Grill Skill

Build and harden a skill with evals — interview to design its eval tasks, then run, measure, and iterate. Use when the user wants to create or improve a skill's eval, or run the create → test → improve loop for a skill.

Interview the user to design a skill's eval, then loop run → measure → improve until it ships. Requires caliper (pipx install caliper-eval if missing). Commands, spec skeleton, and expect/assert guidance: REFERENCE.md.

Entry point

/grill-skill [path] — optional path to a SKILL.md.

• Path given — use it.
• No path — look for SKILL.md in the cwd; if found, confirm before proceeding, else ask where it is.

Phase 1 — Understand

Read the SKILL.md. Summarize what it does, when it triggers, and what a successful run looks like. Ask the user to confirm your reading. Wait for confirmation before continuing.

Phase 2 — Detect eval mode

Look for *.eval.yaml beside the SKILL.md (try <dir-name>.eval.yaml first).

• None → New eval. Found → Gap-fill.

Interview one question at a time and wait for each answer. Never invent the user's answers or write the spec before interviewing.

New eval — three tasks

Elicit three tasks, one question at a time:

1. Happy path — the most common successful use. What did the agent do, and what would confirm it worked?
2. Edge case — a tricky-but-valid input that might trip the raw agent.
3. Adversarial — what the skill should refuse or avoid.

Turn each answer into a task: a realistic prompt, an observable expect, and an assert when the outcome is checkable (see REFERENCE.md). Show the proposed YAML and confirm before writing.

Write the spec beside SKILL.md, named <dir-name>.eval.yaml, with skill.path: ./SKILL.md and claude-code as the default backend for both skill and judge unless the SKILL.md targets another.

Gap-fill

Read the existing spec and report its tasks. Ask what behaviors are missing or under-tested before proposing or writing anything — even if the user only asked you to inspect it, report first, then ask. Sharpen each gap into a task, show it, and confirm before writing it in.

Phase 3 — First run

Validate the spec, then run at k=1 (commands in REFERENCE.md). Show the results. Fix any harness or config error (not a task failure) before asking the user what to do next.

Phase 4 — Iterate

Ask whether to iterate or finish.

• Iterate — after the user edits their SKILL.md, re-run at k=3 and show results. Loop back.
• Done — suggest a --baseline run to prove the skill beats the raw agent, then remind the user to commit SKILL.md and the .eval.yaml together.