技能目录

为 AI Agent 发现可复用技能。

按任务搜索真实的 GitHub 技能,并在使用前查看 Stars、信任、审计、分类和安装路径。

每个推荐都保留与其仓库、审计和安装路径的明确关联。

搜索结果: module

英文目录

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
信任
分类: browser-automation审计

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

9.0K
Stars
86/100
信任
分类: media-automation审计

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

5.0K
Stars
80/100
信任
分类: devops审计

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
信任
分类: data-analysis审计

TypeORM module for Nest framework (node.js) 🍇

2.1K
Stars
76/100
信任
分类: data-analysis审计

Pdf creation module for dart/flutter

1.5K
Stars
77/100
信任
分类: document-processing审计

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

146
Stars
76/100
信任
分类: utility审计

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
信任
分类: coding-agents审计

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
信任
分类: design-creative审计

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
信任
分类: research审计