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: expression

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

Glisp is a Lisp-based design tool that combines generative approaches with traditional design methods, empowering artists to discover new forms of expression.

1.2K
Stars
80/100
信頼
カテゴリ: design-creative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

How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.

34K
Stars
78/100
信頼
カテゴリ: design-creative監査

Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.

34K
Stars
77/100
信頼
カテゴリ: data-analysis監査

Real time WebGL and JavaScript library for face tracking, expression detection and animated emoticons in the browser, with both SVG and Three.js demos included 😄

1.1K
Stars
70/100
信頼
カテゴリ: robotics-iot監査

Compile-time dependency injection in Golang using google/wire — wire.NewSet, wire.Build, wire.Bind (interface→concrete), wire.Struct, wire.Value, wire.InterfaceValue, wire.FieldsOf, cleanup functions, //go:build wireinject injector files, and generated wire_gen.go. Apply when using or adopting google/wire, when the codebase imports `github.com/google/wire`, or when wiring an application graph at compile time via `wire.Build`. For runtime DI with reflection, see `samber/cc-skills-golang@golang-uber-dig` skill.

3.0K
Stars
74/100
信頼
カテゴリ: design-creative監査

System.Linq.Expression expressions optimizer. http://thorium.github.io/Linq.Expression.Optimizer

113
Stars
67/100
信頼
カテゴリ: data-analysis監査

A minimalist multi-agent framework for rubost automation of scientific analysis workflows, such as gene expression analysis.

136
Stars
69/100
信頼
カテゴリ: agent-frameworks監査

FantasyPortrait: Enhancing Multi-Character Portrait Animation with Expression-Augmented Diffusion Transformers

508
Stars
66/100
信頼
カテゴリ: media-automation監査

Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision

879
Stars
65/100
信頼
カテゴリ: robotics-iot監査