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Found 36 Skills
Monitor LLMs and agentic apps: performance, token/cost, response quality, and workflow orchestration. Use when the user asks about LLM monitoring, GenAI observability, or AI cost/quality.
Help developers new to Elasticsearch get from zero to a working search experience. Guide them through understanding their intent, mapping their data, and building a search experience with best practices baked in. Use this when developers are new to Elasticsearch and need help getting started with their search use case.
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.
Manages existing Elastic Cloud Serverless projects: list, get, update, delete, reset credentials, resume, and load saved credentials. Connects to existing projects by resolving endpoints and acquiring scoped Elasticsearch API keys. Use when performing day-2 operations on serverless projects, connecting to an existing project, loading or resetting project credentials, or looking up project details.
Diagnose and resolve Elasticsearch security errors: 401/403 failures, TLS problems, expired API keys, role mapping mismatches, and Kibana login issues. Use when the user reports a security error.
Creates Elastic Cloud Serverless projects (Elasticsearch, Observability, or Security) via the REST API, saves credentials to file, and bootstraps a scoped Elasticsearch API key. Use when creating a new serverless project, provisioning a search or observability environment, or spinning up a new Elastic Cloud project.
Create and manage SLOs in Elastic Observability using the Kibana API. Use when defining SLIs, setting error budgets, or managing SLO lifecycle.
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 up or configure an ML anomaly detection job.
Ingest and transform data files (CSV/JSON/Parquet/Arrow IPC) into Elasticsearch with stream processing, custom transforms, and cross-version reindexing. Use when loading files, batch importing data, or migrating indices across versions — not for general ingest pipeline design or bulk API patterns.
Configures Elastic Cloud authentication and environment defaults. Use when setting up EC_API_KEY, configuring Cloud API access, or when another cloud skill requires credentials.
Search and filter Observability logs using ES|QL. Use when investigating log spikes, errors, or anomalies; getting volume and trends; or drilling into services or containers during incidents.
Review an Elastic agent skill against official documentation for accuracy, completeness, and coverage gaps. Use when a writer wants to review, audit, or validate a skill from a repository of agent skills.