* fix: splitBody and inferType for wiki-style markdown content - splitBody now requires explicit timeline sentinel (<!-- timeline -->, --- timeline ---, or --- directly before ## Timeline / ## History). A bare --- in body text is a markdown horizontal rule, not a separator. This fixes the 83% content truncation @knee5 reported on a 1,991-article wiki where 4,856 of 6,680 wikilinks were lost. - serializeMarkdown emits <!-- timeline --> sentinel for round-trip stability. - inferType extended with /writing/, /wiki/analysis/, /wiki/guides/, /wiki/hardware/, /wiki/architecture/, /wiki/concepts/. Path order is most-specific-first so projects/blog/writing/essay.md → writing, not project. - PageType union extended: writing, analysis, guide, hardware, architecture. Updates test/import-file.test.ts to use the new sentinel. Co-Authored-By: @knee5 (PR #187) Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix: JSONB double-encode bug on Postgres + parseEmbedding NaN scores Two related Postgres-string-typed-data bugs that PGLite hid: 1. JSONB double-encode (postgres-engine.ts:107,668,846 + files.ts:254): ${JSON.stringify(value)}::jsonb in postgres.js v3 stringified again on the wire, storing JSONB columns as quoted string literals. Every frontmatter->>'key' returned NULL on Postgres-backed brains; GIN indexes were inert. Switched to sql.json(value), which is the postgres.js-native JSONB encoder (Parameter with OID 3802). Affected columns: pages.frontmatter, raw_data.data, ingest_log.pages_updated, files.metadata. page_versions.frontmatter is downstream via INSERT...SELECT and propagates the fix. 2. pgvector embeddings returning as strings (utils.ts): getEmbeddingsByChunkIds returned "[0.1,0.2,...]" instead of Float32Array on Supabase, producing [NaN] cosine scores. Adds parseEmbedding() helper handling Float32Array, numeric arrays, and pgvector string format. Throws loud on malformed vectors (per Codex's no-silent-NaN requirement); returns null for non-vector strings (treated as "no embedding here"). rowToChunk delegates to parseEmbedding. E2E regression test at test/e2e/postgres-jsonb.test.ts asserts jsonb_typeof = 'object' AND col->>'k' returns expected scalar across all 5 affected columns — the test that should have caught the original bug. Runs in CI via the existing pgvector service. Co-Authored-By: @knee5 (PR #187 — JSONB triple-fix) Co-Authored-By: @leonardsellem (PR #175 — parseEmbedding) Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat: extract wikilink syntax with ancestor-search slug resolution extractMarkdownLinks now handles [[page]] and [[page|Display Text]] alongside standard [text](page.md). For wiki KBs where authors omit leading ../ (thinking in wiki-root-relative terms), resolveSlug walks ancestor directories until it finds a matching slug. Without this, wikilinks under tech/wiki/analysis/ targeting [[../../finance/wiki/concepts/foo]] silently dangled when the correct relative depth was 3 × ../ instead of 2. Co-Authored-By: @knee5 (PR #187) Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * feat: gbrain repair-jsonb + v0.12.1 migration + CI grep guard - New gbrain repair-jsonb command. Detects rows where jsonb_typeof(col) = 'string' and rewrites them via (col #>> '{}')::jsonb across 5 affected columns: pages.frontmatter, raw_data.data, ingest_log.pages_updated, files.metadata, page_versions.frontmatter. Idempotent — re-running is a no-op. PGLite engines short-circuit cleanly (the bug never affected the parameterized encode path PGLite uses). --dry-run shows what would be repaired; --json for scripting. - New v0_12_1.ts migration orchestrator. Phases: schema → repair → verify. Modeled on v0_12_0 pattern, registered in migrations/index.ts. Runs automatically via gbrain upgrade / apply-migrations. - CI grep guard at scripts/check-jsonb-pattern.sh fails the build if anyone reintroduces the ${JSON.stringify(x)}::jsonb interpolation pattern. Wired into bun test via package.json. Best-effort static analysis (multi-line and helper-wrapped variants are caught by the E2E round-trip test instead). - Updates apply-migrations.test.ts expectations to account for the new v0.12.1 entry in the registry. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * chore: bump version and changelog (v0.12.1) Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * docs: update project documentation for v0.12.1 - CLAUDE.md: document repair-jsonb command, v0_12_1 migration, splitBody sentinel contract, inferType wiki subtypes, CI grep guard, new test files (repair-jsonb, migrations-v0_12_1, markdown) - README.md: add gbrain repair-jsonb to ADMIN command reference - INSTALL_FOR_AGENTS.md: fix verification count (6 -> 7), add v0.12.1 upgrade guidance for Postgres brains - docs/GBRAIN_VERIFY.md: add check #8 for JSONB integrity on Postgres-backed brains - docs/UPGRADING_DOWNSTREAM_AGENTS.md: add v0.12.1 section with migration steps, splitBody contract, wiki subtype inference - skills/migrate/SKILL.md: document native wikilink extraction via gbrain extract links (v0.12.1+) Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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GBrain Installation Guide for AI Agents
Read this entire file, then follow the steps. Ask the user for API keys when needed. Target: ~30 minutes to a fully working brain.
