elasticsearch-anomaly-detection-explainer
Explain Elasticsearch ML anomaly detection scores, model behavior, and result interpretation. Use when the user asks why a score is high or low, how the model learns, what the numbers mean, or how to troubleshoot unexpected anomaly scores.
Install
With your agent
Install OMGSkills skill "elastic/claude-plugin:skills/elasticsearch/elasticsearch-anomaly-detection-explainer" into this agent's normal skills directory: call the OMGSkills MCP get_install_plan tool for your agent and run the script it returns (it installs only the pinned commit and verifies SKILL.md), and stop if MCP or the pin is unavailable. Do not overwrite or change existing skills without asking me.
Manual command
git clone https://github.com/elastic/claude-plugin /tmp/claude-plugin && ln -s /tmp/claude-plugin/skills/elasticsearch/elasticsearch-anomaly-detection-explainer ~/.claude/skills/elasticsearch-anomaly-detection-explainer
From README
Anomaly Detection Score Explainer Explain anomaly scores, model behavior, and why results look the way they do. Use the ML REST API for job config and the standard search API against .ml-anomalies- for results — no ES|QL, fully compatible with Elastic Serverless. For job lifecycle (create, start, stop), use the elasticsearch-anomaly-detection skill. Environment Configuration This skill executes Elasticsearch operations through the elastic CLI. If the elastic CLI is not installed, tell the user what it is needed for. Do not guess credentials, call the HTTP API directly, or attempt other workarounds. This skill references operations in HTTP-shorthand form (e.g., GET /, GET /cat/indices, GET /{index}/mapping, GET /{index}/settings/index.mode, POST /query). The Operations table at the end of this document maps each shorthand to the equivalent elastic CLI command — always use the CLI rather than calling the HTTP API directly.
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