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フォーク26

更新日2026年7月15日 18:36

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.

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opensearch-project

opensearch-project/opensearch-agent-skills

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Search

Category skill for building search applications with OpenSearch.

Skills

Skill	Description
opensearch-launchpad	End-to-end search application builder — from sample data to a running search UI with BM25, semantic, hybrid, or agentic search

When to Use

Read opensearch-launchpad/SKILL.md when the user wants to:

Build a new search application
Set up an OpenSearch index with a specific search strategy
Deploy ML models for semantic or hybrid search
Evaluate and tune search quality
Process documents (PDF, DOCX) for search ingestion

このリポジトリの他の Skills

同じリポジトリ

aoss-nextgen-provisioning

opensearch-project/opensearch-agent-skills

Use when provisioning or deprovisioning OpenSearch Serverless collections, creating collection groups, setting up AOSS NextGen, or tearing down AOSS resources

2026-07-1537

aws-setup

opensearch-project/opensearch-agent-skills

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.

2026-07-1537

cloud

opensearch-project/opensearch-agent-skills

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.

2026-07-1537

log-analytics

opensearch-project/opensearch-agent-skills

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.

2026-07-1537

observability

opensearch-project/opensearch-agent-skills

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.

2026-07-1537

trace-analytics

opensearch-project/opensearch-agent-skills

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.

2026-07-1537

name	search
description	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.
compatibility	Requires Docker and uv.
metadata	{"author":"opensearch-project","version":"2.0"}

Search

Category skill for building search applications with OpenSearch.

Skills

Skill	Description
opensearch-launchpad	End-to-end search application builder — from sample data to a running search UI with BM25, semantic, hybrid, or agentic search

When to Use

Read opensearch-launchpad/SKILL.md when the user wants to:

Build a new search application
Set up an OpenSearch index with a specific search strategy
Deploy ML models for semantic or hybrid search
Evaluate and tune search quality
Process documents (PDF, DOCX) for search ingestion