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Builds search applications and queries log analytics data with OpenSearch. Routes to sub-skills for search, log analytics, trace analytics, and AWS deployment.
How this skill is triggered — by the user, by Claude, or both
Slash command
/opensearch-agent-skills:opensearch-skillsThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
This is the top-level skill for OpenSearch. It contains three category skills that can also be installed and used independently:
cli-reference.mdcloud/aws-setup/aos/domain-01-provision.mdcloud/aws-setup/aos/domain-02-deploy-search.mdcloud/aws-setup/aos/domain-03-agentic-setup.mdcloud/aws-setup/aoss/aoss-nextgen-provisioning/ADVANCED.mdcloud/aws-setup/aoss/aoss-nextgen-provisioning/DEPROVISION.mdcloud/aws-setup/aoss/aoss-nextgen-provisioning/ERRORS.mdcloud/aws-setup/aoss/serverless-02-deploy-search.mdcloud/aws-setup/aoss/serverless-04-agentic-setup.mdcloud/aws-setup/reference.mdobservability/log-analytics/log-analytics.mdobservability/ppl-reference.mdobservability/trace-analytics/traces.mdscripts/lib/__init__.pyscripts/lib/client.pyscripts/lib/evaluate.pyscripts/lib/operations.pyscripts/lib/samples.pyscripts/lib/search.pyscripts/lib/ui.pyThis is the top-level skill for OpenSearch. It contains three category skills that can also be installed and used independently:
| Category | Skill | Install individually |
|---|---|---|
| search | opensearch-launchpad | npx skills add opensearch-project/opensearch-agent-skills@opensearch-launchpad --full-depth |
| observability | log-analytics | npx skills add opensearch-project/opensearch-agent-skills@log-analytics --full-depth |
| observability | trace-analytics | npx skills add opensearch-project/opensearch-agent-skills@trace-analytics --full-depth |
| cloud | aws-setup | npx skills add opensearch-project/opensearch-agent-skills@aws-setup --full-depth |
Route to the right skill based on user intent:
| User Intent | Skill |
|---|---|
| Build a search app, set up an index, choose a search strategy | opensearch-launchpad |
| Analyze logs, query with PPL, discover error patterns | log-analytics |
| Investigate traces, debug spans, analyze service maps | trace-analytics |
| Deploy to AWS, provision a domain or collection | aws-setup |
| General OpenSearch question | Search docs first, then route to the relevant skill |
If the user's intent spans multiple skills (e.g., "build a search app and deploy it to AWS"), start with the appropriate skill and transition to the next when ready.
All skills share these resources:
scripts/opensearch_ops.py — CLI for all OpenSearch operationsscripts/start_opensearch.sh — Start a local OpenSearch clusterscripts/ui/ — React frontend served on port 8765bash scripts/start_opensearch.sh
uv run python scripts/opensearch_ops.py <command> [options]
uv run python scripts/opensearch_ops.py --help
{
"mcpServers": {
"ddg-search": {
"command": "uvx",
"args": ["duckduckgo-mcp-server"]
},
"awslabs.aws-api-mcp-server": {
"command": "uvx",
"args": ["awslabs.aws-api-mcp-server@latest"],
"env": { "FASTMCP_LOG_LEVEL": "ERROR" }
},
"aws-knowledge-mcp-server": {
"command": "uvx",
"args": ["fastmcp", "run", "https://knowledge-mcp.global.api.aws"],
"env": { "FASTMCP_LOG_LEVEL": "ERROR" }
},
"opensearch-mcp-server": {
"command": "uvx",
"args": ["opensearch-mcp-server-py@latest"],
"env": { "FASTMCP_LOG_LEVEL": "ERROR" }
}
}
}
Before using any MCP tool, check if the server is available. If missing:
.kiro/settings/mcp.json.cursor/mcp.json.mcp.json.vscode/mcp.json~/.codeium/windsurf/mcp_config.json{"mcpServers": {}}).uv run python scripts/opensearch_ops.py search-docs --query "<your query>"
uv run python scripts/opensearch_ops.py search-docs --query "<query>" --site docs.aws.amazon.com
npx claudepluginhub opensearch-project/opensearch-agent-skillsQueries OpenSearch logs using PPL for severity filtering, trace correlation, error patterns, and volume analysis in OTEL indices.
Guides Azure AI Search development with expertise on indexes, skillsets, semantic/vector search, RAG patterns, troubleshooting, architecture, and deployment.
Queries and analyzes application logs stored in Elasticsearch. Supports search, count, filtering by trace IDs, and field extraction for debugging requests and error analysis.