Agent skill

Schema Unify

by garrytan in garrytan/gbrain

Migrate a brain from gbrain-base (or any pack) to gbrain-base-v2's 14-canonical-type taxonomy via gbrain onboard --check + the unify-types Minion handler.

MITAuto-check passed

Install Schema Unify

skills CLI
$ npx skills add garrytan/gbrain --skill schema-unify -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install garrytan/gbrain schema-unify --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/garrytan/gbrain.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/schema-unify .claude/skills/schema-unify && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
schema-unify
GitHub stars
31k
Token cost
~3.4k tokens
SKILL.md length
1,345 words
Files
1
Skills in repo
47
Repo updated
First seen
Licence
MIT

At a glance

Migrate a brain from gbrain-base (or any pack) to gbrain-base-v2's 14-canonical-type taxonomy via gbrain onboard --check + the unify-types Minion handler.

  • Works in 5 steps: Discovery → Preview → Apply → …
  • An agent notices packupgradeavailable
  • SKILL.md covers brain_first: exempt, When this skill fires, Mental model (one paragraph) and Workflow, plus 8 more sections
  • Calls jq

What it does

Schema Unify is an agent skill from garrytan/gbrain. Migrate a brain from gbrain-base (or any pack) to gbrain-base-v2's 14-canonical-type taxonomy via gbrain onboard --check + the unify-types Minion handler. Collapses 94 noisy types to 15 canonical with subtypes, alias rows, and link rows. Triggers when an agent notices packupgradeavailable, typeproliferation, or asks "what is the canonical taxonomy / how do I clean up my page types".

Its SKILL.md is about 3.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: Garry's Opinionated OpenClaw/Hermes Agent Brain. The licence is MIT.

When your agent uses it

  • An agent notices packupgradeavailable
  • Typeproliferation
  • Asks what is the canonical taxonomy / how do I clean up my page types

Example prompts

  • “what is the canonical taxonomy / how do I clean up my page types”
  • “/schema-unify”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Discovery
  2. Preview
  3. Apply
  4. Verify
  5. Post-migration

What it can do on your machine

Read from SKILL.md and the folder at commit fc54831. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • jq

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Schema Unify loads about 3.4k tokens when it runs. Until then it costs about 100 tokens; SKILL.md has 1,345 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~100
When it runs · the whole SKILL.md, loaded when a task matches
~3.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from garrytan/gbrain at commit fc54831, republished under its MIT licence (© garrytan). 1,345 words, ~3,416 tokens.

Download SKILL.mdSave it as .claude/skills/schema-unify/SKILL.md (or your agent's skills folder).
name
schema-unify
description
Migrate a brain from gbrain-base (or any pack) to gbrain-base-v2's 14-canonical-type taxonomy via gbrain onboard --check + the unify-types Minion handler. Collapses 94 noisy types to 15 canonical with subtypes, alias rows, and link rows. Triggers when an agent notices pack_upgrade_available, type_proliferation, or asks "what is the canonical taxonomy / how do I clean up my page types".
brain_first
exempt
tools
gbrain onboard --check, gbrain onboard --check --explain, gbrain onboard --check --json, gbrain jobs submit unify-types, gbrain jobs get, gbrain schema…
triggers
unify my types, migrate to gbrain-base-v2, 94 types to 14, apply canonical taxonomy, clean up my page types, pack upgrade, shrink type proliferation, what…

Schema Unification (gbrain-base → gbrain-base-v2)

v0.41.22 ships gbrain-base-v2 — a 15-type DRY/MECE taxonomy (14 canonical + note catch-all) — as the install default for new brains. Existing brains on gbrain-base can opt in via the pack_upgrade_available onboard finding + the unify-types PROTECTED Minion handler.

This skill is the playbook for that migration.

brain_first: exempt

This skill is ABOUT the brain's shape — it can't depend on the brain it's reshaping. No gbrain search lookup first; jump straight to onboard.

When this skill fires

  • Agent runs gbrain onboard --check and sees pack_upgrade_available or type_proliferation warnings
  • User asks "what is the canonical taxonomy / how do I clean up my page types / migrate to v2"
  • A dangling_aliases finding surfaces (post-unify GC)
  • An agent ingesting from a custom pack wants to consult the v2 taxonomy as a reference

Mental model (one paragraph)

A production gbrain brain accreted 94 distinct pages.type values over years of ingestion: tweet / tweet-thread / tweet-bundle / tweet-single / media/x-tweet/bundle / tweet-stub all coexisting; 5.5K concept-redirect pages; atom-partner-link pages that should be links; civic / framework / insight / memo / anecdote one-offs. The cure: collapse to 15 canonical types (person, company, media, tweet, social-digest, analysis, atom, concept, source, deal, email, slack, writing, project, note) with subtypes/format/origin pushed to frontmatter, alias-rows for redirects, real link-rows for edge-shaped pages, and a catch-all that bins long-tail unknowns to note with frontmatter.legacy_type = <original> for rollback.

