Explore AI Agent Skills & Claude Prompts
Discover open-source agent skills for Claude Code, Codex, ChatGPT, and any tool that uses SKILL.md.
Enter through keywords, occupations, creators, and GitHub sources to see what kinds of skills are emerging across domains.
Use the same catalog through the API
Connect 381,784 public skills to your own search, analytics, or agent workflow with the REST API.
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guizang-ppt-skill
by op7418生成横向翻页网页 PPT（单 HTML 文件），含 WebGL 背景、章节幕封、数据大字报、图片网格等模板。提供两种风格：① "电子杂志 × 电子墨水"（衬线 + 流体背景 + 暖色） ② "瑞士国际主义"（无衬线 + 网格点阵 + IKB/柠檬黄/柠檬绿/安全橙高亮）。当用户需要制作分享 / 演讲 / 发布会风格的网页 PPT，或提到"杂志风 PPT"、"瑞士风 PPT"、"Swiss Style"、"horizontal swipe deck"时使用。
humanizer-zh
by op7418去除文本中的 AI 生成痕迹。适用于编辑或审阅文本，使其听起来更自然、更像人类书写。 基于维基百科的"AI 写作特征"综合指南。检测并修复以下模式：夸大的象征意义、 宣传性语言、以 -ing 结尾的肤浅分析、模糊的归因、破折号过度使用、三段式法则、 AI 词汇、否定式排比、过多的连接性短语。
guizang-social-card-skill
by op7418Generate Guizang-style social card image sets and WeChat official account cover pairs from articles, scripts, screenshots, product notes, subtitles, or photos. Use when the user asks for 小红书图文, Rednote/Xiaohongshu images, social cards, carousel images, 3:4 covers, 微信公众号封面, WeChat 21:9 + 1:1 covers, Swiss Style, or magazine-style social images.
claude-to-im
by op7418Bridge THIS Claude Code or Codex session to Telegram, Discord, Feishu/Lark, QQ, or WeChat so the user can chat with Claude from their phone. Use for: setting up, starting, stopping, or diagnosing the claude-to-im bridge daemon; forwarding Claude replies to a messaging app; any phrase like "claude-to-im", "bridge", "消息推送", "消息转发", "桥接", "连上飞书", "手机上看claude", "启动后台服务", "诊断", "查看日志", "配置". Subcommands: setup, start, stop, status, logs, reconfigure, doctor. Do NOT use for: building standalone bots, webhook integrations, or coding with IM platform SDKs — those are regular programming tasks.
youtube-clipper
by op7418YouTube 视频智能剪辑工具。下载视频和字幕，AI 分析生成精细章节（几分钟级别）， 用户选择片段后自动剪辑、翻译字幕为中英双语、烧录字幕到视频，并生成总结文案。 使用场景：当用户需要剪辑 YouTube 视频、生成短视频片段、制作双语字幕版本时。 关键词：视频剪辑、YouTube、字幕翻译、双语字幕、视频下载、clip video
logo-generator
by op7418Generate professional SVG logos and high-end showcase images. Use when the user wants to: (1) Create a logo or icon for their product/brand, (2) Generate logo design concepts based on product information, (3) Create professional logo showcase presentations with multiple background styles, (4) Export logos in various formats (SVG, PNG), or (5) Iterate on logo designs with different visual styles. Supports geometric patterns, dot matrix designs, line systems, and mixed compositions. Generates showcase images using Nano Banana (Gemini image generation) with 12 professional background styles.
document-illustrator
by op7418基于文档内容自动生成配图。AI 智能分析文档结构，归纳核心要点， 为每个主题生成符合特定风格的配图。支持封面图生成和自定义图片比例。 使用场景：当用户需要为文档、文章、笔记生成配图时。 关键词：配图、插图、illustration、generate images、document images
video-wrapper
by op7418为访谈视频添加综艺特效（花字、卡片、人物条、章节标题等）。支持 4 种视觉主题，先分析字幕内容生成建议供用户审批，再渲染视频。
seedance-prompt
by op7418为 Seedance 2.0 视频生成模型撰写产品宣传动画提示词（Motion Graphics Prompt）。 生成 15 秒一镜到底的动态影像提示词，支持 4 种美学风格（Apple/Microsoft/Bauhaus/Vercel）。 支持垫图（参考图）模式，自动标注图片占位符。 生成提示词后可通过即梦 Dreamina CLI 直接生成视频（自动检测安装状态）。 TRIGGER when: 用户需要生成 Seedance 视频提示词、产品宣传动画提示词、motion graphics prompt， 或提到 "Seedance"、"视频提示词"、"产品动画"、"宣传视频提示词"、"video prompt"。 Keywords: Seedance, 视频提示词, video prompt, motion graphics, 产品动画, 宣传动画, 垫图, Dreamina
ai-desk-card
by op7418Drive a physical e-ink desk card (M5Paper 540×960) sitting next to the user's monitor. Use whenever the user wants to: - show / push / display ANYTHING on their card / 卡片 / 副屏 / 墨水屏 / e-ink display / desk card / glanceable display / secondary display - set up the device for the first time (flash firmware, pair, provision Wi-Fi) — phrases like "刚拿到 M5Paper", "怎么装卡片", "first-time setup", "刷固件", "卡片没反应" - schedule recurring pushes / "每小时刷一次" / "工作时间显示日历" / "auto-refresh every 30 min" - configure what the card shows (weather, todos, calendar, inbox, PR queue, AI status, focus, scratch, deadlines, messages, now-playing, git-status, system, next-meeting, break-reminder, ai-tasks) - put the device to sleep / show business card / "息屏" / "睡眠" Single Skill, agent-agnostic: probes current state, then routes to the right sub-flow. Never asks "is the daemon running" — it checks.
card-widget
by op7418Push live data to the user's ai-desk-card M5Paper e-ink companion display. Use whenever the user asks to show todos, calendar, weather, AI status, inbox counts, next meeting, or any glanceable info on their card / 卡片 / 副屏 / 墨水屏 / e-ink display. 16 widget types available; AI picks slot + widget type, fills data, POSTs to the local card daemon (default 127.0.0.1:9877). Communicates over loopback, so individual widget writes don't trigger AI agent approval prompts.
