redirect (v0.8) formats for backward compatibility.

• Redirect format upgraded from .redirect (5 fields) to .redirect.yaml (10 fields: target, bucket, storage_path, size, size_human, hash, mime, uploaded, source_url, type).

• All skills updated to reference actual gbrain files commands instead of theoretical patterns.

• Back-link enforcer closes the loop. gbrain check-backlinks check scans your brain for entity mentions without back-links. gbrain check-backlinks fix creates them. The Iron Law of Back-Linking is in every skill, now the code enforces it.

• Page linter catches LLM slop. gbrain lint flags "Of course! Here is..." preambles, wrapping code fences, placeholder dates, missing frontmatter, broken citations, and empty sections. gbrain lint --fix auto-strips the fixable ones. Every brain that uses AI for ingestion accumulates this. Now it's one command.

• Audit trail for everything. gbrain report --type enrichment-sweep saves timestamped reports to brain/reports/{type}/YYYY-MM-DD-HHMM.md. The maintain skill references this for enrichment sweeps, meeting syncs, and maintenance runs.

• Publish skill added to manifest (8th skill). First code+skill pair.

• Skills version bumped to 0.9.0.

• 67 new unit tests across publish, backlinks, lint, and report. Total: 409 pass.

[0.8.0] - 2026-04-11

Added

• Your AI can answer the phone now. Voice-to-brain v0.8.0 ships 25 production patterns from a real deployment. WebRTC works in a browser tab with just an OpenAI key, phone number via Twilio is optional. Your agent picks its own name and personality. Pre-computed engagement bids mean it greets you with something specific ("dude, your social radar caught something wild today"), not "how can I help you?" Context-first prompts, proactive advisor mode, caller routing, dynamic noise suppression, stuck watchdog, thinking sounds during tool calls. This is the "Her" experience, out of the box.
• Upgrade = feature discovery. When you upgrade to v0.8.0, the CLI tells you what's new and your agent offers to set up voice immediately. WebRTC-first (zero setup), then asks about a phone number. Migration files now have YAML frontmatter with feature_pitch so every future version can pitch its headline feature through the upgrade flow.
• Remote MCP simplified. The Supabase Edge Function deployment is gone. Remote MCP now uses a self-hosted server + ngrok tunnel. Simpler, more reliable, works with any AI client. All docs/mcp/ guides updated to reflect the actual production architecture.

Changed

• Voice recipe is now 25 production patterns deep. Identity separation, pre-computed bid system, context-first prompts, proactive advisor mode, conversation timing (the #1 fix), no-repetition rule, radical prompt compression (13K to 4.7K tokens), OpenAI Realtime Prompting Guide structure, auth-before-speech, brain escalation, stuck watchdog, never-hang-up rule, thinking sounds, fallback TwiML, tool set architecture, trusted user auth, caller routing, dynamic VAD, on-screen debug UI, live moment capture, belt-and-suspenders post-call, mandatory 3-step post-call, WebRTC parity, dual API event handling, report-aware query routing.
• WebRTC session pseudocode updated. Native FormData, tools in session config, type: 'realtime' on all session.update calls. WebRTC transcription NOT supported over data channel (use Whisper post-call).
• MCP docs rewritten. All per-client guides (Claude Code, Claude Desktop, Cowork, Perplexity) updated from Edge Function URLs to self-hosted + ngrok pattern.

Removed

• Supabase Edge Function MCP deployment. scripts/deploy-remote.sh, supabase/functions/gbrain-mcp/, src/edge-entry.ts, .env.production.example, docs/mcp/CHATGPT.md all removed. The Edge Function never worked reliably. Self-hosted + ngrok is the path.

