Build search applications and query log analytics data with OpenSearch. Use this skill when the user mentions OpenSearch, search app, index setup, search architecture, semantic search, vector search, hybrid search, BM25, dense vector, sparse vector, agentic search, RAG, embeddings, KNN, PDF ingestio

OpenSearch Skills This is the top level skill for OpenSearch. It contains four category skills that can also be installed and used independently: Category Skill Install individually [search](search/SKILL.md) [opensearch launchpad](search/opensearch launchpad/SKILL.md) npx skills add opensearch project/opensearch agent skills@opensearch launchpad full depth [observability](observability/SKILL.md) [log analytics](observability/log analytics/SKILL.md) npx skills add opensearch project/opensearch agent skills@log analytics full depth [observability](observability/SKILL.md) [trace analytics](observability/trace analytics/SKILL.md) npx skills add opensearch project/opensearch agent skills@trace analytics full depth [cloud](cloud/SKILL.md) [aws setup](cloud/aws setup/SKILL.md) npx skills add opensearch project/opensearch agent skills@aws setup full depth [cloud](cloud/SKILL.md) [aiven setup](cloud/aiven setup/SKILL.md) npx skills add opensearch project/opensearch agent skills@aiven setup full depth [ingest](ingest/SKILL.md) [document processing](ingest/document processing/SKILL.md) npx skills add opensearch project/opensearch agent skills@document processing full depth [cloud](cloud/SKILL.md) [managed ingestion service](cloud/managed ingestion service/SKILL.md) npx skills add opensearch project/opensearch agent skills@managed ingestion service full depth Routing 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](search/opensearch launchpad/SKILL.md) Analyze logs, query with PPL, discover error patterns [log analytics](observability/log analytics/SKILL.md) Investigate traces, debug spans, analyze service maps [trace analytics](observability/trace analytics/SKILL.md) Deploy to AWS, provision a domain or collection [aws setup](cloud/aws setup/SKILL.md) Deploy to Aiven, provision a managed OpenSearch service [aiven setup](cloud/aiven setup/SKILL.md) Process documents into chunks (PDF/DOCX → JSONL) [document processing](ingest/document processing/SKILL.md) Ingest chunks at scale via OSIS, S3 to AOS/AOSS [managed ingestion service](cloud/managed ingestion service/SKILL.md) 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 Aiven"), start with the appropriate skill and transition to the next when ready. Feedback Collection (Required Behavior) This applies to ALL skills in this collection — opensearch launchpad, log analytics, trace analytics, aws setup, aiven setup, document processing, and managed ingestion service. Regardless of which skill is active, you MUST follow these rules. You MUST proactively collect feedback during every interaction. This is not optional — treat it as a core part of the workflow, not an afterthought. Rules 1. Monitor continuously — watch for failures, confusion, and unmet needs throughout the conversation, not just at the end. 2. Offer immediately on failure — when any command errors or a step doesn't work, immediately offer to capture feedback before troubleshooting. 3. Offer on uncertainty — if you're unsure how to proceed or the skill doesn't cover the user's request, flag it as a potential gap and offer to submit. 4. Ask at natural breakpoints — after completing a major phase (not just at the very end), ask "Is this working as expected? Any friction so far?" 5. Always ask at end — when the user says they're done or the workflow completes, ask for a 1 5 rating. 6. Never send without consent — show the preview, get explicit "yes". Triggers When What to do Command returns non zero exit or error → Immediately: "That failed. Can I capture this as feedback?" User says "that's not what I wanted" / "this is confusing" / expresses frustration → "Sounds like friction. Can I note what went wrong?" User asks for something you can't do → "This isn't supported yet. Can I flag this as a feature gap?" A workaround is needed (something should be simpler) → "That was more steps than it should be. Can I flag this as friction?" Major phase completes → "How's it going so far? Any issues?" User says "done" or workflow ends → "How was the overall experience? (1 5)" How to Submit Requires uv installed (for running Python scripts) 1. Compose the feedback (type + context). 2. Show preview to user. 3. Ask: "May I submit this anonymous feedback?" 4. On consent: Feedback Types failure — A command or step produced an error gap — User needs something the skill doesn't support friction — Workflow was confusing, slow, or required workarounds success — Workflow completed, user satisfied Shared Resources All skills share these resources: Scripts : scripts/opensearch ops.py — CLI for all OpenSearch operations Docker bootstrap : scripts/start opensearch.sh — Start a local OpenSearch cluster CLI Reference : [cli reference.md](cli reference.md) — Full command reference with examples Search Builder UI : scripts/ui/ — React frontend served on port 8765 Optional MCP Servers Auto Installing Missing MCP Servers Before using any MCP tool, check if the server is available. If missing: 1. Locate the MCP config file: Kiro: .kiro/settings/mcp.json Cursor: .cursor/mcp.json Claude Code: .mcp.json VS Code (Copilot): .vscode/mcp.json Windsurf: ~/.codeium/windsurf/mcp config.json 2. Read the existing config (or start with {"mcpServers": {}} ). 3. Merge in the missing server entry. Do not overwrite existing entries. 4. Save and inform the user to restart or reconnect MCP servers. Answering OpenSearch Knowledge Questions

opensearch-skills