OpenSearch Agent Skills

Developers today can go from idea to working prototype in minutes using agentic IDEs like Kiro, Claude Code, and Cursor. But whether you're experimenting with a new idea, building a proof of concept, or running production systems, the experience quickly becomes more complex. Search results don't behave as expected, latency spikes require digging through logs, and deploying to AWS introduces configuration decisions that require deep expertise. Translating high-level intent into query DSLs, index configurations, and multi-step workflows still takes significant time – even with an AI agent at your side.

OpenSearch Agent Skills addresses this by providing a repository of skills that bring OpenSearch intelligence directly into your agent. Each skill encapsulates domain knowledge, best practices, and multi-step execution logic for a specific workflow – so your agent not only gets results, but understands how they were achieved. Skills work with any coding agent that supports the Agent Skills standard, including Kiro, Claude Code, and Cursor.

What you can do with Agent Skills

Build a local search application

The opensearch-launchpad skill brings an intent-driven experience to building and iterating on search applications. It translates natural language requirements or sample data into a fully configured OpenSearch index – with optimized mappings, ingest pipelines, and ML model integrations for keyword, semantic, and hybrid search – and produces a working search experience ready to test and iterate on.

Example prompt:

Build a semantic search application for product documentation

The agent configures the index mappings, sets up an embedding model and ingest pipeline, and returns a working search API and UI – walking you through each decision along the way.

Investigate incidents with log analytics

The log-analytics skill brings agentic intelligence to observability workflows. Instead of manually crafting Piped Processing Language (PPL) queries or piecing together log data across services, you express your intent and the skill handles the complexity – from error pattern detection to anomaly analysis to root cause correlation.

Example prompt:

Investigate why my service is returning 500s and correlate with recent traces

The agent runs PPL queries to surface error patterns and log volume anomalies, then correlates log errors to specific trace IDs for faster root cause analysis – without requiring you to master PPL syntax or manually navigate trace data.

Investigate distributed traces

The trace-analytics skill investigates distributed traces directly within OpenSearch. It identifies slow spans, error spans, and service dependencies, and correlates logs and traces using trace IDs to surface root causes across the full observability stack.

Example prompt:

Which service is causing the p99 latency regression in the checkout flow?

The agent builds a service map, identifies the slow spans, and pinpoints the bottleneck – without requiring you to manually navigate trace data across services.

Deploy OpenSearch to AWS

The aws-setup skill walks your agent through provisioning an OpenSearch Service domain or OpenSearch Serverless collection, configuring access and encryption policies, and connecting your application – with separate guides for managed domains and serverless collections.

Example prompt:

Set up an OpenSearch Serverless collection for my search application

The agent handles provisioning, policy configuration, and validation, guiding you through each step.

Available skills

Skills are organized by category. You can install the complete collection or individual skills:

The project is under active development. For the latest skill list and contribution guidance, see the opensearch-agent-skills repository.

Prerequisites

Prerequisites vary by skill. To use the full collection you need:

Install and use skills

Skills install through the skills CLI, which you invoke with npx. The installer detects your agent and places skill files in the correct location.

To install the entire collection:

npx skills add opensearch-project/opensearch-agent-skills

To install a single skill, use the @skill-name suffix. The --full-depth flag includes all reference material the agent may need for follow-up questions:

npx skills add opensearch-project/opensearch-agent-skills@opensearch-launchpad --full-depth
npx skills add opensearch-project/opensearch-agent-skills@log-analytics --full-depth
npx skills add opensearch-project/opensearch-agent-skills@trace-analytics --full-depth
npx skills add opensearch-project/opensearch-agent-skills@aws-setup --full-depth

Common install options:

After installation, restart your agent so it picks up the new skill files. Then try a prompt such as "I want to build a hybrid search app with OpenSearch." The agent reads the skill instructions and runs the required scripts directly.

The aws-setup skill includes dedicated guides for both OpenSearch Service product families. For Amazon OpenSearch Service managed domains, the skill walks through creating a domain, configuring access policies, and connecting your application (see Introduction). For OpenSearch Serverless, it covers creating a collection, configuring data access and encryption policies, and ingesting data (see Amazon OpenSearch Serverless). For interactive queries against a running cluster, pair the skills with the OpenSearch MCP server.

Security considerations

When you install and run a skill, your agent executes the scripts and commands it describes. Treat skills as you would any third-party developer tool:

Additional resources