Manage, inventory, standardize, migrate, and test reusable Codex skills for the MetaSkill repository. Use when Codex needs to inspect local skills, convert a personal workflow into a public skill candidate, normalize skill folder shape, plan skill promotion, or decide whether a skill belongs in skill-management, publication-review, or skill-examples.
Installs into .claude/skills of the current project.
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---
name: skill-management
description: Manage, inventory, standardize, migrate, and test reusable Codex skills for the MetaSkill repository. Use when Codex needs to inspect local skills, convert a personal workflow into a public skill candidate, normalize skill folder shape, plan skill promotion, or decide whether a skill belongs in skill-management, publication-review, or skill-examples.
---
# Skill Management
## Overview
Use this skill to turn useful local skill workflows into public, reusable, and testable skill packages. For publish-before-review privacy and contract checks, use `publication-review/`.
## Workflow
1. Identify the task type.
- Use `skill-management/` for inventory, audit, standards, tests, migration, and publishing workflows.
- Use `publication-review/` for final public-safety, structure, and truthful-contract checks before publication.
- Use `skill-examples/<skill-name>/` for mature reusable skills and public-safe examples.
2. Inspect the candidate skill or workflow.
- Read `SKILL.md`, `agents/openai.yaml`, and directly referenced resources.
- Search for private paths, user identifiers, unpublished content, account details, and local-only assumptions.
3. Normalize the public contract.
- Keep only implemented behavior in the trigger description and body.
- Mark unsupported behavior as manual, optional, or out of scope.
- Replace private examples with generic fixtures.
4. Validate structure and metadata.
- Ensure the folder name is lowercase hyphen-case.
- Ensure frontmatter follows the system `skill-creator` validator; `name` and `description` are required.
- Ensure optional resources are actually used.
- Ensure reusable `skill-examples/` skills include `install.md` with copy,
dependencies, install, update, verification, rollback, and notes sections.
- Ensure required companion skills, CLIs, app connectors, and bundled scripts
are explicit enough for a post-install agent check.
- Ensure installed path examples resolve from `$CODEX_HOME/skills`, with
`~/.codex/skills` as the fallback when `CODEX_HOME` is unset.
5. Record the result.
- Update collection-level documentation when a new category or convention is introduced.
- Avoid adding per-skill README files unless explicitly required by the repository owner.
## Standard Skill Shape
A public skill should normally look like:
```text
skill-name/
SKILL.md
install.md
agents/openai.yaml
references/
scripts/
assets/
```
Only keep optional directories that serve the skill. Delete scaffold placeholders.
## Validation Commands
When the system skill-creator utilities are available, validate a skill with:
```powershell
uv run --with pyyaml python .\skill-examples\skill-creator\scripts\quick_validate.py .\skill-management
```
If the repository sample is unavailable, use an installed `skill-creator` validator without committing machine-specific absolute paths.
For skill examples, also run the installation smoke checker in source mode:
```powershell
python .\scripts\validate_muxing_install.py --source-only --skill deepseek-agent
```
## Output Expectations
- For audits, report blocking publication issues first.
- For migrations, list changed files and any behavior intentionally omitted.
- For publication-readiness validation, delegate to `publication-review/` and distinguish structural validation from real-world forward testing.
- For public README updates, keep the repository purpose broad and avoid private context.