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: length-extrapolation

英語版ディレクトリ

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

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

A ComfyUI custom node integration for local multi-engine multi-language Text-to-Speech and Voice Conversion. Supports: RVC, Echo-TTS, Qwen3-TTS, Cozy Voice 3, Step Audio EditX, IndexTTS-2, Chatterbox (classic and multilingual), F5-TTS, Higgs Audio 2, 3, and VibeVoice with unlimited text length, SRT timing, Character support, and many audio tools

1.0K
Stars
76/100
信頼
カテゴリ: media-automation監査

A documentation page — inline-start nav, scrollable article body, inline-end table of contents. Use when the brief mentions "docs", "documentation", "guide", "API reference", or "tutorial".

91K
Stars
75/100
信頼
カテゴリ: design-creative監査

A long-form article / blog post — masthead, hero image placeholder, article body with figures and pull quotes, author byline, related posts. Use when the brief asks for "blog", "article", "post", "essay", or "case study".

90K
Stars
77/100
信頼
カテゴリ: design-creative監査

A collection of reusable agent skills for Dart and Flutter development, following the Agent Skills standard.

139
Stars
77/100
信頼
カテゴリ: coding-agents監査

Use when reviewing a PR, API, IPC channel, endpoint, parameter, type, config, or architectural extension point that adds or expands shared surface area, especially when consumers are absent, exports are unused or speculative, existing consumers are hack-heavy, forward compatibility is claimed, or multiple similar APIs may express one demand.

51K
Stars
78/100
信頼
カテゴリ: research監査

React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.

51K
Stars
68/100
信頼
カテゴリ: design-creative監査

Observe the user's screen via screenpipe, detect repeated research workflows, match them against existing scientific-agent-skills, and draft new skills (or composition recipes that chain existing ones) for the patterns not yet covered. Use when the user asks to analyze their recent work and propose skills based on what they actually do. Requires the screenpipe daemon (https://github.com/screenpipe/screenpipe) running locally on port 3030 — the skill has no other data source and will refuse to run if screenpipe is unreachable. All detection runs locally; only redacted cluster summaries reach the LLM.

34K
Stars
70/100
信頼
カテゴリ: research監査

Generate real-timestamp subtitle artifacts from final narration audio or merged video with a caption quality gate.

1.3K
Stars
66/100
信頼
カテゴリ: Video Creation監査

We present StableAvatar, the first end-to-end video diffusion transformer, which synthesizes infinite-length high-quality audio-driven avatar videos without any post-processing, conditioned on a reference image and audio.

1.2K
Stars
76/100
信頼
カテゴリ: media-automation監査

Official implementation for "RIFLEx: A Free Lunch for Length Extrapolation in Video Diffusion Transformers" (ICML 2025) , UltraViCo (ICLR 2026) and UltraImage

808
Stars
73/100
信頼
カテゴリ: media-automation監査