AI agents are good at interpreting goals, but prose instructions are a weak place to enforce exact rules. If a skill says "keep the commit subject short" or "never commit without approval," an agent can still misunderstand the boundary.
The open-source how-to-create-a-skill-tutorial shows a practical split: let the agent make judgments, and let small local scripts validate repeatable rules. This tutorial builds the smallest useful version of that pattern: a commit-crafter skill with a SKILL.md file, a Python validator, and tests that run with the Python standard library.
TL;DR
An Agent Skill is a directory containing at least SKILL.md. Put the workflow and safety boundaries in that file. Put exact validation in a script. Keep the script deterministic, return meaningful exit codes, and run it before presenting the result to a user.
The finished repository's example skill validates Conventional Commit messages. You can copy the same structure for release notes, config generation, research reports, or any other workflow with rules that can be checked mechanically.
