incident
Skill0 starsChanged 2 months agoMITView on GitHub
Diagnoses a production symptom by cross-referencing logs, queues and source code, and returns a diagnosis with evidence. Read-only — it never restarts, purges, replays or deploys. Use when something is stuck, failing or behaving oddly in an environment.
21 other projects use a version of this.
Adopted by
Most recently taken up by
- AsiaOstrich/EngramGraphtheir own version, first seen Nov 8, 2026
- lalulali/vespyrtheir own version, first seen Nov 6, 2026
- AsiaOstrich/universal-dev-standardstheir own version, first seen Nov 1, 2026
- umararshad4/honey-stacktheir own version, first seen Nov 1, 2026
- DataWithBaraa/claude-code-data-engineering-skillstheir own version, first seen Nov 1, 2026
- manusco/resonancetheir own version, first seen Oct 22, 2026
Used with
Projects with it also use runbook, perf and 10 more.
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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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Other versions21 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 21
- AsiaOstrich/universal-dev-standards★ 84same name
- DataWithBaraa/claude-code-data-engineering-skills★ 84same name
- manusco/resonance★ 38same name
- ulises-jeremias/agent-toolkit★ 19same name
- lalulali/vespyr★ 11same name
- NotHarshhaa/devops-skills★ 8same name
- greglas75/zuvo★ 7same name
- umararshad4/honey-stack★ 5same name
- AsiaOstrich/EngramGraph★ 4same name
- gonimar/claude-web-studio★ 4same name
11 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 repository2 other files it gives its agents.
- release-notesSkill
- review-prSkill
The file
We split this skill into the rules it gives an agent
4 rules. 0 are common, 1 is distinctive, and 3 are very specific to this project.
0
Common
Most of the 19 edited versions we read keep these.
1
Distinctive
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 36
Logs around that minute: Search the window, not the last hour:
- Very specific: line 45
Source code last, and only where the trace pointed: Read the handler that threw.
- Very specific: line 83
Never run a mutating command: No purge, no requeue, no restart, no scale, no deploy, no UPDATE.
- Very specific: line 85
Read-only database access only, and always with a LIMIT.
“Common” is measured: kept by at least 6 in 10 of the 19 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
Read-only, without exception. This skill diagnoses. A person decides what to do about it. If the conclusion is "purge the queue", it prints the command and stops.
Fill in the four placeholders below once, for your infrastructure. Half an hour of work, and after that the skill knows your stack.
LOG_QUERY— how you query logs (Loki, CloudWatch, Datadog…)QUEUE_INSPECT— how you list queue depth read-onlySERVICE_MAP— service name to repository pathENVIRONMENTS— what your environments are called
Steps
- Pin down the symptom before touching anything. Which environment, which service, since when, and what a user actually sees. Ask if any of the four is missing. A diagnosis built on a guessed environment is worse than none.
Queues first. Dead letter depth tells you where things stopped, and it is one command:
# QUEUE_INSPECT — read-only listing, no purge, no ackA DLQ that grew from zero at a specific minute is the strongest signal you will get. Note the minute.
Logs around that minute. Search the window, not the last hour:
# LOG_QUERY for {service} between T-5m and T+5mPull a trace id from the first failure and follow that single trace across services. One complete trace beats a thousand log lines.
- Source code last, and only where the trace pointed. Read the handler
that threw. Check whether the error is typed recoverable or terminal
(
standards/01-error-handling.md), because that decides whether the retry behaviour you are seeing is correct. Correlate with what changed. A deploy, a migration, a config change or a dependency bump inside the window:
git log --since='<window start>' --oneline
Output
## Symptom
<what was reported, and what is actually observable>
## Timeline
<T0: first failure — with the evidence line that proves it>
## Root cause
<the specific thing. If uncertain, say so and give the two candidates.>
## Evidence
- <queue/log/commit — each one chaseable by someone else>
## Recommended action — for a human to run
```bash
<the exact command, unexecuted>What would prevent a repeat
<one thing, or nothing>
## Rules
- **Never run a mutating command.** No purge, no requeue, no restart, no scale,
no deploy, no `UPDATE`. Print it, do not run it.
- Read-only database access only, and always with a `LIMIT`.
- **No third-party data in the output.** Ids, not names. Never a payload with
personal data in it.
- "I do not know yet" is a valid diagnosis. A confident wrong root cause costs
more than an honest gap.Does it work?
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