Skill Template (Exemplar)

This is a working reference skill. Copy the entire codexkit-skill-template/ folder and rename it to create a new skill.

When to Use

• When creating a brand-new CodexKit skill from scratch
• When upgrading an existing skill to the v2 format
• When reviewing whether a skill meets the quality bar

Procedure

Step 1 — Define the Intent and Trigger

Write a clear, one-sentence purpose. Answer: "After running this skill, the user will have ___." Then decide whether it should be directly invoked by name, automatically selected from its description, or support both. Keep the description concrete enough to distinguish it from neighboring skills.

Step 2 — Map the Domain

Identify the 3–5 key frameworks or standards that professionals use in this domain. Use the Deep Research Prompt to generate domain knowledge if needed.

Step 3 — Write the Procedure

Break the workflow into 4–7 steps. Each step should produce a concrete, visible output — not just "think about X."

Step 4 — Add Verification

Write domain-specific 4C questions. The Consequence question is the most important: "If this output were used immediately, what could go wrong?"

Step 5 — Document Edge Cases

List situations where the skill's default approach breaks down. For each, provide a mitigation or fallback.

Inputs

Input	Required	Format
Skill domain description	Yes	Free text — the problem space this skill serves
Target audience	Yes	Who will consume the output (developers, managers, executives)
Existing materials	Recommended	Any templates, standards, or examples to build from

Output

A complete skill folder with:

• SKILL.md following v2 format (10 sections)
• agents/openai.yaml with interface block
• CHANGELOG.md initialized at v1.0.0

Quality Criteria

• Purpose is a single, clear sentence — no compound goals
• Invocation mode and trigger description are clear; near-miss requests remain out of scope
• Procedure steps each produce a visible deliverable
• Quality Criteria are measurable or concretely observable
• 4C Verification questions are domain-specific, not generic
• Edge Cases cover at least 3 realistic failure scenarios
• Examples show annotated contrast between good and bad output
• Frontmatter has name, description, version, category

Verification (4C)

Check	Question
Correctness	Does the skill's procedure match established domain frameworks?
Completeness	Are all 10 required sections present and substantive (not placeholder)?
Context-fit	Would the skill produce useful output for its stated audience?
Consequence	If a contributor copied this skill as-is, what would they get wrong?

Edge Cases

• Skill spans multiple domains — Split into separate skills. One skill = one task.
• No established framework exists — Document the decision rationale in Procedure. Use first-principles reasoning instead of citing standards.
• Output format varies by context — Provide 2–3 output templates and add selection criteria.

Examples

Good: A skill with 6 procedure steps where each step ends with "Produce: {specific table/section}." The 4C questions reference domain-specific metrics (e.g., "Does the NPS calculation exclude neutral responses?").

Bad: A skill with a single step "Analyze the data and produce a report." Verification says "Check if it's correct." No edge cases listed.

Definition of Done

• All 10 sections filled with substantive content
• ``agents/openai.yaml` created with valid interface block
• node ./scripts/validate-pack.mjs passes
• At least one person besides the author has reviewed the skill

Changelog

• v1.0.0 — Initial release as exemplar for 5-Layer Skill Framework