Code review, debugging, architecture, testing and docs. 5 reviewed prompts for engineering.
Designs a practical testing strategy for an application: risk map, test layers with targets, dependency handling, the first ten tests to write, CI gates and a four-week rollout. Use it when a suite is missing, slow or untrusted.
Builds a practical test plan for an AI assistant or automated workflow: realistic test cases, pass/fail rules, metrics and review triggers. Use before rolling a workflow out to a team.
Designs how to test an AI-powered feature before and after launch: success metrics, a balanced test set, a 1-5 scoring rubric with examples, pass criteria and a failure log. Use when you need to know whether an AI feature is good enough to ship.
Use when you have just written or changed code and before presenting it: runs a focused second pass for the mistakes generated code commonly contains, fixes what it can, and reports what was fixed and what needs the author's attention.
Standing approach for reviewing code: rank findings by impact, explain why, and suggest a fix. Use when asked to review code, a change or a pull request.
