/nw-post-mortem-framework
Blameless post-mortem structure, incident timeline reconstruction, response evaluation, and organizational learning
Claude Code
$ npx -y skills add nWave-ai/nWave --skill nw-post-mortem-framework --agent claude-code
Codex
$ npx skills add nWave-ai/nWave --skill nw-post-mortem-framework -a codex -y
Cursor
$ npx skills add nWave-ai/nWave --skill nw-post-mortem-framework -a cursor -y
Gemini CLI
$ npx skills add nWave-ai/nWave --skill nw-post-mortem-framework -a gemini-cli -y
GitHub Copilot
$ npx skills add nWave-ai/nWave --skill nw-post-mortem-framework -a github-copilot -y
OpenCode
$ npx skills add nWave-ai/nWave --skill nw-post-mortem-framework -a opencode -y
Windsurf
$ npx skills add nWave-ai/nWave --skill nw-post-mortem-framework -a windsurf -y
SKILL.md
nw-post-mortem-framework.SKILL.mdname: nw-post-mortem-framework
description: Blameless post-mortem structure, incident timeline reconstruction, response evaluation, and organizational learning
user-invocable: false
disable-model-invocation: true
Post-Mortem Framework
Principles
- **Blameless**: focus on systems/processes, not individuals. People make reasonable decisions given available info.
- **Evidence-based**: every finding backed by logs, metrics, or documented actions
- **Action-oriented**: every finding produces concrete, assigned action item
- **Learning-focused**: capture what worked alongside what failed
Post-Mortem Document Structure
# Post-Mortem: [Incident Title]
**Date**: [incident date]
**Duration**: [start to resolution]
**Severity**: [P0-P3]
**Author**: [analyst]
## Summary
[2-3 sentence overview: what happened, impact, resolution]
## Timeline
| Time | Event | Source |
|------|-------|--------|
| HH:MM | [event] | [log/metric/report] |
## Impact
- Users affected: [number/percentage]
- Duration of impact: [time]
- Business impact: [quantified if possible]
- Systems affected: [list]
## Root Cause Analysis
[5 Whys analysis with evidence at each level]
## Detection and Response
- Time to detect: [duration] -- [how detected]
- Time to respond: [duration] -- [first action]
- Time to mitigate: [duration] -- [mitigation applied]
- Time to resolve: [duration] -- [permanent fix]
## What Went Well
- [positive observations about detection, response, recovery]
## What Could Be Improved
- [areas where detection, response, recovery fell short]
## Action Items
| ID | Action | Owner | Priority | Due Date |
|----|--------|-------|----------|----------|
| 1 | [specific action] | [team/person] | [P0-P3] | [date] |
## Lessons Learned
- [key takeaways for the organization]
Incident Timeline Reconstruction
Sources
1. Monitoring alerts/dashboards (timestamps) | 2. Deployment logs/CI-CD records 3. Communication channels (Slack, email, incident) | 4. VCS (commits, merges, deploys) | 5. User reports/support tickets
Quality Checks
Events chronological with verified timestamps | gaps >5 min noted/explained | decision points identified with available info | causal relationships noted
Response Effectiveness Evaluation
Detection
Detected by monitoring or users? | Duration onset-to-detection? | Existing alerts relevant? Missing?
Escalation
Right team at right time? | Procedures followed? | Communication clear to stakeholders?
Resolution
Mitigation effective? | Rollback considered/viable? | Duration mitigation-to-permanent-fix?
Organizational Learning
Knowledge Capture
Document root causes as reusable patterns | update runbooks | share in retrospectives
Process Improvements
Update monitoring/alerting per detection gaps | revise deployment per rollback effectiveness | strengthen testing for failure scenario
Action Item Tracking
Every item has owner + due date | track in standups/sprint reviews | verify effectiveness post-deployment
Read more
name: nw-post-mortem-framework description: Blameless post-mortem structure, incident timeline reconstruction, response evaluation, and organizational learning user-invocable: false disable-model-invocation: true
Post-Mortem Framework
Principles
- **Blameless**: focus on systems/processes, not individuals. People make reasonable decisions given available info.
- **Evidence-based**: every finding backed by logs, metrics, or documented actions
- **Action-oriented**: every finding produces concrete, assigned action item
- **Learning-focused**: capture what worked alongside what failed
Post-Mortem Document Structure
# Post-Mortem: [Incident Title] **Date**: [incident date] **Duration**: [start to resolution] **Severity**: [P0-P3] **Author**: [analyst] ## Summary [2-3 sentence overview: what happened, impact, resolution] ## Timeline | Time | Event | Source | |------|-------|--------| | HH:MM | [event] | [log/metric/report] | ## Impact - Users affected: [number/percentage] - Duration of impact: [time] - Business impact: [quantified if possible] - Systems affected: [list] ## Root Cause Analysis [5 Whys analysis with evidence at each level] ## Detection and Response - Time to detect: [duration] -- [how detected] - Time to respond: [duration] -- [first action] - Time to mitigate: [duration] -- [mitigation applied] - Time to resolve: [duration] -- [permanent fix] ## What Went Well - [positive observations about detection, response, recovery] ## What Could Be Improved - [areas where detection, response, recovery fell short] ## Action Items | ID | Action | Owner | Priority | Due Date | |----|--------|-------|----------|----------| | 1 | [specific action] | [team/person] | [P0-P3] | [date] | ## Lessons Learned - [key takeaways for the organization]
Incident Timeline Reconstruction
Sources
1. Monitoring alerts/dashboards (timestamps) | 2. Deployment logs/CI-CD records 3. Communication channels (Slack, email, incident) | 4. VCS (commits, merges, deploys) | 5. User reports/support tickets
Quality Checks
Events chronological with verified timestamps | gaps >5 min noted/explained | decision points identified with available info | causal relationships noted
Response Effectiveness Evaluation
Detection
Detected by monitoring or users? | Duration onset-to-detection? | Existing alerts relevant? Missing?
Escalation
Right team at right time? | Procedures followed? | Communication clear to stakeholders?
Resolution
Mitigation effective? | Rollback considered/viable? | Duration mitigation-to-permanent-fix?
Organizational Learning
Knowledge Capture
Document root causes as reusable patterns | update runbooks | share in retrospectives
Process Improvements
Update monitoring/alerting per detection gaps | revise deployment per rollback effectiveness | strengthen testing for failure scenario
Action Item Tracking
Every item has owner + due date | track in standups/sprint reviews | verify effectiveness post-deployment
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Questions about nw-post-mortem-framework.
- Which coding agents can use nw-post-mortem-framework?
- nw-post-mortem-framework installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.

