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: fixed-wing

英語版ディレクトリ

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

Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading), reduced-motion, or the design foundations (feedback, spatial consistency, restraint) behind Apple-style interfaces.

18K
Stars
87/100
信頼
カテゴリ: design-creative監査

A Codex skill for generating minimal zine-style editorial poster prompts and images.

6.3K
Stars
83/100
信頼
カテゴリ: design-creative監査

A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.

3.1K
Stars
80/100
信頼
カテゴリ: finance監査

Nelm is a Helm 4 alternative. It is a Kubernetes deployment tool that manages Helm Charts and deploys them to Kubernetes. The Nelm goal is to provide a modern alternative to Helm, with long-standing issues fixed and many new major features introduced.

1.1K
Stars
75/100
信頼
カテゴリ: devops監査

Opinionated Oxlint rules packaged as an installable agent skill for rejecting low-evidence TypeScript/JavaScript patterns.

645
Stars
85/100
信頼
カテゴリ: coding-agents監査

A platform-neutral analytical skill that profiles messy data, selects adaptive methods, and produces source-backed visual reports for high-stakes decisions.

204
Stars
77/100
信頼
カテゴリ: data監査

Self-contained floating chat widget with welcome screen, social links, meeting button, and message input. Single HTML file, zero dependencies.

90K
Stars
72/100
信頼
カテゴリ: design-creative監査

Admin / analytics dashboard in a single HTML file. Fixed left sidebar, top bar with user/search, main grid of KPI cards and one or two charts. Use when the brief asks for a "dashboard", "admin", "analytics", or "control panel" screen.

90K
Stars
72/100
信頼
カテゴリ: research監査

Terminal-first, knowledge-grounded multi-agent software delivery pipeline: scope requirements, implement changes, run tests, and gate pull requests with deterministic QA and ensemble code review.

137
Stars
73/100
信頼
カテゴリ: utility監査

Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.

34K
Stars
77/100
信頼
カテゴリ: research監査

Official GSAP skill for gsap.utils — clamp, mapRange, normalize, interpolate, random, snap, toArray, wrap, pipe. Use when the user asks about gsap.utils, clamp, mapRange, random, snap, toArray, wrap, or helper utilities in GSAP.

14K
Stars
76/100
信頼
カテゴリ: automation監査