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.
Querying local SQLite index...
computer-repair
by XiaoLuoLYGDiagnose and repair a computer or small device.
windows-boot-recovery
by dmaynorDiagnose and recover non-booting Windows machines from a Linux recovery environment (e.g., SystemRescue USB). Use this skill whenever a user or agent mentions: a Windows machine that won't boot, BSOD loops, NTFS filesystem errors, hibernation/Fast Startup issues, GPU driver crashes preventing boot, or needs to back up data from a dead Windows drive. Also triggers on: "my laptop won't boot", "Windows is stuck", "ntfsfix", "dirty filesystem", "rsync from Windows", "recover data from Windows drive", or any scenario involving Linux-based diagnosis of a Windows disk. When in doubt, use this skill — it is designed to run safely and will ask the operator before any destructive action.
mobile-repair-technician
by HaibarakikuExpert mobile repair technician specializing in smartphone and tablet diagnostics, screen replacement, component-level repair, micro-soldering, water damage treatment, and data recovery
qing-li-dian-nao
by 86Kolton安全清理电脑、清理C盘、释放磁盘空间、整理下载/桌面/文档、查找大文件/旧文件/重复文件、迁移开发工具缓存、分析Docker/WSL/浏览器/包管理器缓存时使用。用户输入“/清理电脑”“清理电脑”“电脑空间不够”“C盘爆了”“帮我整理文件”“找重复文件”等都应触发。默认只读扫描，生成分级清理/迁移方案，任何删除、移动、改配置前必须逐项确认并保留回滚路径。
hibernate-pc
by studiogadgetタスク完了後にPCを休止状態にする。Use when: ユーザーが「休止」「hibernate」「タスク完了後に休止状態」「作業後にPCをスリープ/休止」と明示的に指示した場合のみ。正常終了時だけでなく、エラーや未解決事項が残っていても、明示指示があれば最後に休止へ移行する。Windows only.
book-computer-repair
by LJT-520Book computer-repair services through Lokuli MCP. Use when user needs to find and book computer-repair. Triggers on requests like "book a computer-repair", "find computer-repair near me", or any computer-repair service request.
book-phone-repair
by LJT-520Book phone-repair services through Lokuli MCP. Use when user needs to find and book phone-repair. Triggers on requests like "book a phone-repair", "find phone-repair near me", or any phone-repair service request.
setup-dell-monitors
by ArthurZakirovTroubleshoot Arthur's Dell P2725DE/P2225D monitor setup, especially DisplayPort daisy chaining, "No DP signal from your device" on the P2225D, Windows Fast Startup or shutdown-related display breakage, and reset/reinstall steps for a Lenovo laptop or Dell desktop tower using original Dell cables.
check-ink
by danielrosehillCheck ink levels on the HP DeskJet 5200. Reports tri-color and black cartridge percentages with low-ink warnings.
phone-setup
by echosprintGuide user step-by-step to set up their iPhone for PhysiClaw — enable AssistiveTouch, create three iOS Shortcuts (take screenshot, upload latest, clipboard sync).
hardware-printer
by EMIYAttk处理打印机卡纸、缺墨、无法连接、打印质量差等硬件故障，涵盖激光打印机和喷墨打印机常见问题
pc-performance-audit
by LeolebleisUse when the user wants to diagnose performance issues on a Windows PC, optimize a gaming setup, audit system resources, find what's eating RAM or CPU, check for bloatware, or improve FPS. Applies to both local machines and remote PCs via SSH.
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.