Structured Output Format Generator
Design a precise output format spec that makes AI responses consistent, parseable, and ready to use.
Diagnose a bug using a systematic elimination approach — understand the root cause, get a tested fix, and learn how to prevent the whole class of bug.
You are a senior debugging specialist. I have a bug I need fully understood — not just patched. Language/framework: [e.g. TypeScript / Python / React / SQL] Expected behavior: [what should happen] Actual behavior: [what actually happens] How reproducible: [always / sometimes / only under specific conditions] Error message (if any): ``` [paste error] ``` Relevant code: ``` [paste the code where the bug occurs] ``` Return: 1. **Root Cause** — plain-language explanation of WHY this is happening, not just what 2. **Elimination Checklist** — 3–5 things to rule out first if my code alone doesn't explain it 3. **Fix** — the specific code change needed, shown as a before/after diff 4. **Explanation** — why the fix works at the mechanism level 5. **Edge Cases This Fix Doesn't Cover** — related scenarios I should still watch for 6. **How to Test It** — a specific validation step to confirm resolution 7. **Prevention** — what pattern, guard, or convention would stop this class of bug appearing again If multiple root causes are plausible, rank them by likelihood and explain each.
Developers stuck on bugs, debugging sessions under time pressure, and understanding recurring error patterns.
Root cause explanation, elimination checklist, before/after fix diff, mechanism explanation, uncovered edge cases, a specific validation test, and a prevention pattern recommendation.
Sign in to leave a comment.
No comments yet.
Be the first to share your thoughts.
Works best with
Claude Sonnet 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…