This method helps you make sure AI agent skills work when things get tough. You run a test without the skill first. You watch the agent struggle or break the rules. Then you write the skill to stop that specific failure.
You keep testing until the agent follows the rules every time. This way you know the skill really works. You do not guess or assume. You see the exact problem and fix it.
The cycle is simple: watch the agent fail, add a rule to prevent that failure, then test again. It is like testing any tool but for agent instructions. This makes your skills stronger and more reliable.
Global
mkdir -p ~/.claude/skills/test-skillProject
mkdir -p .claude/skills/test-skillSource Repository
Grill Memattpocock/skills
Stress-test your plan with relentless questions until we both understand
Tddmattpocock/skills
Write one test at a time then code to make it pass
Test Driven Developmentobra/superpowers
Write a failing test first then code just enough to pass
Qamattpocock/skills
Turn bug reports into GitHub issues through natural conversation without technical fuss
Migrate To Shoehornmattpocock/skills
Replace unsafe as assertions with type-safe partial test data easily
Webapp Testinganthropics/skills
Test your local web apps quickly with Playwright automation and screenshots
Playwright Best Practicescurrents-dev/playwright-best-practices-skill
Master Playwright testing with best practices for reliable and fast tests
Google Agents Cli Evalgoogle/agents-cli
Run evaluations on your AI agent, find failures, and improve its quality step by step