[0.7.0] - 2026-04-11

Added

• Your brain now runs locally with zero infrastructure. PGLite (Postgres 17.5 compiled to WASM) gives you the exact same search quality as Supabase, same pgvector HNSW, same pg_trgm fuzzy matching, same tsvector full-text search. No server, no subscription, no API keys needed for keyword search. gbrain init and you're running in 2 seconds.
• Smart init defaults to local. gbrain init now creates a PGLite brain by default. If your repo has 1000+ markdown files, it suggests Supabase for scale. --supabase and --pglite flags let you choose explicitly.
• Migrate between engines anytime. gbrain migrate --to supabase transfers your entire brain (pages, chunks, embeddings, tags, links, timeline) to remote Postgres with manifest-based resume. gbrain migrate --to pglite goes the other way. Embeddings copy directly, no re-embedding needed.
• Pluggable engine factory. createEngine() dynamically loads the right engine from config. PGLite WASM is never loaded for Postgres users.
• Search works without OpenAI. hybridSearch now checks for OPENAI_API_KEY before attempting embeddings. No key = keyword-only search. No more crashes when you just want to search your local brain.
• Your brain gets new senses automatically. Integration recipes teach your agent how to wire up voice calls, email, Twitter, and calendar into your brain. Run gbrain integrations to see what's available. Your agent reads the recipe, asks for API keys, validates each one, and sets everything up. Markdown is code -- the recipe IS the installer.
• Voice-to-brain: phone calls create brain pages. The first recipe: Twilio + OpenAI Realtime voice agent. Call a number, talk, and a structured brain page appears with entity detection, cross-references, and a summary posted to your messaging app. Opinionated defaults: caller screening, brain-first lookup, quiet hours, thinking sounds. The smoke test calls YOU (outbound) so you experience the magic immediately.
• gbrain integrations command. Six subcommands for managing integration recipes: list (dashboard of senses + reflexes), show (recipe details), status (credential checks with direct links to get missing keys), doctor (health checks), stats (signal analytics), test (recipe validation). --json on every subcommand for agent-parseable output. No database connection needed.
• Health heartbeat. Integrations log events to ~/.gbrain/integrations/<id>/heartbeat.jsonl. Status checks detect stale integrations and include diagnostic steps.
• 17 individually linkable SKILLPACK guides. The 1,281-line monolith is now broken into standalone guides at docs/guides/, organized by category. Each guide is individually searchable and linkable. The SKILLPACK index stays at the same URL (backward compatible).
• "Getting Data In" documentation. New docs/integrations/ with a landing page, recipe format documentation, credential gateway guide, and meeting webhook guide. Explains the deterministic collector pattern: code for data, LLMs for judgment.
• Architecture and philosophy docs. docs/architecture/infra-layer.md documents the shared foundation (import, chunk, embed, search). docs/ethos/THIN_HARNESS_FAT_SKILLS.md is Garry's essay on the architecture philosophy with an agent decision guide. docs/designs/HOMEBREW_FOR_PERSONAL_AI.md maps the 10-star vision.

Changed

• Engine interface expanded. Added runMigration() (replaces internal driver access for schema migrations) and getChunksWithEmbeddings() (loads embedding data for cross-engine migration).
• Shared utilities extracted. validateSlug, contentHash, and row mappers moved from postgres-engine.ts to src/core/utils.ts. Both engines share them.
• Config infers engine type. If database_path is set but engine is missing, config now infers pglite instead of defaulting to postgres.
• Import serializes on PGLite. Parallel workers are Postgres-only. PGLite uses sequential import (single-connection architecture).

[0.6.1] - 2026-04-10

Fixed

• Import no longer silently drops files with "..." in the name. The path traversal check rejected any filename containing two consecutive dots, killing 1.2% of files in real-world corpora (YouTube transcripts, TED talks, podcast titles). Now only rejects actual traversal patterns like ../. Community fix wave, 8 contributors.
• Import no longer crashes on JavaScript/TypeScript projects. The file walker crashed on node_modules directories and broken symlinks. Now skips node_modules and handles broken symlinks gracefully with a warning.
• gbrain init exits cleanly after setup. Previously hung forever because stdin stayed open. Now pauses stdin after reading input.
• pgvector extension auto-created during init. No more copy-pasting SQL into the Supabase editor. gbrain init now runs CREATE EXTENSION IF NOT EXISTS vector automatically, with a clear fallback message if it can't.
• Supabase connection string hint matches current dashboard UI. Updated navigation path to match the 2026 Supabase dashboard layout.
• Hermes Agent link fixed in README. Pointed to the correct NousResearch GitHub repo.

Changed

• Search is faster. Keyword search now runs in parallel with the embedding pipeline instead of waiting for it. Saves ~200-500ms per hybrid search call.
• .mdx files are now importable. The import walker, sync filter, and slug generator all recognize .mdx alongside .md.

Added

• Community PR wave process documented in CLAUDE.md for future contributor batches.

