GITHUB AGENT SKILLS / 技能收录
给你的 AI 助手
装上专业技能
我们从 GitHub 持续收录、审核并分类优质的 Agent Skills，按职业与使用场景整理，复制一行命令即可安装到 Claude Code、Cursor 等智能体。
按职业浏览 Agent Skills
为不同岗位挑选的高频技能
按使用场景浏览 Agent Skills
从你要完成的任务出发
按创作者浏览 Agent Skills
按 GitHub Stars 排序的优秀创作者
Microsoft
@microsoft
openclaw
@openclaw
OpenAI
@openai
The Apache Software Foundation
@apache
GitHub
@github
Anthropic
@anthropics
AutoGPT
@Significant-Gravitas
Garry Tan
@garrytan全部 Skills 196852
feature-video
Record a video walkthrough of a feature and add it to the PR description
document-review
This skill should be used to refine brainstorm or plan documents before proceeding to the next workflow step. It applies when a brainstorm or plan document exists and the user wants to improve it.
deploy-docs
Validate and prepare documentation for GitHub Pages deployment
deepen-plan
Enhance a plan with parallel research agents for each section to add depth, best practices, and implementation details
create-agent-skills
Expert guidance for creating Claude Code skills and slash commands. Use when working with SKILL.md files, authoring new skills, improving existing skills, creating slash commands, or understanding skill structure and best practices.
create-agent-skill
Create or edit Claude Code skills with expert guidance on structure and best practices
compound-docs
Capture solved problems as categorized documentation with YAML frontmatter for fast lookup
changelog
Create engaging changelogs for recent merges to main branch
cancel-ralph
Cancel an active ralph loop
brainstorming
This skill should be used before implementing features, building components, or making changes. It guides exploring user intent, approaches, and design decisions before planning. Triggers on "let's brainstorm", "help me think through", "what should we build", "explore approaches", ambiguous feature requests, or when the user's request has multiple valid interpretations that need clarification.
agent-native-architecture
Build applications where agents are first-class citizens. Use this skill when designing autonomous agents, creating MCP tools, implementing self-modifying systems, or building apps where features are outcomes achieved by agents operating in a loop.
agent-browser
Browser automation using Vercel's agent-browser CLI. Use when you need to interact with web pages, fill forms, take screenshots, or scrape data. Alternative to Playwright MCP - uses Bash commands with ref-based element selection. Triggers on "browse website", "fill form", "click button", "take screenshot", "scrape page", "web automation".
tabular-demo
Demo step skill for tabular data.
leakage-demo
Demo knowledge skill about target leakage.
bad-name
Name does not match its folder.
train-test-split
How to split data so the score is honest.
tabular-features
Writes src/features.py with derived features (ratios, logs, interactions) and no target use. Usually right after tabular-eda. Check: run src/features.py, expects data/processed/features.csv.
tabular-export
Writes the shipped code (src/pipeline.py, src/train.py, src/predict.py) from the winning run and trains it. Usually right after evolve-search or tabular-ensemble. Check: run src/train.py, expects models/model.joblib, metric accuracy (classification) or r2 (regression) with a minimum.