Browse Agent Skills by Occupation
23 major groups · 867 SOC occupations
Browse by Category
Explore agent skills organized by their primary use case
Explore the agent skills ecosystem by occupation and creator
SkillMD is not just a keyword search box. It is an open map that organizes public skills by occupation, creator, and repository, helping you see which workflows, judgment criteria, and domain habits people are writing for AI agents.
Then follow creators and GitHub repositories back to the source: compare the skills a team maintains, whether the repo is active, and how the README frames the work before you open, install, or reuse anything.
Use it three ways: learn an unfamiliar field by occupation, study how creators organize skills, then use source context to decide what is worth opening or reusing.
01 Map a field
Browse 23 occupation groups and 867 SOC roles to learn what skills exist in adjacent domains and how they break down real work.
02 Follow creators
Use creator and repository pages to inspect maintained skill collections, recent updates, and source context before trusting a result.
03 Search with sources
Search 1.7M+ collected skills, then use occupation tags, creators, and GitHub source context to decide what is worth opening.
Start with the occupation map, then follow creators and repositories back to real code. SkillMD helps explain why a skill is worth opening, not only what it is named.
Standardizing Agent Capabilities with SKILL.md and Model Context Protocol (MCP)
In the rapidly evolving landscape of artificial intelligence, LLM agents (Large Language Model agents) have transitioned from simple text predictors to autonomous problem solvers. To orchestrate complex, multi-step agentic workflows, developers require a standardized format to specify agent capabilities, prompt instructions, system rules, and database bindings. This is where SKILL.md and the Model Context Protocol (MCP) have emerged as standard developer paradigms. SkillMD serves as the central directory for indexing, exploring, and sharing these critical agent configurations.
Our open-source registry currently tracks over 1.7 million collected SKILL.md configurations and system prompts. By compiling agent configurations from active developers on GitHub, we bridge the gap between prompt engineering research and production execution. Whether you are building agents with Anthropic's Claude Code, OpenAI's GPT-4, Google's Gemini, or local models using Ollama and LlamaIndex, standardized skill definitions ensure your agents behave predictably across different runtime environments.
What is the Model Context Protocol (MCP)?
The Model Context Protocol (MCP) is an open-source standard designed to connect LLMs to data sources, developer tools, and external environments. MCP establishes a bidirectional communication channel between client applications (like Cursor, Claude Desktop, or custom agent systems) and servers hosting data or capabilities. Standardizing instructions via SKILL.md enables LLMs to query databases, read local files, execute terminal commands, and integrate third-party APIs. SkillMD allows you to find ready-to-run MCP servers and prompt instructions for various occupations and technical tasks.
The Structure of a Professional SKILL.md File
A valid SKILL.md configuration is designed to be easily read by humans and parsed by LLMs. It contains precise system instructions, trigger conditions, required parameters, and execution examples. Below is the typical architectural blueprint of a professional agent skill:
- Metadata & Core Scope: Declares the name of the skill, author details, target models, and a description of the capability.
- Triggers & Intent Detection: Details semantic triggers that help the agent decide when to invoke this skill.
- System Prompts: Explicit system-level instructions that direct the agent's behavior, personality, safety guardrails, and formatting preferences.
- Capabilities & Tools: Lists the files, databases, or APIs the agent must access to complete the tasks.
- Few-Shot Examples: Demonstrates real inputs and outputs, helping the model generalize behavior through in-context learning.
Optimizing Agent Workflows for Modern LLMs
Writing effective agent skills requires deep knowledge of prompt engineering. With the release of advanced reasoning models like Claude 3.5 Sonnet, ChatGPT o1, and DeepSeek-V3, prompt templates must focus on structured thinking. Developers are encouraged to use XML tags (e.g., <thought>, <context>, and <rules>) to isolate execution boundaries. Standardized prompts prevent agents from suffering from context drift, ensuring that long-running tasks remain aligned with the initial system parameters.
Exploring by SOC Occupations and Creator Profiles
What makes SkillMD unique is its taxonomy. Instead of simple text search, we parse and organize files according to the Standard Occupational Classification (SOC) system. This means you can discover skills written for Computer and Mathematical roles, Business and Financial operations, Legal, Design, and and Educational Instruction fields. By tracking creator profiles, developers can study how different teams organize their custom instructions, compare version updates, and fork public configs for specialized enterprise use cases.
SkillMD operates as a high-performance index running on a fast Go backend and a highly responsive Astro SSR frontend. All search queries execute in milliseconds, featuring smart debouncing to prevent multiple API requests while keeping user data secure. Join our community of developers to standardize your AI agent instructions and optimize your LLM prompting workflows today.
Frequently Asked Questions
A practical guide to agent skills: what they are, how to inspect them, and how SkillMD helps you explore the ecosystem.