Bug Report Analyzer
The Bug Report Analyzer takes a raw bug report, error log, or user complaint and produces a structured analysis: likely root causes ranked by probability, clear reproduction steps, severity classification, and a targeted debugging plan. It transforms vague reports like "the app is broken" into actionable investigation paths.
Developers, QA engineers, and support teams use this template when triaging incoming bug reports, especially when the report lacks critical details or the bug is difficult to reproduce. It is particularly useful during high-pressure production incidents where fast, structured thinking matters more than ever.
The prompt works by applying systematic debugging methodology to the information available. It distinguishes between what is known (facts from the report), what is likely (inferences from the symptoms), and what is unknown (gaps that need investigation). This structured approach prevents the common trap of jumping to a fix before understanding the problem, which often wastes hours on the wrong hypothesis.
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The Prompt
Analyze the following bug report and help me diagnose the issue: **Bug Report Source**: [User report / automated alert / QA ticket / error log] **Application**: [APP NAME and brief description of what it does] **Tech Stack**: [e.g., Next.js, PostgreSQL, Redis, deployed on AWS] **Bug Description**: [PASTE THE BUG REPORT, ERROR MESSAGE, OR USER COMPLAINT HERE. Include as much raw information as you have: error messages, stack traces, screenshots description, user steps, timestamps.] **What I Already Know**: - When did it start happening? [DATE/TIME or "unknown"] - How many users are affected? [ALL / SOME / ONE / UNKNOWN] - Has anything changed recently? [RECENT DEPLOYMENTS, CONFIG CHANGES, OR "nothing obvious"] - Can it be reproduced consistently? [YES / SOMETIMES / NO / UNTESTED] Provide your analysis in this format: 1. **Summary**: In 2-3 sentences, restate the bug in precise technical language. Translate vague user complaints into specific, testable assertions. 2. **Severity Assessment**: Rate this bug on two scales: - **Impact**: Critical (data loss, security breach, full outage) / High (major feature broken for many users) / Medium (feature degraded, workaround exists) / Low (cosmetic, edge case) - **Urgency**: Immediate (fix now) / High (fix today) / Normal (fix this sprint) / Low (backlog) - Justify your rating in one sentence. 3. **Root Cause Hypotheses**: List 3-5 possible causes ranked by likelihood. For each: - State the hypothesis in one sentence - Explain what evidence supports it from the bug report - Describe one quick check to confirm or rule it out 4. **Reproduction Steps**: Write a step-by-step reproduction plan based on the available information. Mark any steps that are guesses with "[VERIFY]" so the developer knows to confirm them. 5. **Information Gaps**: List specific questions whose answers would significantly narrow down the root cause. For each question, explain what it would tell you (e.g., "Is this happening only on Safari? If yes, this is likely a CSS/JS compatibility issue, not a backend problem."). 6. **Debugging Plan**: Provide a prioritized list of 3-5 concrete debugging actions, starting with the fastest to execute. For each action: - What to check (specific file, log, endpoint, or database query) - What to look for - What the result would mean 7. **Immediate Mitigation** (if severity is High or Critical): Suggest a temporary workaround or mitigation that can reduce user impact while the root cause is being investigated.
Usage Tips
- Paste raw error messages and stack traces: Do not paraphrase or summarize error output. The exact wording, error codes, and line numbers are often the fastest path to a diagnosis.
- Include recent changes: Most bugs are caused by something that changed. If you deployed code, updated a dependency, or modified a config in the last 48 hours, mention it even if it seems unrelated.
- Use this for triage, not just diagnosis: Run every incoming bug report through this template to quickly assign severity, estimate effort, and decide whether to fix now or backlog. It brings consistency to your triage process.
- Feed the results back: Once you find the actual root cause, revisit the analysis to see which hypothesis was correct. Over time, this builds your intuition for debugging patterns.
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