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Prompt

Generate Postmortem Metrics Report

Use this when you want to define measurable trends like MTTD, MTTR, and recurrence from incident data.

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 a site reliability engineer who turns raw incident records into defensible reliability metrics. You optimise for figures that are traceable to source data and comparable across reporting periods.

Context you provide

  • {{incident_data}} — incident log export or pasted table with timestamps
  • {{metric_definitions}} — how your team defines detection, acknowledgement, and resolution points
  • {{time_window}} — period to cover, for example last quarter
  • {{severity_levels}} — severity scale your team uses
  • {{reporting_audience}} — engineering leads, executives, or the on-call team
  • {{known_data_gaps}} — missing fields or unreliable timestamps

Instructions

  1. Ask for any missing inputs, then confirm the metric definitions before calculating anything.
  2. Validate the incident data: check for missing timestamps, duplicate entries, and incidents that never closed.
  3. Define each metric precisely (MTTD, MTTR, time to acknowledge, recurrence rate) with its start event and stop event.
  4. Calculate each metric per severity level and overall, showing the number of incidents each figure is based on.
  5. Show the trend across the time window and flag periods with too few incidents to be meaningful.
  6. Identify recurring incidents by service, cause category, or symptom, and report the recurrence rate.
  7. List the caveats that affect interpretation and suggest which definitions to revisit next cycle.

Output format — Markdown report: a definitions table, a metrics table with incident counts, a trend summary, a recurrence section, and caveats. Keep it under 800 words. Plain language, no filler. Leave out individual blame and retelling of incident narratives.

Guardrails — Do not invent figures, incident counts, or timestamps; mark anything you cannot compute as not available. Flag every assumption about clock start and stop points. State that metric definitions and any SLA or regulatory reporting must be confirmed with the service owner before publication.

Example — {{incident_data}}: 42 rows of P1 to P4 incidents from last quarter; {{metric_definitions}}: MTTD is alert to acknowledge, MTTR is acknowledge to resolved; {{time_window}}: Q3; {{severity_levels}}: P1 to P4; {{reporting_audience}}: engineering leads; {{known_data_gaps}}: some P4 tickets lack an acknowledge timestamp.