nima-skill-creator

# Nima Skill Creator Treat skill creation as workflow design, not just file formatting. ## Start Here 1. Ground the skill in 2-4 concrete user requests before writing structure. 2. Choose the simplest fitting pattern from [design-patterns.md](references/design-patterns.md). 3. Create only the resources that remove repeated work: `scripts/`, `references/`, `assets/`, and optionally `agents/openai.yaml`. 4. Keep `SKILL.md` procedural and concise. Move deep detail into `references/`. 5. Validate before packaging. Do not create the skill body until the trigger examples, outputs, and reusable resources are clear. ## Phase 1: Discovery Gate Run this phase first. Do not jump into implementation until the gaps below are resolved. Capture: - What inputs the future skill must handle. - What outputs it must reliably produce. - What a user would actually say to trigger it. - Whether the skill is new or an update to an existing folder. Ask in Chinese when the user is exploring requirements. Keep it short and concrete. Use the prompts in [interaction-guide.md](references/interaction-guide.md) if the request is underspecified. Before moving on, summarize: - Primary job of the skill. - Trigger phrases or task shapes. - Constraints or quality bar. - Target directory. ## Phase 2: Pattern Selection Choose one primary pattern, then add a secondary pattern only if it removes ambiguity. - Use [design-patterns.md](references/design-patterns.md) to map the request to `tool-wrapper`, `generator`, `reviewer`, `inversion`, or `pipeline`. - Use `inversion` when the agent must collect structured context before acting. - Use `generator` when output shape must stay consistent. - Use `reviewer` when evaluation criteria should live in a checklist. - Use `pipeline` when steps must happen in order with explicit checkpoints. - Use `tool-wrapper` when the main value is on-demand domain guidance. For most skill-creation requests, combine: - `inversion` for discovery - `generator` for scaffolding - `reviewer` for validation - `pipeline` for the overall sequence ## Phase 3: Resource Planning Translate the examples into reusable artifacts. - Put deterministic automation in `scripts/`. - Put long-lived, load-on-demand guidance in `references/`. - Put templates or starter files in `assets/`. Use [best-practices.md](references/best-practices.md) to tighten naming, frontmatter, and progressive disclosure. Use [workflows.md](references/workflows.md) to shape staged skills with gates. Avoid: - Auxiliary docs like `README.md`, `PROJECT.md`, or status reports inside the skill folder. - Repeating the same guidance in both `SKILL.md` and `references/`. - Deep reference chains. ## Phase 4: Implementation When creating a new skill, initialize it with the provided scripts instead of hand-building the folder. ### Create a new skill ```bash python3 scripts/init_skill.py my-skill --path "${CODEX_HOME:-$HOME/.codex}/skills" --resources scripts,references ``` Optional: ```bash python3 scripts/init_skill.py my-skill --path /path/to/skills --resources scripts,references,assets --examples --interface display_name="My Skill" --interface short_description="Create or update My Skill tasks" ``` ### Validate a skill ```bash python3 scripts/validate_skill.py /path/to/skill ``` ### Package a skill ```bash python3 scripts/package_skill.py /path/to/skill ``` ## Phase 5: Review Gate Before calling the skill done, verify: - Frontmatter has only `name` and `description`. - `description` explains both function and trigger scenarios. - `SKILL.md` tells the agent what to do, not what the project is. - Every optional directory exists for a reason. - Scripts are real, runnable programs. - References are one hop away from `SKILL.md`. If the skill still feels vague, run another discovery pass instead of adding filler. ## Output Shape When responding to a user about a skill you are creating or improving, prefer this order: 1. Discovery summary 2. Chosen pattern and why 3. Planned resources 4. Files created or changed 5. Validation result Use [output-patterns.md](references/output-patterns.md) when you need a compact deliverable format.