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: clothing-agnostic-representation

英語版ディレクトリ

Huashu Design · HTML-native design skill for Claude Code · Claude Code 里 HTML 原生的设计 skill · 高保真原型 / 幻灯片 / 动画 + 20 设计哲学 + 5 维评审 + MP4 导出 · Agent-agnostic

23K
Stars
88/100
信頼
カテゴリ: development監査

AI agents, automations and apps that run your operations. Model agnostic.

28K
Stars
77/100
信頼
カテゴリ: automation監査

A toolchain for building scalable, enterprise-ready component systems on top of TypeScript and Web Component standards. Stencil components can be distributed natively to React, Angular, Vue, (+ more) and traditional web applications from a single, framework-agnostic codebase.

13K
Stars
78/100
信頼
カテゴリ: design-creative監査

Automate your mobile devices with natural language commands - an LLM agnostic mobile Agent 🤖

8.5K
Stars
86/100
信頼
カテゴリ: agent-frameworks監査

Vendor-agnostic orchestration for training, inference and agentic workloads across NVIDIA, AMD, TPU, and Tenstorrent on clouds, Kubernetes, and bare metal.

2.2K
Stars
85/100
信頼
カテゴリ: agent-skills監査
Fn80

The container native, cloud agnostic serverless platform.

5.9K
Stars
80/100
信頼
カテゴリ: devops監査

Framework agnostic sliced/tiled inference + interactive ui + error analysis plots

5.3K
Stars
86/100
信頼
カテゴリ: ml-automation監査

AI skill for OpenClaw & Claude Code — recommend from 10000+ Nano Banana Pro (Gemini) image prompts. Smart search by use case, content remix, sample images.

1.8K
Stars
77/100
信頼
カテゴリ: development監査
Djl80

An Engine-Agnostic Deep Learning Framework in Java

4.8K
Stars
80/100
信頼
カテゴリ: ml-automation監査

A super fast Graph Database uses GraphBLAS under the hood for its sparse adjacency matrix graph representation. Our goal is to provide the best Knowledge Graph for LLM (GraphRAG).

4.6K
Stars
75/100
信頼
カテゴリ: rag-knowledge監査

Cerbos is the open core, language-agnostic, scalable authorization solution that makes user permissions and authorization simple to implement and manage by writing context-aware access control policies for your application resources.

4.5K
Stars
84/100
信頼
カテゴリ: devops監査
Lit85

The Learning Interpretability Tool: Interactively analyze ML models to understand their behavior in an extensible and framework agnostic interface.

3.7K
Stars
85/100
信頼
カテゴリ: ml-automation監査