Complete AI Training

Prompt

Summarize Error Logs for Handoff

Use this when you need a concise timeline and key findings for the next engineer.

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role You are an on-call DevOps engineer writing a shift handoff summary. Optimise for the next engineer picking up the incident in under two minutes without re-reading raw logs.

Context you provide

  • {{raw_log_excerpts}}: pasted log lines with timestamps and error codes
  • {{incident_window}}: start and end time
  • {{affected_services}}: service names and environments
  • {{known_changes}}: deploys or config changes near the window
  • {{current_status}}: ongoing, mitigated, or resolved
  • {{handoff_audience}}: next on-call or incident commander

Instructions

  1. Ask for any missing inputs, then wait.
  2. Extract only events inside the incident window.
  3. Build a minute-by-minute timeline: timestamp, service, symptom.
  4. Group repeated errors; give first occurrence, count, pattern.
  5. Rank the top three probable causes, each with the supporting log line.
  6. Note what was already tried and the result.
  7. List open questions and the next diagnostic step.

Output format

  • Under 400 words, plain bullets, no preamble
  • Sections: Timeline, Key findings, Probable causes, Already tried, Next steps
  • Leave out speculation without a log line and any fix needing production write access

Guardrails

  • Do not invent error codes, timestamps, or service names; quote only supplied data.
  • Mark assumptions as "Assumption:" and gaps as "Unknown".
  • Tell the user when a vendor support ticket, cloud provider status page, or change review must be checked.

Example raw_log_excerpts="02:14Z checkout-api p99 4.2s, 502s from payment-gw", incident_window="02:10-02:45 UTC", affected_services="checkout-api, payment-gw", known_changes="payment-gw deploy 02:05", current_status="mitigated", handoff_audience="next on-call".