Step 1: Install GBrain
git clone https://github.com/garrytan/gbrain.git ~/gbrain && cd ~/gbrain
curl -fsSL https://bun.sh/install | bash
export PATH="$HOME/.bun/bin:$PATH"
bun install && bun link
Verify: gbrain --version should print a version number. If gbrain is not found,
restart the shell or add the PATH export to the shell profile.
Step 2: API Keys
Ask the user for these:
export OPENAI_API_KEY=sk-... # required for vector search
export ANTHROPIC_API_KEY=sk-ant-... # optional, improves search quality
Save to shell profile or .env. Without OpenAI, keyword search still works.
Without Anthropic, search works but skips query expansion.
Step 3: Create the Brain
gbrain init # PGLite, no server needed
gbrain doctor --json # verify all checks pass
The user's markdown files (notes, docs, brain repo) are SEPARATE from this tool repo. Ask the user where their files are, or create a new brain repo:
mkdir -p ~/brain && cd ~/brain && git init
Read ~/gbrain/docs/GBRAIN_RECOMMENDED_SCHEMA.md and set up the MECE directory
structure (people/, companies/, concepts/, etc.) inside the user's brain repo,
NOT inside ~/gbrain.
Step 4: Import and Index
gbrain import ~/brain/ --no-embed # import markdown files
gbrain embed --stale # generate vector embeddings
gbrain query "key themes across these documents?"
Step 4.5: Wire the Knowledge Graph
If the user already had a brain repo (Step 3 imported existing markdown), backfill
the typed-link graph and structured timeline. This populates the links and
timeline_entries tables that future writes will maintain automatically.
gbrain extract links --source db --dry-run | head -20 # preview
gbrain extract links --source db # commit
gbrain extract timeline --source db # dated events
gbrain stats # verify links > 0
For brand-new empty brains, skip this step — auto-link populates the graph as the agent writes pages going forward. There is nothing to backfill yet.
After this step:
gbrain graph-query <slug> --depth 2works (relationship traversal)- Search ranks well-connected entities higher (backlink boost)
- Every future
put_pageauto-creates typed links and reconciles stale ones
If a user has a very large brain (>10K pages), extract --source db is idempotent
and supports --since YYYY-MM-DD for incremental runs.
Step 5: Load Skills
Read ~/gbrain/skills/RESOLVER.md. This is the skill dispatcher. It tells you which
skill to read for any task. Save this to your memory permanently.
The three most important skills to adopt immediately:
-
Signal detector (
skills/signal-detector/SKILL.md) — fire this on EVERY inbound message. It captures ideas and entities in parallel. The brain compounds. -
Brain-ops (
skills/brain-ops/SKILL.md) — brain-first lookup on every response. Check the brain before any external API call. -
Conventions (
skills/conventions/quality.md) — citation format, back-linking iron law, source attribution. These are non-negotiable quality rules.
Step 6: Identity (optional)
Run the soul-audit skill to customize the agent's identity:
Read skills/soul-audit/SKILL.md and follow it.
This generates SOUL.md (agent identity), USER.md (user profile), ACCESS_POLICY.md (who sees what), and HEARTBEAT.md (operational cadence) from the user's answers.
If skipped, minimal defaults are installed automatically.
Step 7: Recurring Jobs
Set up using your platform's scheduler (OpenClaw cron, Railway cron, crontab):
- Live sync (every 15 min):
gbrain sync --repo ~/brain && gbrain embed --stale - Auto-update (daily):
gbrain check-update --json(tell user, never auto-install) - Dream cycle (nightly): read
docs/guides/cron-schedule.mdfor the full protocol. Entity sweep, citation fixes, memory consolidation. This is what makes the brain compound. Do not skip it. - Weekly:
gbrain doctor --json && gbrain embed --stale
Step 8: Integrations
Run gbrain integrations list. Each recipe in ~/gbrain/recipes/ is a self-contained
installer. It tells you what credentials to ask for, how to validate, and what cron
to register. Ask the user which integrations they want (email, calendar, voice, Twitter).
Verify: gbrain integrations doctor (after at least one is configured)
Step 9: Verify
Read docs/GBRAIN_VERIFY.md and run all 7 verification checks. Check #4 (live sync
actually works) is the most important.
Upgrade
cd ~/gbrain && git pull origin main && bun install
gbrain init # apply schema migrations (idempotent)
gbrain post-upgrade # show migration notes for the version range
Then read ~/gbrain/skills/migrations/v<NEW_VERSION>.md (and any intermediate
versions you skipped) and run any backfill or verification steps it lists. Skipping
this is how features ship in the binary but stay dormant in the user's brain.
For v0.12.0+ specifically: if your brain was created before v0.12.0, run
gbrain extract links --source db && gbrain extract timeline --source db to
backfill the new graph layer (see Step 4.5 above).
For v0.12.2+ specifically: if your brain is Postgres- or Supabase-backed and
predates v0.12.2, the v0_12_2 migration runs gbrain repair-jsonb
automatically during gbrain post-upgrade to fix the double-encoded JSONB
columns. PGLite brains no-op. If wiki-style imports were truncated by the old
splitBody bug, run gbrain sync --full after upgrading to rebuild
compiled_truth from source markdown.