incident-response
SkillCloud & infraLets your agent triage production incidents, gather evidence, find root cause, deploy fixes, and write post-mortems.
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Details
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About this skill
When something breaks in production: triage the severity, gather evidence, identify root cause, deploy a fix or mitigation, and write a post-mortem. Provides a calm, structured process for high-stress moments.
What this skill tells your AI
The instructions your AI receives, as published by omergocmen/vibe-coder-kit in .agent/skills/incident-response/SKILL.md and read by ahel’s review.
Incident Response Skill
When to Trigger
- Production is down or severely degraded
- Error rate spikes significantly above baseline
- A customer reports a critical bug in production
- A security breach or data leak is suspected
- A deployment caused an unexpected regression
Step-by-Step Process
1. Declare and Classify the Incident
First: breathe. Then classify.
| Severity | Definition | Response Time |
|---|---|---|
| P1 — Critical | Full outage, data loss, security breach | Immediate |
| P2 — High | Major feature broken, significant users affected | < 30 min |
| P3 — Medium | Partial degradation, workaround exists | < 2 hours |
| P4 — Low | Minor bug, cosmetic issue | Next sprint |
Open .agent/incidents/INC-<YYYY-MM-DD>-<slug>.md and write:
# Incident: <short title>
**Date:** <YYYY-MM-DD HH:MM UTC>
**Severity:** P<N>
**Status:** Investigating
**Incident Commander:** <name>
2. Triage — Gather Evidence Fast
Don't guess. Collect data first.
Checklist:
- What is the user-visible symptom?
- When did it start? (check monitoring, not just "someone reported it")
- What changed recently? (last deploy, config change, dependency update)
- What does the error log say? (get exact error messages + stack traces)
- Is it affecting all users or a subset?
- Is there an automated alert, or was this user-reported?
Commands to run immediately:
# Recent deploys
git log --oneline -20
# Check running process / container health
# (adjust for your stack)
docker ps
systemctl status <service>
# Tail live logs
docker logs -f <container> --tail 100
journalctl -u <service> -n 100 -f
Add findings to the incident file under ## Evidence.
3. Contain the Blast Radius
Before fixing, limit the damage:
- If a bad deploy caused it: roll back immediately
git revert HEAD # or redeploy previous known-good version - If a specific feature is failing: toggle it off via feature flag
- If data is being corrupted: take the affected service offline temporarily
- If a secret was exposed: rotate it immediately, then investigate
Document every action taken in the incident file with timestamps.
4. Root Cause Analysis
Once contained, find the real cause — not just the symptom.
Use the 5 Whys technique:
Why did users see a 500 error?
→ Because the database query timed out.
Why did the query time out?
→ Because a new index was missing after the migration.
Why was the index missing?
→ Because the migration script didn't include CREATE INDEX.
Why didn't the migration script include it?
→ Because we don't have a convention for checking query plans before deploy.
→ Root cause: Missing pre-deploy query plan review process.
The root cause is almost never the immediate technical failure — it's the process gap that allowed it.
5. Fix and Deploy
Write the fix:
- Smallest possible change that resolves the issue
- Add a test that would have caught this
- Double-check the fix in staging before production
Deploy:
- Monitor metrics during deploy
- Keep someone watching logs for 15 minutes post-deploy
- Confirm symptom is resolved with a real user test
6. Write the Post-Mortem
Within 24h of resolution, write a post-mortem in .agent/incidents/INC-<date>-<slug>.md:
# Post-Mortem: <title>
## Summary
<2-3 sentences: what happened, how long, how many users affected>
## Timeline
| Time (UTC) | Event |
|------------|-------|
| HH:MM | Issue first occurred (inferred from logs) |
| HH:MM | First alert / user report |
| HH:MM | Incident declared |
| HH:MM | Mitigation applied |
| HH:MM | Root cause identified |
| HH:MM | Fix deployed |
| HH:MM | Incident resolved |
## Root Cause
<The actual root cause — not just the symptom>
## What Went Well
- <something that helped — good monitoring, fast rollback, etc.>
## What Went Poorly
- <something that made it worse — slow detection, unclear runbook, etc.>
## Action Items
| Action | Owner | Due Date |
|--------|-------|----------|
| Add missing index to migration convention | <name> | <date> |
| Add test for query performance | <name> | <date> |
| Set up alert for DB query p99 latency | <name> | <date> |
7. Update the Knowledge Base
After the post-mortem, use the knowledge-base-update skill to create a gotcha entry for the root cause so future agents and developers know about it.
Rules
- Contain first, diagnose second. Stopping the bleeding is more important than understanding the wound.
- No blame in post-mortems. Focus on process gaps, not people.
- Every incident generates at least one action item. If nothing changes, it will happen again.
- Never declare an incident resolved until a real user confirms the fix. Metrics can lie; users don't.
- All P1/P2 incidents require a post-mortem. No exceptions.
Signals
- GitHub stars
- 92
- Forks
- 10
- Last commit
- Jun 2026
Advanced
- Item type
- skill
- Key
incident-response-omergocmen- Source
- github.com/omergocmen/vibe-coder-kit
github.com/omergocmen/vibe-coder-kit
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