Contributors

Thank you to everyone who reported bugs, submitted fixes, and helped make GBrain better:

• @orendi84 — slug validator ellipsis fix (PR #31)
• @mattbratos — import walker resilience + MDX support (PRs #26, #27)
• @changergosum — init exit fix + auto pgvector (PRs #17, #18)
• @eric-hth — Supabase UI hint update (PR #30)
• @irresi — parallel hybrid search (PR #8)
• @howardpen9 — Hermes Agent link fix (PR #34)
• @cktang88 — the thorough 12-bug report that drove v0.6.0 (Issue #22)
• @mvanhorn — MCP schema handler fix (PR #25)

[0.6.0] - 2026-04-10

Added

• Access your brain from any AI client. Deploy GBrain as a serverless remote MCP endpoint on your existing Supabase instance. Works with Claude Desktop, Claude Code, Cowork, and Perplexity Computer. One URL, bearer token auth, zero new infrastructure. Clone the repo, fill in 3 env vars, run scripts/deploy-remote.sh, done.
• Per-client setup guides in docs/mcp/ for Claude Code, Claude Desktop, Cowork, Perplexity, and ChatGPT (coming soon, requires OAuth 2.1). Also documents Tailscale Funnel and ngrok as self-hosted alternatives.
• Token management via standalone src/commands/auth.ts. Create, list, revoke per-client bearer tokens. Includes smoke test: auth.ts test <url> --token <token> verifies the full pipeline (initialize + tools/list + get_stats) in 3 seconds.
• Usage logging via mcp_request_log table. Every remote tool call logs token name, operation, latency, and status for debugging and security auditing.
• Hardened health endpoint at /health. Unauthenticated: 200/503 only (no info disclosure). Authenticated: checks postgres, pgvector, and OpenAI API key status.

Fixed

• MCP server actually connects now. Handler registration used string literals ('tools/list' as any) instead of SDK typed schemas. Replaced with ListToolsRequestSchema and CallToolRequestSchema. Without this fix, gbrain serve silently failed to register handlers. (Issue #9)
• Search results no longer flooded by one large page. Keyword search returned ALL chunks from matching pages. Now returns one best chunk per page via DISTINCT ON. (Issue #22)
• Search dedup no longer collapses to one chunk per page. Layer 1 kept only the single highest-scoring chunk per slug. Now keeps top 3, letting later dedup layers (text similarity, cap per page) do their job. (Issue #22)
• Transactions no longer corrupt shared state. Both PostgresEngine.transaction() and db.withTransaction() swapped the shared connection reference, breaking under concurrent use. Now uses scoped engine via Object.create with no shared state mutation. (Issue #22)
• embed --stale no longer wipes valid embeddings. upsertChunks() deleted all chunks then re-inserted, writing NULL for chunks without new embeddings. Now uses UPSERT (INSERT ON CONFLICT UPDATE) with COALESCE to preserve existing embeddings. (Issue #22)
• Slug normalization is consistent. pathToSlug() preserved case while inferSlug() lowercased. Now validateSlug() enforces lowercase at the validation layer, covering all entry points. (Issue #22)
• initSchema no longer reads from disk at runtime. Both schema loaders used readFileSync with import.meta.url, which broke in compiled binaries and Deno Edge Functions. Schema is now embedded at build time via scripts/build-schema.sh. (Issue #22)
• file_upload actually uploads content. The operation wrote DB metadata but never called the storage backend. Fixed in all 3 paths (operation, CLI upload, CLI sync) with rollback semantics. (Issue #22)
• S3 storage backend authenticates requests. signedFetch() was just unsigned fetch(). Replaced with @aws-sdk/client-s3 for proper SigV4 signing. Supports R2/MinIO via forcePathStyle. (Issue #22)
• Parallel import uses thread-safe queue. queue.shift() had race conditions under parallel workers. Now uses an atomic index counter. Checkpoint preserved on errors for safe resume. (Issue #22)
• redirect verifies remote existence before deleting local files. Previously deleted local files unconditionally. Now checks storage backend before removing. (Issue #22)
• gbrain call respects dry_run. handleToolCall() hardcoded dryRun: false. Now reads from params. (Issue #22)

Changed

• Added @aws-sdk/client-s3 as a dependency for authenticated S3 operations.
• Schema migration v2: unique index on content_chunks(page_id, chunk_index) for UPSERT support.
• Schema migration v3: access_tokens and mcp_request_log tables for remote MCP auth.

