Use when an outage, production incident, or significant service degradation has occurred and the team needs to write a structured blameless post-mortem. Triggers on phrases like "write a post-mortem", "incident review", "what went wrong", "outage report", "root cause analysis", or "RCA". Covers timeline reconstruction, contributing factor analysis, impact quantification, and action item generation with owners.
npx skills add https://github.com/github/awesome-copilot --skill incident-postmortem
Guide a team through writing a structured, blameless post-mortem after a production incident. The output is a document that builds shared understanding, identifies root causes without blame, and produces concrete action items to prevent recurrence.
Systems fail, not people. The goal is to understand HOW the incident happened — not WHO caused it. Avoid language like "X forgot to", "Y should have known". Use "the system did not", "the process lacked", "the alert did not fire".
Not for: Minor bugs caught in staging, planned maintenance windows, or incidents with no learning value.
Gather these details before writing the post-mortem. Ask for anything missing:
Key moments to reconstruct:
Ask the team: "What made this worse than it needed to be?" — not "who failed". Examples:
If the user has not provided full incident details, ask for them section by section. Don't proceed to writing until you have: title, times, severity, affected services, and at least a rough timeline.
Work with the user to build a precise chronological timeline. For each event:
Flag gaps: "We don't know what happened between 14:32 and 14:47 — worth checking logs."
Use the 5 Whys iteratively:
Why did users see 500 errors?
→ The API pods were crash-looping.
Why were they crash-looping?
→ Memory limit was exceeded.
Why was the limit exceeded?
→ A new query was loading full result sets into memory.
Why wasn't this caught before deploy?
→ Load tests only covered the p50 case, not high-cardinality accounts.
Why did load tests only cover p50?
→ We had no test fixtures for large accounts.
Stop when you reach a system/process gap you can fix. The last "why" should point to an action item.
Distinguish:
Help the user be precise:
For each root cause and contributing factor, generate at least one action item:
| # | Action | Owner | Due Date | Priority |
|---|--------|-------|----------|----------|
| 1 | Add load test fixtures for accounts > 10k records | @eng-team | 2026-07-01 | High |
| 2 | Lower memory alert threshold from 90% to 75% | @platform | 2026-06-23 | High |
| 3 | Add runbook for memory OOM pods | @on-call-rotation | 2026-06-30 | Medium |
Action items must have an owner (a person, not a team) and a due date. Vague actions like "improve monitoring" are not acceptable — break them into specific deliverables.
Produce the full post-mortem using the template below. Save to docs/postmortems/YYYY-MM-DD-<slug>.md.
# Post-Mortem: [Incident Title]
**Date:** YYYY-MM-DD
**Severity:** P[1-4]
**Duration:** X hours Y minutes (HH:MM UTC – HH:MM UTC)
**Incident Commander:** @name
**Status:** Resolved
---
## Summary
[2–3 sentences. What happened, what was the user impact, how was it resolved. Written for someone who wasn't involved.]
## Impact
| Dimension | Value |
|-----------|-------|
| Affected services | [list] |
| User-facing impact | [errors / degraded / full outage] |
| Users affected | [estimated number or %] |
| Peak error rate | [X% vs Y% baseline] |
| Data loss | [none / describe scope] |
| SLA breach | [yes/no — by how much] |
## Timeline
All times UTC.
| Time | Event |
|------|-------|
| HH:MM | [First symptom / alert fired] |
| HH:MM | [On-call paged] |
| HH:MM | [Incident declared] |
| HH:MM | [Root cause identified] |
| HH:MM | [Mitigation applied] |
| HH:MM | [Full resolution confirmed] |
| HH:MM | [Customer communication sent] |
## Root Cause
[1–2 paragraphs. The deepest systemic gap that, if fixed, would have prevented the incident. Written in blameless language. Reference the 5 Whys chain if helpful.]
## Contributing Factors
- [Factor 1 — condition that made the incident worse]
- [Factor 2]
- [Factor 3]
## What Went Well
- [Thing that worked — good alert, fast response, clear runbook]
- [Another positive]
## What Could Have Gone Better
- [Gap in process, tooling, or coverage — no blame language]
- [Another gap]
## Action Items
| # | Action | Owner | Due Date | Priority |
|---|--------|-------|----------|----------|
| 1 | [Specific deliverable] | @person | YYYY-MM-DD | High/Medium/Low |
| 2 | | | | |
## Lessons Learned
[Optional. 2–4 bullet points capturing non-obvious insights worth sharing with the broader team.]
| Mistake | Fix |
|---------|-----|
| "Bob forgot to check the config" | "The deploy checklist did not include config validation" |
| Root cause is "human error" | Keep asking Why — human error is always a symptom |
| Action items without owners | Every item needs a named individual, not a team |
| Timeline reconstructed from memory | Check logs, alerts, Slack, PagerDuty before writing |
| "Improve monitoring" as an action | Specify: which service, which metric, what threshold, by when |
| Post-mortem written weeks later | Write within 48–72 hours while context is fresh |
Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.
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Build and distribute Expo development clients locally or via TestFlight
Use when you have a written implementation plan to execute in a separate session with review checkpoints
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
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Take github/incident-postmortem from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.