Works with the AI tools you already use
Production Incident Triage Starter
Turn a rough production incident report into a scoped first-look brief with facts, unknowns, severity signals, next checks, and a clean handoff.
Free
See it in action
You say
At 14:07 UTC checkout latency rose from 400 ms to 8 s. A deployment finished at 13:58. Error rate increased only in eu-west, and some customers report duplicate refresh attempts. We have one timeout graph and 30 sanitized log lines, but no confirmed root cause. Build a first-look triage brief and safe next checks. Do not access production or invent a fix.
Your agent does
First-look triage: the regional latency increase and deployment timing are facts; deployment causality and duplicate-attempt impact remain unproven. Preserve the timeline, compare changed versus unchanged regions, check timeout/retry ownership, quantify affected requests, and hand off to the appropriate reliability or debugging skill once evidence identifies the failure class.
About this skill
The problem
Initial incident reports are often a chaotic mix of conflicting logs, team theories, and fragmented timestamps. Without a clear triage, engineers waste time chasing red herrings or confusing correlation with actual causality.
What it does
- Separates observed facts from unverified hypotheses and team assumptions.
- Normalizes incident timelines and identifies critical missing data intervals.
- Classifies impact signals based strictly on provided telemetry and reports.
- Generates a list of safe, low-risk checks to disprove leading theories.
- Maps findings to specific specialist roles for efficient handoff.
Why this beats prompting it yourself
General-purpose models often hallucinate root causes or conflate timing with proof. This skill enforces a strict diagnostic discipline that prevents premature conclusions and ensures your next investigation step is based on evidence rather than intuition.
Use cases
- Synthesizing fragmented reports from multiple teams during an active outage.
- Standardizing the first-look brief before escalating to senior SREs.
- Mapping out safe diagnostic steps when deployment timing is known but impact is not.
- Converting raw log dumps and alerts into a structured status report for stakeholders.
Known limitations
This tool performs no external actions and cannot access production environments. It relies entirely on sanitized material provided by the user.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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