Skill ディレクトリ

AI Agent のための再利用可能な Skill を見つける。

タスクで実際の GitHub Skill を検索し、利用前に Stars、Trust、監査、カテゴリ、インストール経路を確認できます。

すべての推奨は、リポジトリ、監査、インストール経路に明確につながっています。

検索結果: graph-libraries

英語版ディレクトリ

A tool that converts codebases, SQL schemas, and other files into queryable knowledge graphs for AI coding assistants.

92K
Stars
80/100
信頼
カテゴリ: development監査

AI coding assistant skill (Claude Code, Codex, OpenCode, Cursor, Gemini CLI, and more). Turn any folder of code, SQL schemas, R scripts, shell scripts, docs, papers, images, or videos into a queryable knowledge graph. App code + database schema + infrastructure in one graph.

91K
Stars
80/100
信頼
カテゴリ: rag-knowledge監査

Cognee is the open-source AI memory platform for agents. Give your AI agents persistent long-term memory across sessions with a self-hosted knowledge graph engine.

30K
Stars
87/100
信頼
カテゴリ: rag-knowledge監査

Graphs that teach > graphs that impress. Turn any code into an interactive knowledge graph you can explore, search, and ask questions about. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.

75K
Stars
84/100
信頼
カテゴリ: rag-knowledge監査

Pre-indexed code knowledge graph for Claude Code, Codex, Gemini, Cursor, OpenCode, AntiGravity, Kiro, and Hermes Agent — fewer tokens, fewer tool calls, 100% local

54K
Stars
87/100
信頼
カテゴリ: development監査
Ray87

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

43K
Stars
87/100
信頼
カテゴリ: ml-automation監査

A comprehensive collection of ready-to-use scientific and research skills for AI agents.

31K
Stars
78/100
信頼
カテゴリ: utility監査

A modular graph-based Retrieval-Augmented Generation (RAG) system

34K
Stars
82/100
信頼
カテゴリ: data監査

A scalable, distributed, collaborative, document-graph database, for the realtime web

32K
Stars
76/100
信頼
カテゴリ: coding-agents監査

Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading), reduced-motion, or the design foundations (feedback, spatial consistency, restraint) behind Apple-style interfaces.

18K
Stars
87/100
信頼
カテゴリ: design-creative監査

🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

24K
Stars
82/100
信頼
カテゴリ: data-analysis監査