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: back-in-stock

英語版ディレクトリ

Guidance for distinctive, intentional UI design, typography, visual direction, and non-template-like product interfaces.

171K
Stars
82/100
信頼
カテゴリ: design-creative監査

All Algorithms implemented in Python

222K
Stars
82/100
信頼
カテゴリ: education監査

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

Open-source LLM-friendly web crawler and scraper

73K
Stars
82/100
信頼
カテゴリ: web-automation監査

Review a branch or diff against repository standards and the originating spec in two independent analysis passes.

169K
Stars
86/100
信頼
カテゴリ: coding-agents監査

Break a plan, spec, or conversation into independently actionable tracer-bullet tickets with explicit blocking relationships.

177K
Stars
81/100
信頼
カテゴリ: coding-agents監査

Reverse-lookup glossary that turns a vague description of a web animation or motion effect into its exact term ("the bouncy thing when a popover opens" → Pop in; "the iOS rubber-band scroll" → Rubber-banding). Use when the user asks "what's it called when…", or describes a motion effect without knowing its name and wants the right word to prompt an AI or designer with. For naming an effect, not designing or building one.

17K
Stars
87/100
信頼
カテゴリ: design-creative監査

Tensors and Dynamic neural networks in Python with strong GPU acceleration

101K
Stars
76/100
信頼
カテゴリ: ml-automation監査

🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

162K
Stars
87/100
信頼
カテゴリ: ml-automation監査

Implement work from an approved spec or ticket set, run focused and full tests, invoke code review, and commit the result to the current branch.

176K
Stars
81/100
信頼
カテゴリ: coding-agents監査

Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

97K
Stars
77/100
信頼
カテゴリ: ml-automation監査

React and Next.js performance guidance for writing, reviewing, and refactoring production UI code.

30K
Stars
88/100
信頼
カテゴリ: coding-agents監査