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: novel-categories

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

🔒 Consolidating and extending hosts files from several well-curated sources. Optionally pick extensions for porn, social media, and other categories.

31K
Stars
87/100
信頼
カテゴリ: legal-compliance監査

视觉小说翻译器 / Visual Novel Translator

12K
Stars
82/100
信頼
カテゴリ: document-processing監査

A collection of agent skills for AI short-drama production, covering character bibles, outlines, art bibles, scripts, and storyboards, designed for Claude Code and Codex.

1.6K
Stars
86/100
信頼
カテゴリ: design-creative監査

Autonomous novel writing AI Agent — agents write, audit, and revise novels with human review gates

7.6K
Stars
83/100
信頼
カテゴリ: agent-frameworks監査

A novel Android app store focused on security, privacy, and usability

2.2K
Stars
81/100
信頼
カテゴリ: legal-compliance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

面向长篇小说创作的 AI Native 开源系统,用 Agent、世界观、写法引擎、RAG 和整本生产工作流,帮助新手从一句灵感走到完整小说。AI-native engine for end-to-end novel creation — from idea to full chapters, with structured planning, worldbuilding, and agent-driven workflows.

1.6K
Stars
76/100
信頼
カテゴリ: rag-knowledge監査

A novel Multimodal Large Language Model (MLLM) architecture, designed to structurally align visual and textual embeddings.

1.5K
Stars
84/100
信頼
カテゴリ: support-automation監査

🤖 The most comprehensive list of AI agents, frameworks & tools in 2026. 300+ resources · 20+ categories · Updated monthly.

1.4K
Stars
76/100
信頼
カテゴリ: agent-frameworks監査

Objectron is a dataset of short, object-centric video clips. In addition, the videos also contain AR session metadata including camera poses, sparse point-clouds and planes. In each video, the camera moves around and above the object and captures it from different views. Each object is annotated with a 3D bounding box. The 3D bounding box describes the object’s position, orientation, and dimensions. The dataset contains about 15K annotated video clips and 4M annotated images in the following categories: bikes, books, bottles, cameras, cereal boxes, chairs, cups, laptops, and shoes

2.3K
Stars
75/100
信頼
カテゴリ: robotics-iot監査

Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.

51K
Stars
83/100
信頼
カテゴリ: research監査