AI coding agents write code that looks finished but fails differently than human code: dropped auth checks, tests that mock the function they test, hallucinated API calls. This toolkit gives you the 6 recurring failure patterns, a 45-item review checklist, a risk-scoring rubric, and a PR tracker spreadsheet to see which AI tool causes the most rework. For solo devs and small teams using Claude Code, Cursor, or Copilot.
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I merged a PR from Claude Code that looked completely clean, only to find out two weeks later it had quietly dropped an authorization check during a refactor. That sent me looking for the recurring failure patterns AI coding agents actually produce (they're different from what human reviewers are trained to catch), and this toolkit is the checklist and tracker I built out of that. Would love feedback from anyone else reviewing a lot of AI-generated code.