agent-skills

Execute ESQL (Elasticsearch Query Language) queries, use when the user wants to query Elasticsearch data, analyze logs, aggregate metrics, explore data, or create charts and dashboards from ESQL results.

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 the user shows intent to build search-related functionality, asks about Elasticsearch-related concepts for their use case, or expresses the need for help getting started with Elasticsearch.

Create and manage Kibana Dashboards and Lens visualizations. Use when you need to define dashboards and visualizations declaratively, version control them, or automate their deployment.

Create, search, update, and manage SOC cases via the Kibana Cases API. Use when tracking incidents, linking alerts to cases, adding investigation notes, or managing triage output.

Create and manage Kibana alerting rules. Use when creating, updating, or managing rule lifecycle (enable, disable, mute, snooze), choosing metric threshold rule types and params, or read-only find/list with tag filters.

Create and manage Kibana Agent Builder agents and custom tools. Use when asked to create, update, delete, test, or inspect agents or tools in Agent Builder, or when the user wants to understand what agents or tools already exist.

Answer questions about LLM and agentic-application behavior from data already ingested into Elastic: latency and error rate, token and cost utilization, response quality and guardrail events, and agentic call-chain orchestration. Use when the user asks about LLM monitoring, GenAI observability, token spend or AI cost, model latency, prompt or guardrail failures, or how an agent's tool-call chain executed.

Triage Elastic Security alerts — gather context, classify threats, create cases, and acknowledge. Use when triaging alerts, performing SOC analysis, or investigating detections.

Create, tune, and manage Elastic Security detection rules (SIEM and Endpoint). Use for false positives, exceptions, new coverage, noisy rules, or rule management via Kibana API.

Generate sample security events, attack scenarios, and synthetic alerts for Elastic Security. Use when demoing, populating dashboards, testing detection rules, or setting up a POC.

Search and filter Observability logs using ESQL. Use when investigating log spikes, errors, or anomalies; getting volume and trends; or drilling into services or containers during incidents.

Elastic ML anomaly detection — investigation/RCA, score explanation, job lifecycle troubleshooting, and job operations. Use when answering "what broke?"/"which entity?"/RCA, "why is score high/low?"/renormalization, "datafeed stopped"/"memory limit"/hardlimit, or configuring ML anomaly detection jobs. Reads results from .ml-anomalies- and job state from ML REST APIs.

Investigate Kubernetes workload, node, and control-plane issues using OTel telemetry (EDOT). Use when diagnosing pod failures (CrashLoopBackOff, OOMKilled, Error), node pressure, resource exhaustion, image pull failures, admission rejections, autoscaling anomalies, or correlating K8s state with application signals. OTel ingest path only — the legacy ECS Kubernetes integration shape is out of scope.

Authenticate to Elasticsearch using native, file-based, LDAP/AD, SAML, OIDC, Kerberos, JWT, or certificate realms. Use when connecting with credentials, choosing a realm, or managing API keys. Assumes the target realms are already configured.

Ingest and transform data files (CSV/JSON/Parquet/Arrow IPC) into Elasticsearch with stream processing and custom transforms. Use when loading files or batch importing data — not for reindexing, general ingest pipeline design, or bulk API patterns.

Manage Elasticsearch RBAC: native users, roles, role mappings, document- and field-level security. Use when creating users or roles, assigning privileges, or mapping external realms like LDAP/SAML.

Enable, configure, and query Elasticsearch security audit logs. Use when the task involves audit logging setup, event filtering, or investigating security incidents like failed logins.

List, inspect, enable, disable, and resync Kibana Streams via the REST API. Use when the user needs stream details, ingest settings, query-stream settings, or linked attachments (dashboards, rules, SLOs).

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.

Create Vega and Vega-Lite visualizations with ESQL data sources in Kibana. Use when building custom charts, dashboards, or programmatic panel layouts beyond standard Lens charts.

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.

Assess APM service health using SLOs, alerts, ML, throughput, latency, error rate, and dependencies. Use when checking service status, performance, or when the user asks about service health.

Enable and configure Kibana audit logging for saved object access, logins, and space operations. Use when setting up Kibana audit, filtering events, or correlating Kibana and ES audit logs.

Create and manage SLOs in Elastic Observability using the Kibana API. Use when defining SLIs, setting error budgets, or managing SLO lifecycle.

Manage Serverless network security (traffic filters): create, update, and delete IP filters and AWS PrivateLink VPC filters. Use when restricting network access or configuring private connectivity.

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.

Configures Elastic Cloud authentication and environment defaults. Use when setting up ECAPIKEY, configuring Cloud API access, or when another cloud skill requires credentials.

Instrument a Python application with the Elastic Distribution of OpenTelemetry (EDOT) Python agent for automatic tracing, metrics, and logs. Use when adding observability to a Python service that has no existing APM agent.

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.

Instrument a Java application with the Elastic Distribution of OpenTelemetry (EDOT) Java agent for automatic tracing, metrics, and logs. Use when adding observability to a Java service that has no existing APM agent.

