12 skills published by opensearch-project across 1 repository. Together they weigh 269 557 tokens — that is what loading all of them at once would cost you in context.
12 skills 269 557 tokens total
Use when provisioning or deprovisioning OpenSearch Serverless collections, creating collection groups, setting up AOSS NextGen, or tearing down AOSS resources
> Deploy OpenSearch search applications to Amazon OpenSearch Service or Amazon OpenSearch Serverless. Use this skill when the user wants to provision an OpenSearch domain or serverless collection on AWS, deploy search configurations to AWS, set up Bedrock connectors, configure IAM roles for OpenSearch, migrate a local search setup to AWS, or manage Amazon OpenSearch infrastructure. Activate even if the user says AOS, AOSS, OpenSearch Service, serverless collection, Bedrock connector, SigV4, or AWS deployment without mentioning search.
> Deploy OpenSearch search applications to AWS. Use this skill when the user wants to provision an OpenSearch domain or serverless collection on AWS, deploy search configurations, set up Bedrock connectors, configure IAM roles for OpenSearch, or migrate a local setup to Amazon OpenSearch Service or Serverless. Activate even if the user says AOS, AOSS, OpenSearch Service, serverless collection, Bedrock connector, SigV4, or AWS deployment.
> Process unstructured documents (PDF, DOCX, PPTX, XLSX) into search-ready JSONL chunks using Docling. Runs locally — no AWS or cloud services needed. Use this skill when the user wants to prepare documents for indexing, chunk documents, evaluate chunk quality, or convert PDFs to searchable text. Activate even if the user says process documents, chunk my files, prepare for search, or Docling.
> Process unstructured documents into search-ready chunks. Use this skill when the user wants to process PDFs or unstructured documents into JSONL chunks using Docling. Activate even if the user says document processing, chunking, Docling, PDF processing, or chunk quality evaluation. For cloud-scale ingestion via OSIS pipelines, see cloud/managed-ingestion-service.
> Analyze logs in OpenSearch using PPL and Query DSL. Use this skill when the user wants to query logs, analyze error patterns, discover log patterns, check error rates, perform anomaly detection on logs, or investigate application issues through log data. Activate even if the user says log analysis, Fluent Bit, Fluentd, Logstash, syslog, PPL, error rate, anomaly detection, log patterns, or log analytics without mentioning OpenSearch.
> Ingest documents at scale into Amazon OpenSearch using OpenSearch Ingestion Service (OSIS) pipelines. Upload pre-generated JSONL chunks to S3 and OSIS indexes them — optionally using semantic_enrichment in the sink to create the index with ASE automatically. Cloud ingestion — uploading raw PDF/DOCX and letting document_extractor parse them in the cloud — is available via private beta. Use this skill when the user wants to ingest documents into a cloud OpenSearch domain or collection, process documents at full volume beyond local limits, or set up an OSIS pipeline. Activate even if the user says OSIS, ingestion pipeline, document extraction, S3 ingestion, managed ingestion, or cloud processing.
> Analyze logs and investigate traces in OpenSearch. Use this skill when the user wants to query logs with PPL, analyze error patterns, discover log patterns, investigate traces, check stack health, or perform any observability task. Activate even if the user says log analysis, Fluent Bit, Fluentd, Logstash, syslog, traceId, OpenTelemetry, PPL, span, latency, error rate, anomaly detection, or log analytics without mentioning OpenSearch.
> Build search applications with OpenSearch from scratch. Use this skill when the user mentions search app, index setup, search architecture, semantic search, vector search, hybrid search, BM25, dense vector, sparse vector, agentic search, RAG, embeddings, KNN, PDF ingestion, document processing, or any related search topic. Activate even if the user says search quality, evaluation, nDCG, precision, relevance tuning, or search builder without mentioning OpenSearch.
> 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 ingestion, document processing, or any related search topic. Also use for log analytics and observability — when the user wants to set up log ingestion, query logs with PPL, analyze error patterns, set up index lifecycle policies, investigate traces, or check stack health. Activate even if the user says log analysis, Fluent Bit, Fluentd, Logstash, syslog, traceId, OpenTelemetry, or log analytics without mentioning OpenSearch.
> Build search applications with OpenSearch. Use this skill when the user mentions search app, index setup, search architecture, semantic search, vector search, hybrid search, BM25, dense vector, sparse vector, agentic search, RAG, embeddings, KNN, PDF ingestion, document processing, search quality evaluation, or any related search topic.
> Investigate distributed traces and spans in OpenSearch. Use this skill when the user wants to analyze traces, investigate slow spans, find error spans, track agent invocations, measure token usage, reconstruct trace trees, query service maps, or debug distributed systems through trace data. Activate even if the user says traceId, spanId, OpenTelemetry, OTel, distributed tracing, latency, span duration, service map, or trace investigation without mentioning OpenSearch.