[0.5.1] - 2026-04-10

Fixed

• Apple Notes and files with spaces just work. Paths like Apple Notes/2017-05-03 ohmygreen.md now auto-slugify to clean slugs (apple-notes/2017-05-03-ohmygreen). Spaces become hyphens, parens and special characters are stripped, accented characters normalize to ASCII. All 5,861+ Apple Notes files import cleanly without manual renaming.
• Existing brains auto-migrate. On first run after upgrade, a one-time migration renames all existing slugs with spaces or special characters to their clean form. Links are rewritten automatically. No manual cleanup needed.
• Import and sync produce identical slugs. Both pipelines now use the same slugifyPath() function, eliminating the mismatch where sync preserved case but import lowercased.

[0.5.0] - 2026-04-10

Added

• Your brain never falls behind. Live sync keeps the vector DB current with your brain repo automatically. Set up a cron, use --watch, hook into GitHub webhooks, or use git hooks. Your agent picks whatever fits its environment. Edit a markdown file, push, and within minutes it's searchable. No more stale embeddings serving wrong answers.
• Know your install actually works. New verification runbook (docs/GBRAIN_VERIFY.md) catches the silent failures that used to go unnoticed: the pooler bug that skips pages, missing embeddings, stale sync. The real test: push a correction, wait, search for it. If the old text comes back, sync is broken and the runbook tells you exactly why.
• New installs set up live sync automatically. The setup skill now includes live sync (Phase H) and full verification (Phase I) as mandatory steps. Agents that install GBrain will configure automatic sync and verify it works before declaring setup complete.
• Fixes the silent page-skip bug. If your Supabase connection uses the Transaction mode pooler, sync silently skips most pages. The new docs call this out as a hard prerequisite with a clear fix (switch to Session mode). The verification runbook catches it by comparing page count against file count.

[0.4.2] - 2026-04-10

Changed

• All GitHub Actions pinned to commit SHAs across test, e2e, and release workflows. Prevents supply chain attacks via mutable version tags.
• Workflow permissions hardened: contents: read on test and e2e workflows limits GITHUB_TOKEN blast radius.
• OpenClaw CI install pinned to v2026.4.9 instead of pulling latest.

Added

• Gitleaks secret scanning CI job runs on every push and PR. Catches accidentally committed API keys, tokens, and credentials.
• .gitleaks.toml config with allowlists for test fixtures and example files.
• GitHub Actions SHA maintenance rule in CLAUDE.md so pins stay fresh on every /ship and /review.
• S3 Sig V4 TODO for future implementation when S3 storage becomes a deployment path.

[0.4.1] - 2026-04-09

Added

• gbrain check-update command with --json output. Checks GitHub Releases for new versions, compares semver (minor+ only, skips patches), fetches and parses changelog diffs. Fail-silent on network errors.
• SKILLPACK Section 17: Auto-Update Notifications. Full agent playbook for the update lifecycle: check, notify, consent, upgrade, skills refresh, schema sync, report. Never auto-upgrades without user permission.
• Standalone SKILLPACK self-update for users who load the skillpack directly without the gbrain CLI. Version markers in SKILLPACK and RECOMMENDED_SCHEMA headers, with raw GitHub URL fetching.
• Step 7 in the OpenClaw install paste: daily update checks, default-on. User opts into being notified about updates, not into automatic installs.
• Setup skill Phase G: conditional auto-update offer for manual install users.
• Schema state tracking via ~/.gbrain/update-state.json. Tracks which recommended schema directories the user adopted, declined, or added custom. Future upgrades suggest new additions without re-suggesting declined items.
• skills/migrations/ directory convention for version-specific post-upgrade agent directives.
• 20 unit tests and 5 E2E tests for the check-update command, covering version comparison, changelog extraction, CLI wiring, and real GitHub API interaction.
• E2E test DB lifecycle documentation in CLAUDE.md: spin up, run tests, tear down. No orphaned containers.

Changed

• detectInstallMethod() exported from upgrade.ts for reuse by check-update.

Fixed

• Semver comparison in changelog extraction was missing major-version guard, causing incorrect changelog entries to appear when crossing major version boundaries.

