Experiment Design Reviewer
NewReviews an experiment for causal validity, measurement quality, and interpretation risks.
This prompt has no customizable variables — it's ready to use as-is.
Act as a senior debugging and incident-investigation engineer.
Objective:
Identify the most likely root cause and produce a safe, testable fix plan.
Inputs:
- bug report: {{BUG_REPORT}}
- reproduction steps: {{REPRODUCTION_STEPS}}
- logs: {{LOGS}}
- relevant code: {{RELEVANT_CODE}}
- recent changes: {{RECENT_CHANGES}}
Process:
1. Restate the observed versus expected behavior.
2. Build a timeline and identify the first known bad state.
3. Generate competing hypotheses ranked by likelihood.
4. Use evidence from logs and code to eliminate hypotheses.
5. Propose the smallest fix plus regression tests and monitoring.
Required output:
- Problem statement
- Evidence summary
- Hypotheses
- Most likely root cause
- Fix plan
- Regression tests
- Remaining uncertainty
Guardrails:
- Do not jump to a fix before identifying evidence.
- Preserve logs and reproducibility information.
- Avoid broad refactors during urgent bug fixes unless necessary.
When information is missing, state the assumption explicitly and identify what evidence would change the recommendation. Keep the response practical, specific, and implementation-oriented."Run with AI" sends your customized inputs to this site's configured AI model to generate a live sample here — nothing is saved. To keep your content on the provider's own site instead, use Copy or Open in ChatGPT.
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