Workflow

Phase 1: Discovery

Confirm the brain is actually on gbrain-base (not already on v2).

bash
gbrain schema active --json | jq -r '.identity'

Expected: gbrain-base@1.0.0+<sha>. If you see gbrain-base-v2@..., the brain is already on v2 — skip the migration.

Then run onboard to see what would change:

bash
gbrain onboard --check

Look for the pack_upgrade_available finding. If it's ok, there's no successor declared for the active pack — done.

Phase 2: Preview

Run the per-cluster narrative:

bash
gbrain onboard --check --explain

This invokes the unify-types handler in dry-run mode and prints:

  • How many pages would retype per cluster (tweets, articles, companies, etc.)
  • How many concept-redirect pages would become alias rows
  • How many edge-shaped pages would convert to real links
  • The synthesized catch-all rules for unknown types

Review the output. If the proposed changes look wrong, don't proceed — file an issue or write a custom pack with adjusted mapping_rules.

Phase 3: Apply

Managed brains: stop after the preview. Applying the migration is not supported on a managed brain (managed persistence on) yet: the retype writes pages directly instead of through the coordinated writer, so the apply job is refused (writer_coordinator_required) before it changes anything. The pack_upgrade_available finding says so on those brains. Keep using gbrain onboard --check --explain to preview, tell the user the pack upgrade waits for coordinated retype support, and don't submit the apply job below. One exception: when the preview shows nothing to retype, link or alias, the apply job only switches the active pack, so it may be submitted with the user's agreement.

The handler is PROTECTED (manual_only) — autopilot will never auto-fire it. Submit explicitly:

bash
gbrain jobs submit unify-types \
  --params '{"target_pack":"gbrain-base-v2","apply":true}'

On PGLite (the install default), or on any setup without a running gbrain jobs work worker or supervisor daemon, add --follow so the job executes inline:

bash
gbrain jobs submit unify-types \
  --follow \
  --params '{"target_pack":"gbrain-base-v2","apply":true}'

The persistent worker daemon is Postgres-only. Without --follow on PGLite, the job sits queued forever and the migration never runs.

apply defaults to false (dry-run) per the handler contract, so "apply":true is required here or the job reports success having retyped nothing and left the active pack unflipped. Omit it to preview.

Watch progress per phase (worker-daemon runs; with --follow the same progress streams inline):

bash
gbrain jobs get <job_id>      # one job: status, progress, result
gbrain jobs watch --follow    # live dashboard of the whole queue

A job that stays queued here means no worker is running; resubmit with --follow to execute it inline.

On a 186K-page brain expect ~10 minutes. The handler runs:

  1. Preflight (validate target pack has mapping_rules:)
  2. Stats snapshot (pre-state for celebration summary)
  3. Acquire gbrain-unify db-lock (60min TTL)
  4. Apply phases:
    • Explicit retype rules (tweets, articles, companies, etc.)
    • Catch-all retype (unknown types → note with legacy_type)
    • Page-to-link rules (atom-partner-link, symlink)
    • Page-to-alias rules (concept-redirect)
  5. Final sync (untyped rows by path-prefix)
  6. Flip active pack to gbrain-base-v2
  7. Verify + celebration summary
Phase 4: Verify
bash
gbrain onboard --check
gbrain schema stats

Expected:

  • pack_upgrade_available → ok (active pack is now v2)
  • type_proliferation → ok (≤16 distinct typed values)
  • dangling_aliases → ok (slug_aliases all point at active canonicals)
  • gbrain schema stats shows ≤16 distinct types
Phase 5: Post-migration

Search and query --type article keep returning those pages post-unify: media declares article as an alias, so the type filter expands through the active pack's alias closure (the results also include other media pages). Direct SQL against pages.type needs updating to the canonical types.

Search queries get a small ranking signal: pages reached via slug_aliases (canonicals of one or more aliases) get a 1.05x boost. Visible via gbrain search --explain.

