6 skills found
Elastic ML anomaly detection skill — investigation/RCA, score explanation, job operations (create, datafeed, start/stop, results), and troubleshooting (missing docs, memory limits, datafeed health, lifecycle). Operates against Kibana Agent Builder MCP tools (`ad_*`) on `.ml-anomalies-*`, `.ml-config`, `.ml-notifications-*`, `.ml-annotations-*`. Use when answering "what broke?"/"which entity?"/RCA, "why is score high/low?"/renormalization, "datafeed stopped"/"memory limit", or any request to set
Create Vega and Vega-Lite visualizations with ES|QL data sources in Kibana. Use when building custom charts, dashboards, or programmatic panel layouts beyond standard Lens charts.
Create and manage Kibana connectors for Slack, PagerDuty, Jira, webhooks, and more via REST API or Terraform. Use when configuring third-party integrations or managing connectors as code.
List, inspect, enable, disable, and resync Kibana Streams via the REST API. Use when the user needs stream details, ingest/query settings, queries, significant events, or attachments.
Create and manage Kibana alerting rules via REST API or Terraform. Use when creating, updating, or managing rule lifecycle (enable, disable, mute, snooze) or rules-as-code workflows.
Create and manage Kibana Dashboards and visualizations. Use when you need to define dashboards and visualizations declaratively, version control them, or automate their deployment.
