Skill Creator

11 steps · start to finish.

1. 1
   Step 1

   Environment Setup

   ▶

   Verify the environment has all required tools and the skill path is valid.

   # Check Python is available
   python3 --version || { echo "ERROR: python3 not found"; exit 1; }
   
   # Check claude CLI (needed for description optimization)
   command -v claude >/dev/null 2>&1 && echo "claude CLI present" || echo "WARN: claude CLI not found (description optimization will be unavailable)"
   
   # Verify skill path exists or create it
   SKILL_NAME="${SKILL_NAME:-my-skill}"
   SKILL_PATH="${SKILL_PATH:-./$SKILL_NAME}"
   mkdir -p "$SKILL_PATH"
   mkdir -p "$SKILL_PATH/evals"
   mkdir -p "${SKILL_NAME}-workspace"
   mkdir -p /app/results
   
   echo "Setup complete. Skill path: $SKILL_PATH"
   

   ---

2. 2
   Step 2

   Capture Intent

   ▶

   Understand the user's intent before writing anything. If the current conversation already contains a workflow the user wants to capture (e.g., they say "turn this into a skill"), extract answers from history first.

3. 3
   Step 3

   Interview and Research

   ▶

   Before writing the SKILL.md, proactively gather:

4. 4
   Step 4

   Write the SKILL.md

   ▶

   Based on the user interview, produce `<skill-path>/SKILL.md` with this structure:

5. 5
   Step 5

   Write Test Cases

   ▶

   After drafting the skill, create 2–3 realistic test prompts — the kind of message a real user would actually send. Share them with the user for confirmation before running.

6. 6
   Step 6

   Run & Evaluate (max 5 iterations)

   ▶

   This is one continuous sequence — do not stop partway through.

7. 7
   Step 7

   Iterate on Errors (max 3 rounds)

   ▶

   After reading feedback, improve the skill and re-run:

8. 8
   Step 8

   Advanced — Blind Comparison (Optional)

   ▶

   For rigorous comparison between two skill versions, use the blind comparison system in `agents/comparator.md` and `agents/analyzer.md`. An independent agent evaluates both outputs without knowing which is which. This is optional and most users won't need it — the human review loo

9. 9
   Step 9

   Description Optimization

   ▶

   After finalizing the skill body, offer to optimize the description for better triggering accuracy.

10. 10
    Step 10

    Package and Present

    ▶

    If the `present_files` tool is available:

11. 11
    Step 11

    Environment-Specific Adaptations

    ▶

    - **No subagents**: run test cases sequentially, executing SKILL.md instructions inline. Skip baseline runs. - **No browser**: skip `generate_review.py`. Present results directly in conversation; ask for feedback inline.