Rollback

Every retyped page preserves frontmatter.legacy_type = <original>.

Restore types in bulk (Postgres/Supabase deployments only; requires direct DB access):

sql
UPDATE pages SET type = frontmatter->>'legacy_type'
WHERE source_id = 'default' AND frontmatter->>'legacy_type' IS NOT NULL;

On PGLite there is no SQL shell, so use the CLI surface instead: frontmatter.legacy_type persists per page, so individual retypes can be reverted through the normal put_page/CLI surface, and the soft-delete restore and pack-flip revert below work on every engine.

Page-to-alias and page-to-link source pages soft-delete with 72h TTL. Restore within that window:

bash
gbrain restore <slug>

Revert the active pack flip:

bash
gbrain schema use gbrain-base
Show full SKILL.md (518 more words)Show less

Anti-patterns

  • Don't run unify-types under autopilot. It's manual_only by design. Autopilot remediation should never silently change your taxonomy.
  • Don't expect mapping_rules to cover every legacy type explicitly. Use the catch-all (*unknown*) for the long tail. Pages get retyped to note with legacy_type preserved.
  • Don't rewrite body-text wikilinks. The slug_aliases table IS the resolver. [[old-redirect-slug]] keeps working via engine.resolveSlugWithAlias short-circuit.
  • Don't bypass the dry-run. Always run --explain before applying. The trust delta is real.
  • Don't run two unify jobs concurrently. The gbrain-unify db-lock serializes them; the second submission rejects with "already in progress."

Decision tree

Active pack already gbrain-base-v2?
  → Skip migration.

Custom pack with own mapping_rules?
  → Run --check --explain to see if your pack declares migration_from
    for the active pack. If yes, target_pack = your pack name.

Brain has many custom types not covered by gbrain-base-v2 mapping_rules?
  → The catch-all retype binds them to `note` with legacy_type preserved.
    Review by inspecting frontmatter.legacy_type after the migration.

Federated brain (multiple sources)?
  → Add --params source_id to scope the migration per-source. Each
    source can be migrated independently.

Worried about a specific cluster's mapping?
  → Fork gbrain-base-v2 (`gbrain schema fork gbrain-base-v2 my-pack`),
    edit mapping_rules in your fork, then target the fork.

Contract

Inputs:

  • A brain on gbrain-base (or any pack with migration_from: gbrain-base-v2).
  • Trusted local CLI access on the brain host: gbrain jobs submit grants the PROTECTED-handler opt-in itself for protected names; the remote MCP submit_job op cannot.
  • ~10 min wallclock on a 186K-page brain.

Outputs:

  • Pages retyped to canonical types with frontmatter.legacy_type preserved (per-page rollback signal).
  • slug_aliases rows for concept-redirect pages (alias table IS the resolver — no link rewrite).
  • Real links rows for edge-shaped pages (atom-partner-link, symlink, etc.).
  • Active pack flipped to gbrain-base-v2 atomically at end of successful run.

Side effects:

  • Source pages soft-deleted with 72h restore TTL (gbrain restore <slug>).
  • One-time cache invalidation on KNOBS_HASH_VERSION bump (5→6); self-healing in cache.ttl_seconds.
  • Search/query --type X expands through the active pack's alias closure (back-compat).

Failure modes:

  • Concurrent submission rejected by the gbrain-unify db-lock; second call exits gracefully.
  • Catch-all retype excludes page_to_link + page_to_alias source types (caught in E2E pre-merge).
  • Phase failures abort the run before active_pack_flipped; partial state restorable via op_checkpoint resume.

When it fails

Follow the agent operator protocol for any gbrain error code, exit code, [AGENT] block or notice block. Specific to this skill:

  • A second unify submission is rejected because the gbrain-unify lock is held ("already in progress"): wait for the running job (gbrain jobs get <id>); do not resubmit.
  • A phase fails before active_pack_flipped: the pack did not change; resume from the checkpoint rather than restarting from scratch.
  • The run reports a cost line: retyping can call a model, so confirm the budget with the user before submitting on a large brain.

Anti-Patterns

DON'T:

  • Submit unify-types via the remote MCP submit_job op. PROTECTED handlers require trusted local callers (gbrain jobs submit on the brain host); remote MCP rejection is the intentional trust boundary.
  • Edit mapping_rules in gbrain-base-v2.yaml to skip clusters you don't trust. Fork the pack instead (gbrain schema fork) so the source-of-truth migration stays consistent across brains.
  • Run unify-types from inside an autopilot tick. The check is manual_only — autopilot deliberately never auto-fires it because pack upgrades are one-time consenting taxonomy decisions.
  • Hard-delete soft-deleted source pages before the 72h restore window. Use gbrain restore <slug> first if rollback is needed.
  • Assume frontmatter.legacy_type survives every roundtrip. The marker is canonical for the immediate post-migration window; downstream re-imports may overwrite it.

