skillify
Best for Skill maintainersWorks with GitHubLow risk
⌘source
- author
@garrytan- repo
- garrytan/gbrain
- language
- TypeScript
★9.1kstars
1kforks
Apr 18, 2026
✦overview.md
Key Features
- ·Validates skill completeness against 10-item checklist
- ·Checks for proper skill file structure with YAML frontmatter
- ·Verifies unit and integration test coverage
- ·Ensures LLM evals are present for LLM-based features
- ·Confirms resolver trigger patterns are properly registered
Use Cases
- →Validating newly created features before deployment
- →Auditing existing skills for completeness
- →Ensuring consistent skill quality across a codebase
- →Preparing features for agent visibility and execution
Best for
- ✓Skill maintainers
- ✓Quality assurance workflows
- ✓Development teams adopting skill-based architecture
Not ideal for
- !One-off scripts without skill infrastructure
- !Features not intended for agent execution
FAQs
name
skillify
description
The meta skill. Turn any raw feature or script into a properly-skilled,
tested, resolvable, evaled unit of agent-visible capability. Use when
the user says "skillify this", "is this a skill?", "make this proper",
or after a new feature is built without the full skill infrastructure.
Paired with `gbrain check-resolvable`, skillify gives a user-controllable
equivalent of Hermes' auto-skill-creation: you build, skillify checks the
checklist, check-resolvable verifies nothing is orphaned. The human keeps
judgment; the tooling keeps the checklist honest.
version:1.0.0
triggers:["skillify this","skillify","is this a skill?","make this proper","add tests and evals for this","check skill completeness"]
tools:["search","list_pages"]
mutating:false
Skillify — The Meta Skill
Contract
A feature is "properly skilled" when all ten checklist items are present:
SKILL.md— skill file with YAML frontmatter, triggers, contract, phases.- Code — deterministic script if applicable.
- Unit tests — cover every branch of deterministic logic.
- Integration tests — exercise live endpoints, not just in-memory shape.
- LLM evals — quality/correctness cases if the feature includes any LLM call.
- Resolver trigger —
skills/RESOLVER.mdentry with the trigger patterns the user actually types. - Resolver trigger eval — test that feeds trigger phrases to the resolver and asserts they route to this skill, not the old pre-skillify path.
- Check-resolvable —
gbrain check-resolvablepasses (skill is reachable, MECE against its siblings, no DRY violations). - E2E test — exercises the full pipeline from user turn to side effect.
- Brain filing — if the feature writes brain pages,
brain/RESOLVER.mdhas an entry for the directory so the pages aren't orphaned.
Trigger
- "skillify this" / "skillify" / "is this a skill?" / "make this proper"
- "add tests and evals for this"
$install
1-click copynpx skills add garrytan/gbrain --skill skillifySafety assessment
★
Clarity score
How clear and easy to understand the SKILL.md instructions are, rated from 1 to 5.
1/ 5
poorThe SKILL.md content is hard to understand and quite ambiguous.
◎
Actionability score
How directly an agent can act on the SKILL.md instructions, rated from 1 to 5.
1/ 5
not actionableThe SKILL.md is hard to act on; an agent would not know what to do.