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: wired

英語版ディレクトリ

Run a 5-dimension expert design review on any HTML artifact in the project — Philosophy / Visual hierarchy / Detail / Functionality / Innovation, each scored 0–10. Outputs a single self-contained HTML report with a radar chart, evidence-backed scores, and three lists: Keep / Fix / Quick-wins. Use when the brief asks for a "design review", "design critique", "5 维度评审", "design audit", or "what's wrong with my design".

90K
Stars
80/100
信頼
カテゴリ: security監査

AI coding agent that edits symbols, not strings. AST surgery, full LSP, and a live code graph wired to memory that resurfaces by file, co-change, and semantics.

778
Stars
65/100
信頼
カテゴリ: agent-frameworks監査

Read when the user asks what OpenKnowledge is, wants to install it on a repository, wants to open or preview a single markdown file that is not part of an OpenKnowledge project, wants to share an OpenKnowledge project with collaborators, asks whether OpenKnowledge supports a particular capability, or asks how `ok init` / `ok cowork` / OK Desktop set up a project. Do NOT load to perform OpenKnowledge reads/writes — the runtime guidance for editing markdown inside an initialized OK project ships as a separate project-local skill installed into each detected agent's skills dir (for example `.claude/skills/open-knowledge/`) whenever `ok init` runs.

3.6K
Stars
70/100
信頼
カテゴリ: design-creative監査

A stage-gated Claude Code skill for academic manuscript writing with discovery, adversarial review, and EN/JP humanizing, packaged as an installable SKILL.md.

49
Stars
70/100
信頼
カテゴリ: research監査

A Claude Code skill that performs 5-layer audits of SwiftUI user flows, detecting workflow bugs and verifying data wiring.

54
Stars
69/100
信頼
カテゴリ: coding-agents監査

Fast native networking primitives for React Native built on Nitro Modules — react-native-nitro-fetch, react-native-nitro-websockets, and react-native-nitro-text-decoder. Covers the fetch API, global replacement, prefetching and cold-start cache warming, the NitroWebSocket class and pre-warming, migrating from React Native's built-in WebSocket, the in-process NetworkInspector, native Perfetto / Instruments tracing, the native TextDecoder, and plugging nitro-fetch into axios via a custom adapter.

161
Stars
68/100
信頼
カテゴリ: research監査

Use when working with TeamCity CI/CD or when a user provides a TeamCity build URL — drives the `teamcity` CLI for builds, logs, jobs, queues, agents, pools, projects, and pipelines.

121
Stars
67/100
信頼
カテゴリ: design-creative監査

Capture-authoring protocol for the main agent. Read on demand when a TRIGGER fires (per `using-karpathy-wiki/SKILL.md`). Defines how to format a capture, how to invoke `bin/wiki capture`, body-size floors, and the subagent-report workflow.

101
Stars
64/100
信頼
カテゴリ: automation監査

Use when generating, planning, authoring, or recording an Epic Web / Epic React style workshop, exercise, tip, or video. Applies Kent C. Dodds' "How to be an Epic Instructor" principles to workshop design, exercise structure, recording, and material delivery, and encodes Epic Web's exercise-comment emoji conventions. Used to generate workshops following https://www.epicweb.dev/get-started. Triggers on "create a workshop", "generate a workshop", "design an exercise", "record a workshop video", "Epic workshop", "Epic Web", "Epic React", or `/epic-workshop`.

39
Stars
57/100
信頼
カテゴリ: design-creative監査

An annotated library of real AI writing failure patterns with full dissection. Use to teach a writer what AI slop actually looks like, diagnose why a specific passage reads as machine-written, or explain the mechanism behind a pattern.

28
Stars
61/100
信頼
カテゴリ: research監査

Bootstrap a new project at a chosen graduation tier (t0 minimum, t1 decision-tracked, t2 full pattern language) following AI-Assisted Project Orchestration best practices. Use when starting a new software project, promoting an existing project to a higher tier, or converting an existing project for AI-assisted development.

14
Stars
58/100
信頼
カテゴリ: automation監査