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Skillsskill-creator

skill-creator

Agents & models

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Updated 10-15 08:28

About this skill

Skill Creator

Use this as the canonical lifecycle skill for agent skills in /Users/dobby/GitHub/agents. It absorbs the old skill-router role: placement decisions, registry ownership, creation, promotion, refresh, sync, and validation belong in one workflow.

Scope

  • Apply /Users/dobby/GitHub/agents/AGENTS.md first when working in this repo.
  • If the current repo is not /Users/dobby/GitHub/agents, decide placement and list exact control-plane changes unless the user explicitly asked to edit the agents repo.
  • Edit canonical sources, not generated runtime symlinks under .agents/skills, .claude/skills, or ~/.agents/skills.
  • Keep skills/registry.json as the only mapping manifest.

Read References

  • Read references/skill_design.md before writing a substantial new SKILL.md, choosing bundled resources, splitting references, or reviewing skill quality.
  • Read references/control_plane_lifecycle.md when updating skills/registry.json, importing an external skill, promoting repo-local skills, or choosing exact bootstrap/check commands.
  • Read references/openai_yaml.md before creating or updating agents/openai.yaml.

Placement Decision

Choose placement before creating or editing files:

  1. Use external when the source is upstream and should remain refreshable.
  2. Use owned when the skill is authored locally and should be reusable across one or more repos.
  3. Use repo-local when the skill is specific to one repo and should stay in that repo.
  4. Use managed scope: dormant when the source should stay tracked but should not be linked into any runtime.
  5. Default to the narrowest useful scope. Prefer scope: repo or dormant over global unless the skill clearly belongs in the small default kit for unrelated repos.
  6. When a skill depends on a repo-level MCP preset, align the repo-scoped skill targets with repos declaring that preset in codex/config/repo-bootstrap.json.
  7. If placement is still ambiguous after inspecting context, ask one question: "Should this be external, owned, repo-local, or dormant?"

Standard Workflow

  1. Understand the intended use with concrete examples. Skip only when the usage pattern is already clear from the request or existing skill.
  2. Route placement using the decision rules above.
  3. For substantial or fragile skills, define 2-3 realistic evaluation prompts before writing extensive instructions.
  4. Plan reusable resources: scripts for deterministic/repeated operations, references for context that should load only when needed, and assets for output files/templates.
  5. Create or edit the canonical skill source.
  6. Generate or update agents/openai.yaml.
  7. Validate the skill folder.
  8. Update registry/distribution when the skill is managed by this repo.
  9. Run the required bootstrap/check commands.
  10. Iterate from real use and update durable instructions when the skill exposes a repeatable gap.

Creating Managed Owned Skills

For new owned skills in this repo, scaffold under /Users/dobby/GitHub/agents/skills-source/owned:

python3 /Users/dobby/GitHub/agents/skills-source/owned/skill-creator/scripts/init_skill.py <skill-name> --path /Users/dobby/GitHub/agents/skills-source/owned

Use --resources scripts,references,assets only for resource directories the skill actually needs. Use --examples only when placeholder examples help and delete any placeholders before finishing.

After scaffolding:

  • Replace TODOs in SKILL.md.
  • Add only useful scripts, references, or assets.
  • Test added scripts by running them.
  • Generate agents/openai.yaml with explicit interface values.
  • Validate with scripts/quick_validate.py.
  • Add a managed owned registry entry with the narrowest useful scope.
  • Run bootstrap/check.

Updating Existing Skills

  • Preserve the skill name unless the user asked for a rename.
  • Keep frontmatter to exactly name and description.
  • Put all trigger/use information in the frontmatter description; the body loads only after the skill triggers.
  • Keep SKILL.md lean. Move detailed variants, schemas, examples, and long policy into directly linked files under references/.
  • Keep information in one place; do not duplicate detailed guidance between SKILL.md and references.
  • Regenerate agents/openai.yaml when the skill's scope or user-facing behavior changes.
  • Run validation after edits.

Importing External Skills

When the user gives a skills.sh URL or upstream reference and no special handling is needed, prefer the canonical bootstrap helper:

cd /Users/dobby/GitHub/agents
./scripts/bootstrap-skill.sh <skills.sh-url-or-upstream-ref> --repo <repo> --apply

Use managed external entries only for skills that should remain refreshable from upstream. If an imported skill becomes local infrastructure or intentionally drifts, adopt it into skills-source/owned/<skill> and change upstream_ref to "-".

Repo-Local and Promotion

  • Keep a skill repo-local at <repo>/.agents/skills/<skill> when it is specific to one repo.
  • Record repo-local skills in unmanaged_repo_local_skills for visibility.
  • Promote a repo-local skill to managed owned when it becomes reusable or needs central distribution.
  • For repo-scoped managed skills, prefer scope: repo first and use global only when it belongs in the small default kit.

Registry and Distribution

When skills/registry.json changes, run sync/check in the same change:

cd /Users/dobby/GitHub/agents
./scripts/bootstrap-machine-agent-control-planes.sh --apply
./scripts/check-fast.sh

Use scoped bootstrap/check only when intentionally limiting a repo-scoped run:

cd /Users/dobby/GitHub/agents
./scripts/bootstrap-machine-agent-control-planes.sh --apply --repo <repo-root>
./scripts/check-agent-control-planes.sh --repo <repo-root>

If bootstrap creates tracked repo-local links, stage those generated links with the canonical skill source and registry change. Do not stage unrelated session-memory or work-in-progress files merely because lifecycle hooks touched them.

Validation Commands

Validate a single skill:

python3 /Users/dobby/GitHub/agents/skills-source/owned/skill-creator/scripts/quick_validate.py /path/to/skill-folder

The bundled Python scripts require PyYAML for YAML parsing. If import yaml fails, install or repair the local Python dependency before changing the script behavior.

Regenerate OpenAI UI metadata:

python3 /Users/dobby/GitHub/agents/skills-source/owned/skill-creator/scripts/generate_openai_yaml.py /path/to/skill-folder --interface display_name="..." --interface short_description="..." --interface default_prompt="Use $skill-name to ..."

Safety Rules

  • Do not hand-edit rendered runtime links or generated repo-local control-plane surfaces.
  • Do not add README, changelog, installation guide, or other auxiliary docs to a skill unless the user explicitly asks; skills should contain only what agents need to do the job.
  • Do not add compatibility shims or legacy fallbacks unless explicitly required.
  • Keep temporary artifacts under the owning repo's tmp/ directory and remove disposable scratch files before finishing.