incident-response
Skill0 starsChanged 2 months agoMITView on GitHub
Investigate production incidents and reliability events using a safe, evidence-driven workflow. Use for outages, service degradation, alert storms, regressions, mitigation planning, timelines, and post-incident analysis.
81 other projects use a version of this.
Adopted by
Most recently taken up by
- anuragsarkar97/skillstheir own version, first seen Nov 8, 2026
- tigu77/tiguclawtheir own version, first seen Nov 8, 2026
- darkweb19/skillstheir own version, first seen Nov 8, 2026
- mdigital94/vibe-shield-plugintheir own version, first seen Nov 8, 2026
- nisarth/claude-skills-storetheir own version, first seen Nov 8, 2026
- aymardkouakou/claude-gh-skillstheir own version, first seen Nov 8, 2026
Used with
Projects with it also use dora-metrics, background-jobs and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
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YepAPISkilldata-pipelines
ETL patterns, cron scheduling, queue-based processing, and batch jobs with Inngest/BullMQ.
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mmondoraSkillinfrastructure-as-code
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csiddhant796-blipSkillthreat-detection
Use when hunting for threats in an environment, analyzing IOCs, or detecting behavioral anomalies in telemetry. Covers hypothesis-driven threat hunting, IOC sweep generation, z-score anomaly detection, and MITRE ATT&CK-mapped signal prioritization.
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Other versions81 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 81
- anthropics/knowledge-work-plugins★ 35ksame name
- microsoft/hve-core★ 1.6ksame name
- hypnguyen1209/offensive-claude★ 401same name
- duyet/clickhouse-monitoring★ 303same name
- kid-sid/claude-spellbook★ 190same name
- irahardianto/awesome-agv★ 157same name
- harness/harness-skills★ 127same name
- nahid-sparktales/agent-dispatcher★ 59same name
- Happy-Technologies-LLC/happy-platform-skills★ 41same name
- drafthq/draft★ 40same name
71 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository5 other files it gives its agents.
- AGENTS.mdAGENTS.md
- cpp-reliabilitySkill
- distributed-systems-debuggingSkill
- performance-investigationSkill
- pull-requestSkill
The file
We split this skill into the rules it gives an agent
3 rules. 0 are common, 3 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 68 edited versions we read keep these.
3
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 37
Prefer discriminating tests over collecting more undirected data.
- Distinctive: line 41
Prefer reversible, well-understood actions.
- Distinctive: line 43
Do not combine several mitigations when one can be evaluated independently.
“Common” is measured: kept by at least 6 in 10 of the 68 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Incident response
Establish the situation
- Record the current time, impact, affected scope, and incident start time.
- Identify what is confirmed, what is inferred, and what remains unknown.
- Define the expected behavior and the observed deviation.
- Determine whether impact is growing, stable, or recovering.
Build the timeline
Collect timestamps for:
- First customer or monitoring signal.
- Deployments and configuration changes.
- Dependency failures and recovery events.
- Operator actions and automated mitigations.
- Changes in traffic, capacity, latency, errors, and resource pressure.
Normalize timestamps before drawing conclusions.
Manage hypotheses
For every hypothesis record:
- Evidence that supports it.
- Evidence that contradicts it.
- The smallest safe test that could disprove it.
- Confidence and remaining unknowns.
Prefer discriminating tests over collecting more undirected data.
Mitigate safely
- Prefer reversible, well-understood actions.
- State blast radius and rollback before acting.
- Do not combine several mitigations when one can be evaluated independently.
- Preserve diagnostic evidence when possible.
- Separate immediate impact reduction from permanent remediation.
Close the investigation
Produce:
- Impact summary.
- Confirmed timeline.
- Root cause with supporting evidence.
- Trigger and contributing factors.
- Mitigation and recovery.
- Detection and response gaps.
- Prioritized follow-up work with owners when known.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
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