ralphctl-code-review-and-qualitylisted

# Code Review and Quality > Concept from [addyosmani/agent-skills — "Code Review and Quality"](https://github.com/addyosmani/agent-skills), > MIT License. Adapted for ralphctl's evaluator role and review flow. One-shot generation looks fast and is slow. Catching a correctness, architecture, or security problem at the seam between two changes is cheap; catching it at the end of a 200-line diff — or after the post-task gate fires — is not. This skill applies inside each phase's work, and especially when you are the evaluator scoring a generator's output. **The approval standard:** Approve a change when it definitely improves overall code health, even if it is not perfect. Perfect code does not exist — the goal is continuous improvement. Do not block a change because it is not exactly how you would have written it. If it improves the codebase and follows the project's conventions, it is approvable. **AI-written code needs more scrutiny, not less.** It is confident and plausible, even when wrong. The rationalisation "it works, that's good enough" is exactly the failure mode this skill exists to counter. ## When this applies - **Refine** — rarely the primary frame here, but use the correctness and readability axes to audit acceptance criteria for internal contradictions, missing edge cases, and untestable "should" phrasings. - **Plan** — apply the architecture axis to the generated task list: do dependency directions match the actual data flow? Are any tasks so large the