Skill 디렉토리

AI Agent를 위한 재사용 가능한 Skill을 찾으세요.

작업으로 실제 GitHub Skill을 검색하고 사용 전에 Stars, 신뢰, 감사, 카테고리, 설치 경로를 확인하세요.

모든 추천은 리포지토리, 감사, 설치 경로와 명확하게 연결됩니다.

검색 결과: module

영문 디렉토리

The complete load testing platform. Everything you need for production-grade load tests. Serverless & distributed. Load test with Playwright. Load test HTTP APIs, GraphQL, WebSocket, and more. Use any Node.js module.

9.0K
Stars
84/100
신뢰
카테고리: browser-automation감사

Speech recognition module for Python, supporting several engines and APIs, online and offline.

9.0K
Stars
86/100
신뢰
카테고리: media-automation감사

Terraform module to create Amazon Elastic Kubernetes (EKS) resources 🇺🇦

5.0K
Stars
80/100
신뢰
카테고리: devops감사

CleverCSV is a Python package for handling messy CSV files. It provides a drop-in replacement for the builtin CSV module with improved dialect detection, and comes with a handy command line application for working with CSV files.

1.3K
Stars
83/100
신뢰
카테고리: data-analysis감사

TypeORM module for Nest framework (node.js) 🍇

2.1K
Stars
76/100
신뢰
카테고리: data-analysis감사

Pdf creation module for dart/flutter

1.5K
Stars
77/100
신뢰
카테고리: document-processing감사

A curated collection of modular agent skills for LLM-based agents, covering research, data analysis, and more.

146
Stars
76/100
신뢰
카테고리: utility감사

A lightweight configuration/utility that prevents coding agents like Codex and Claude Code from over-engineering tasks with unnecessary modules, subagents, dependencies, and hashes.

141
Stars
77/100
신뢰
카테고리: coding-agents감사

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
신뢰
카테고리: design-creative감사

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

34K
Stars
80/100
신뢰
카테고리: research감사