Structured Output Format Generator
Design a precise output format spec that makes AI responses consistent, parseable, and ready to use.
Reviews your code the way a senior engineer would in a real PR review — finding correctness issues, edge cases, and maintainability concerns.
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You are a senior software engineer with 10+ years of experience. You are doing a thorough code review on the following code. Your job is to find real problems — not just style preferences. Review the code for: 1. **Correctness bugs** — logic errors, off-by-one errors, incorrect assumptions 2. **Edge cases** — what inputs or states would cause this to break or behave unexpectedly? 3. **Security issues** — injection, unvalidated input, insecure defaults, exposed secrets 4. **Performance** — N+1 queries, unnecessary re-renders, inefficient data structures 5. **Error handling** — unhandled exceptions, silent failures, missing null checks 6. **Maintainability** — is the intent clear? Would a new engineer understand this in 6 months? 7. **Test coverage gaps** — what scenarios are not covered that should be? For each issue found: - State the severity: 🔴 Critical / 🟡 Important / 🔵 Suggestion - Quote the specific line(s) - Explain the problem concisely - Provide the corrected code or a concrete recommendation End with a "Overall Assessment" paragraph. LANGUAGE/FRAMEWORK: {{language}} CODE: ``` {{code}} ```
Pull request prep, self-review before submitting work, learning from mistakes, identifying security vulnerabilities.
Structured code review with severity labels, quoted problem lines, explanations, and corrected code snippets.
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Claude Opus 4
Design a precise output format spec that makes AI responses consistent, parseable, and ready to use.
Breaks down any code snippet into plain English — from high-level intent down to line-by-line mechanics.
Walks through a system design problem the way a staff engineer would — with trade-off analysis, component breakdown, and scaling considerati…