Instrument a .NET application with the Elastic Distribution of OpenTelemetry (EDOT) .NET SDK for automatic tracing, metrics, and logs. Use when adding observability to a .NET service that has no existing APM agent.

Migrate a .NET application from the classic Elastic APM .NET agent to the EDOT .NET SDK. Use when switching from Elastic.Apm. packages to Elastic.OpenTelemetry.

Manage Elastic Cloud organization access: invite users, assign roles to Serverless projects, and create or revoke Cloud API keys. Use when granting, modifying, or auditing user access.

Migrate a Python application from the classic Elastic APM Python agent to the EDOT Python agent. Use when switching from elastic-apm to elastic-opentelemetry.

Migrate a Java application from the classic Elastic APM Java agent to the EDOT Java agent. Use when switching from elastic-apm-agent.jar to elastic-otel-javaagent.jar.

Author, validate, test, run, and inspect Elastic Workflow YAML definitions. Use when the user wants to turn natural language into a Kibana workflow, fix workflow YAML, understand triggers or steps, or run a quick test loop against a real Kibana.

Design and review Elasticsearch index mappings for stated access patterns: correct field types, text+keyword multi-fields, docvalues tuning, mapping-explosion avoidance, and explicit shard settings. Use when creating a new index, reviewing a mapping for storage or query performance, fixing wrong field types, or when the user asks which type to use for search, filter, sort, or aggregation on a field.

Diagnose slow Elasticsearch Query DSL searches and propose measured fixes. Use when a search is slow, profile output shows an expensive clause, exact-match filters sit in scoring context, or leading wildcards dominate latency. Ground every recommendation in search profiling — move non-scoring clauses to filter context, eliminate leading wildcards, and re-profile to confirm improvement.

Improve Elasticsearch search relevance for content and catalog indices: pin or promote results with query rules (correct rule type, criteria, and rule-query wiring) and tune organic ranking with multimatch, field boosts, and analysis grounded in the index mapping. Use when search results rank poorly, a specific document must appear first for a query, or the user asks to tune full-text matching — not for ESQL analytics, index ingest, or cluster health.

Load CSV and JSON files into Elasticsearch indices using the bulk API and explicit mappings when field types matter. Use when batch-importing local files, converting CSV rows or JSON arrays to NDJSON bulk format, or verifying document counts and mappings after ingest — not for Logstash pipelines, Beats, custom scripts, or index-to-index reindex.

Diagnose a non-green Elasticsearch cluster and surface the single most likely cause with remediation. Use when an operator reports yellow or red status, unassigned shards, allocation failures, or wants read-only triage before deeper investigation. Teaches replica-vs-primary impact, allocation decider classification, and data-loss awareness.

Guide Elasticsearch reindex for performance: local and remote, slicing, throttling, task API. Use when copying or migrating indices, changing mappings, or transforming during reindex.

Triage a degraded or suspect service end to end: read SLO status and burn rate, check active alerting rules and ML anomalies, measure throughput, latency, and error rate, assess dependency health and infrastructure saturation, and funnel logs down to the failures that explain it. Use when someone asks whether a service is healthy, why it is slow or erroring, what is in its logs, or which attribute distinguishes the requests that are failing. Also use when someone asks for the query behind any of those signals — throughput, latency percentiles, error rate, dependency health, or log volume — over APM/OTel traces, metrics, or logs.

Create and manage Elastic ML anomaly detection jobs via the API. Use when setting up jobs on an index or data stream, configuring jobs and datafeeds, or opening, starting, or stopping them.

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.

Onboard an application into Elastic Observability with the Elastic Distribution of OpenTelemetry (EDOT): route on language and runtime, detect and replace a classic Elastic APM agent, apply the required OTLP configuration, and then verify with ESQL that traces, metrics, and logs actually arrive under the expected service name. Use when adding observability to a service, migrating off the classic Elastic APM agent, or debugging why an instrumented service is not showing up in Elastic.

Design and operate service reliability targets in Elastic Observability: choose an SLI type and a defensible target, pick a time window and budgeting method, create and maintain SLOs through the Kibana API, attach burn-rate alert rules, and decide when an SLO is the wrong instrument and a threshold rule, anomaly job, or synthetics monitor is right. Use when defining or reviewing SLOs and error budgets, tuning burn-rate alerting, reducing alert noise, or setting up availability monitoring for a user-facing endpoint.

Onboard an Elastic Cloud organization: configure the elastic CLI's Cloud context and API key, establish a default region, then invite users, assign predefined or custom Serverless project roles, and create or revoke Cloud API keys. Use when setting up Cloud authentication or when granting, modifying, or auditing user access to an organization and its projects.

Provision and operate Elastic Cloud infrastructure: create, connect to, update, and delete Serverless projects (Elasticsearch, Observability, Security); manage traffic filters (IP and AWS PrivateLink network security); and manage the lifecycle of Elastic Cloud Hosted deployments. Use when creating or performing day-2 operations on serverless projects or hosted deployments, or restricting their network access.