Output Format

Per phase, the handler emits to stderr:

[unify-types] phase=retype-explicit applied=N skipped=M  cost=USD  ttl=Ns
[unify-types] phase=retype-catch-all applied=N
[unify-types] phase=page-to-link converted=N pages soft-deleted
[unify-types] phase=page-to-alias aliased=N pages soft-deleted
[unify-types] phase=sync residual=N
[unify-types] active_pack flipped from gbrain-base to gbrain-base-v2

Final celebration summary to stderr:

═══════════════════════════════════════════════════════════
  gbrain-base-v2 migration complete
═══════════════════════════════════════════════════════════
  Before: 94 distinct page types
  After:  15 canonical types
  Retyped:      25,632 pages
  Aliased:       5,521 redirects → slug_aliases table
  Linkified:        65 ghost pages → real link rows
  Soft-deleted:  5,586 pages (restorable for 72h)
═══════════════════════════════════════════════════════════

For structured JSON, gbrain call get_job '{"id": <id>}' returns the job row; its result field carries the UnifyTypesResult shape with per_phase, pack_identity_after, active_pack_flipped (gbrain jobs get <id> prints the same result inline).

Reference

© garrytan, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/schema-unify of garrytan/gbrain.

Open the folder on GitHubat commit fc54831

Compare with similar skills

Schema Unify next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Schema Unify this skillgarrytan/gbrain31k—~3.4kAutomated safety check: PassMIT
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Database Migrationsaffaan-m/ECC276k4 repos~3kAutomated safety check: PassMIT
Database Migrationsaffaan-m/ECC276k1 repos~2.4kAutomated safety check: PassMIT
Safe Database Migration Patternsaffaan-m/ECC276k—~3.3kAutomated safety check: PassMIT
gbrain Syncgarrytan/gstack136k—~15kAutomated safety check: NotesMIT

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Questions about Schema Unify

What does Schema Unify do?

Migrate a brain from gbrain-base (or any pack) to gbrain-base-v2's 14-canonical-type taxonomy via gbrain onboard --check + the unify-types Minion handler. Schema Unify is an agent skill from garrytan/gbrain. Migrate a brain from gbrain-base (or any pack) to gbrain-base-v2's 14-canonical-type taxonomy via gbrain onboard --check + the unify-types Minion handler.

When should I use Schema Unify?

Schema Unify fits situations like: an agent notices packupgradeavailable; typeproliferation; asks what is the canonical taxonomy / how do I clean up my page types.

How do I install Schema Unify in Claude Code?

Run `npx skills add garrytan/gbrain --skill schema-unify -a claude-code`. Or copy the skill folder (skills/schema-unify in garrytan/gbrain) into .claude/skills/schema-unify in your project. Claude Code loads it when a task matches its description.

How do I install Schema Unify in Codex?

Run `npx skills add garrytan/gbrain --skill schema-unify -a codex`. Or copy the skill folder (skills/schema-unify in garrytan/gbrain) into .agents/skills/schema-unify in your project. Codex loads it when a task matches its description.

Can I use Schema Unify in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add garrytan/gbrain --skill schema-unify -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/schema-unify, .gemini/skills/schema-unify, .github/skills/schema-unify and .opencode/skills/schema-unify in your project.

What does Schema Unify need to run?

Going by SKILL.md and its folder, Schema Unify needs the command-line tools its instructions call (jq).

Does Schema Unify access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Schema Unify safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Schema Unify use?

Schema Unify is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Schema Unify use?

About 3.4k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Schema Unify?

Skills that share tags, products or a category with Schema Unify: Reversible Migration (JuliusBrussee/caveman, 111k stars), Database Migrations (affaan-m/ECC, 276k stars), Database Migrations (affaan-m/ECC, 276k stars) and Safe Database Migration Patterns (affaan-m/ECC, 276k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Schema Unify?

garrytan (a GitHub user) maintains it in garrytan/gbrain, which has 30,701 GitHub stars. The repository holds 47 skills in this directory. The repository was last updated on October 9, 2026.

Source: garrytan/gbrain on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.