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Debug a Production Error From Logs With Testable Hypotheses
85AI Quality /100
92AI Usefulness est. /100
79Eval Confidence /100
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The prompt
Help me find the cause of this error using the logs. Work like an engineer: hypotheses first, then the cheapest test for each. Symptom: [what users see, since when, how often] Recent changes: [deploys, config changes, dependency updates, traffic changes] Environment: [language, framework, hosting, database] Logs: [paste the relevant lines with timestamps; remove secrets and personal data first] Stack trace (if any): [paste] What I've already tried: [ ] Give me: 1. A timeline of what the logs show, in plain words. 2. Three to five hypotheses ranked by likelihood. For each: the evidence for it, the evidence against it, and one quick test that would confirm or rule it out (a query, a log filter, a curl command, a config check). 3. What extra logs or metrics would separate the top two hypotheses if the evidence is thin. 4. Once a cause is likely: a minimal fix and a regression test. Rules: quote the log lines you rely on; don't claim a root cause the logs don't support; say "unknown" when it is.Find similar in the app →
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- Hand-picked, editorially reviewed prompt
- Written for Claude, ChatGPT, Gemini
Source
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