[0.4.0] - 2026-04-09

Added

• gbrain doctor command with --json output. Checks pgvector extension, RLS policies, schema version, embedding coverage, and connection health. Agents can self-diagnose issues.
• Pluggable storage backends: S3, Supabase Storage, and local filesystem. Choose where binary files live independently of the database. Configured via gbrain init or environment variables.
• Parallel import with per-worker engine instances. Large brain imports now use multiple database connections concurrently instead of a single serial pipeline.
• Import resume checkpoints. If gbrain import is interrupted, it picks up where it left off instead of re-importing everything.
• Automatic schema migration runner. On connect, gbrain detects the current schema version and applies any pending migrations without manual intervention.
• Row-Level Security (RLS) enabled on all tables with BYPASSRLS safety check. Every query goes through RLS policies.
• --json flag on gbrain init and gbrain import for machine-readable output. Agents can parse structured results instead of scraping CLI text.
• File migration CLI (gbrain files migrate) for moving files between storage backends. Two-way-door: test with --dry-run, migrate incrementally.
• Bulk chunk INSERT for faster page writes. Chunks are inserted in a single statement instead of one-at-a-time.
• Supabase smart URL parsing: automatically detects and converts IPv6-only pooler URLs to the correct connection format.
• 56 new unit tests covering doctor, storage backends, file migration, import resume, slug validation, setup branching, Supabase admin, and YAML parsing. Test suite grew from 9 to 19 test files.
• E2E tests for parallel import concurrency and all new features.

Fixed

• validateSlug now accepts any filename characters (spaces, unicode, special chars) instead of rejecting non-alphanumeric slugs. Apple Notes and other real-world filenames import cleanly.
• Import resilience: files over 5MB are skipped with a warning instead of crashing the pipeline. Errors in individual files no longer abort the entire import.
• gbrain init detects IPv6-only Supabase URLs and adds the required pgvector check during setup.
• E2E test fixture counts, CLI argument parsing, and doctor exit codes cleaned up.

Changed

• Setup skill and README rewritten for agent-first developer experience.
• Maintain skill updated with RLS verification, schema health checks, and nohup hints for large embedding jobs.

[0.3.0] - 2026-04-08

Added

• Contract-first architecture: single operations.ts defines ~30 shared operations. CLI, MCP, and tools-json all generated from the same source. Zero drift.
• OperationError type with structured error codes (page_not_found, invalid_params, embedding_failed, etc.). Agents can self-correct.
• dry_run parameter on all mutating operations. Agents preview before committing.
• importFromContent() split from importFile(). Both share the same chunk+embed+tag pipeline, but importFromContent works from strings (used by put_page). Wrapped in engine.transaction().
• Idempotency hash now includes ALL fields (title, type, frontmatter, tags), not just compiled_truth + timeline. Metadata-only edits no longer silently skipped.
• get_page now supports optional fuzzy: true for slug resolution. Returns resolved_slug so callers know what happened.
• query operation now supports expand toggle (default true). Both CLI and MCP get the same control.
• 10 new operations wired up: put_raw_data, get_raw_data, resolve_slugs, get_chunks, log_ingest, get_ingest_log, file_list, file_upload, file_url.
• OpenClaw bundle plugin manifest (openclaw.plugin.json) with config schema, MCP server config, and skill listing.
• GitHub Actions CI: test on push/PR, multi-platform release builds (macOS arm64 + Linux x64) on version tags.
• gbrain init --non-interactive flag for plugin mode (accepts config via flags/env vars, no TTY required).
• Post-upgrade version verification in gbrain upgrade.
• Parity test (test/parity.test.ts) verifies structural contract between operations, CLI, and MCP.
• New setup skill replacing install: auto-provision Supabase via CLI, AGENTS.md injection, target TTHW < 2 min.
• E2E test suite against real Postgres+pgvector. 13 realistic fixtures (miniature brain with people, companies, deals, meetings, concepts), 14 test suites covering all operations, search quality benchmarks, idempotency stress tests, schema validation, and full setup journey verification.
• GitHub Actions E2E workflow: Tier 1 (mechanical) on every PR, Tier 2 (LLM skills via OpenClaw) nightly.
• docker-compose.test.yml and .env.testing.example for local E2E development.

Fixed

• Schema loader in db.ts broke on PL/pgSQL trigger functions containing semicolons inside $$ blocks. Replaced per-statement execution with single conn.unsafe() call.
• traverseGraph query failed with "could not identify equality operator for type json" when using SELECT DISTINCT with json_agg. Changed to jsonb_agg.

