ml-anomalies
Skill17 starsChanged 7 months agoLicence not identifiedView on GitHub
Query Elastic ML anomaly detection results to understand what's behaving unusually, why, and how badly. Use when the user asks "what's anomalous", "is anything unusual happening", "why is X slow/spiking", "show me the weirdness", or mentions memory growth, CPU spikes, restart patterns, unusual latency, unexpected error rates, or drift from typical behavior. Also trigger for "ML anomalies", "anomaly detection", "Elastic ML", "what does ML think", or when the user wants to understand behavior that deviates from baseline. The tool opens an inline explainer view with a severity gauge, plain-English narrative, and per-entity deviation breakdown — so the agent should USE the visualization, not just dump JSON.
In this repository5 other files it gives its agents.
- apm-health-summarySkill
- apm-service-dependenciesSkill
- k8s-blast-radiusSkill
- manage-alertsSkill
- observeSkill
The file
We split this skill into the rules it gives an agent
9 rules. About 0 are common, 6 are distinctive, and 3 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈6
Distinctive · estimate
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
The licence could not be identified — read it at the source. We count its rules but don't quote them. Read them on GitHub.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Does it work?
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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.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.