Changed

• src/mcp/server.ts rewritten from ~233 to ~80 lines. Tool definitions and dispatch generated from operations[].
• src/cli.ts rewritten. Shared operations auto-registered from operations[]. CLI-only commands (init, upgrade, import, export, files, embed) kept as manual registrations.
• tools-json output now generated FROM operations[]. Third contract surface eliminated.
• All 7 skills rewritten with tool-agnostic language. Works with both CLI and MCP plugin contexts.
• File schema: storage_url column dropped, storage_path is the only identifier. URLs generated on demand via file_url operation.
• Config loading: env vars (GBRAIN_DATABASE_URL, DATABASE_URL, OPENAI_API_KEY) override config file values. Plugin config injected via env vars.

Removed

• 12 command files migrated to operations.ts: get.ts, put.ts, delete.ts, list.ts, search.ts, query.ts, health.ts, stats.ts, tags.ts, link.ts, timeline.ts, version.ts.
• storage_url column from files table.

[0.2.0.2] - 2026-04-07

Changed

• Rewrote recommended brain schema doc with expanded architecture: database layer (entity registry, event ledger, fact store, relationship graph) presented as the core architecture, entity identity and deduplication, enrichment source ordering, epistemic discipline rules, worked examples showing full ingestion chains, concurrency guidance, and browser budget. Smoothed language for open-source readability.

[0.2.0.1] - 2026-04-07

Added

• Recommended brain schema doc (docs/GBRAIN_RECOMMENDED_SCHEMA.md): full MECE directory structure, compiled truth + timeline pages, enrichment pipeline, resolver decision tree, skill architecture, and cron job recommendations. The OpenClaw paste now links to this as step 5.

Changed

• First-time experience rewritten. "Try it" section shows your own data, not fictional PG essays. OpenClaw paste references the GitHub repo, includes bun install fallback, and has the agent pick a dynamic query based on what it imported.
• Removed all references to data/kindling/ (a demo corpus directory that never existed).

[0.2.0] - 2026-04-05

Added

• You can now keep your brain current with gbrain sync, which uses git's own diff machinery to process only what changed. No more 30-second full directory walks when 3 files changed.
• Watch mode (gbrain sync --watch) polls for changes and syncs automatically. Set it and forget it.
• Binary file management with gbrain files commands (list, upload, sync, verify). Store images, PDFs, and audio in Supabase Storage instead of clogging your git repo.
• Install skill (skills/install/SKILL.md) that walks you through setup from scratch, including Supabase CLI magic path for zero-copy-paste onboarding.
• Import and sync now share a checkpoint. Run gbrain import, then gbrain sync, and it picks up right where import left off. Zero gap.
• Tag reconciliation on reimport. If you remove a tag from your markdown, it actually gets removed from the database now.
• gbrain config show redacts database passwords so you can safely share your config.
• updateSlug engine method preserves page identity (page_id, chunks, embeddings) across renames. Zero re-embedding cost.
• sync_brain MCP tool returns structured results so agents know exactly what changed.
• 20 new sync tests (39 total across 3 test files)

[0.1.0] - 2026-04-05

Added

• Pluggable engine interface (BrainEngine) with full Postgres + pgvector implementation
• 25+ CLI commands: init, get, put, delete, list, search, query, import, export, embed, stats, health, link/unlink/backlinks/graph, tag/untag/tags, timeline/timeline-add, history/revert, config, upgrade, serve, call
• MCP stdio server with 20 tools mirroring all CLI operations
• 3-tier chunking: recursive (delimiter-aware), semantic (Savitzky-Golay boundary detection), LLM-guided (Claude Haiku topic shifts)
• Hybrid search with Reciprocal Rank Fusion merging vector + keyword results
• Multi-query expansion via Claude Haiku (2 alternative phrasings per query)
• 4-layer dedup pipeline: by source, cosine similarity, type diversity, per-page cap
• OpenAI embedding service (text-embedding-3-large, 1536 dims) with batch support and exponential backoff
• Postgres schema with pgvector HNSW, tsvector (trigger-based, spans timeline_entries), pg_trgm fuzzy slug matching
• Smart slug resolution for reads (fuzzy match via pg_trgm)
• Page version control with snapshot, history, and revert
• Typed links with recursive CTE graph traversal (max depth configurable)
• Brain health dashboard (embed coverage, stale pages, orphans, dead links)
• Stale alert annotations in search results
• Supabase init wizard with CLI auto-provision fallback
• Slug validation to prevent path traversal on export
• 6 fat markdown skills: ingest, query, maintain, enrich, briefing, migrate
• ClawHub manifest for skill distribution
• Full design docs: GBRAIN_V0 spec, pluggable engine architecture, SQLite engine plan