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...
security-hardening
by jx1100370217Harden OpenClaw security configuration. Use when: (1) Setting up security for new OpenClaw installation, (2) Configuring exec approvals and allowlists, (3) Securing gateway access, (4) Setting up tool policies, (5) User asks about OpenClaw security or hardening.
repo-to-blog-series
by jx1100370217Turn an open-source GitHub repo into a multi-article CSDN-style technical blog series with cinematic Gemini covers and ≤200-char abstracts. Use when the user provides a GitHub URL and asks to "analyze this codebase and write N articles in the same format as my existing series", especially when they want to mirror an existing series style (e.g. OpenClaw → MemPalace), parallelize the writing across subagents, generate matching cover images via gemini.google.com, and end with a short abstract per article. Trigger phrases: "基于这个仓库写系列博客", "参考xxx系列写后续几篇", "分析代码库 + 写文章 + 生成封面 + 总结摘要".
openclaw-updater
by jx1100370217Check and update OpenClaw to the latest version from GitHub. Use when the user asks to update OpenClaw, check for updates, sync with GitHub, or review changelog. Handles source installation from GitHub.
ios-ui-ux-design
by jx1100370217Design iOS app interfaces following Apple Human Interface Guidelines (HIG). Use when creating UI designs, defining design systems, planning user flows, selecting colors/typography, designing for accessibility, or ensuring iOS platform consistency. Fourth step in the idea-to-App-Store workflow.
ios-testing
by jx1100370217Implement comprehensive testing strategies for iOS apps. Use when writing unit tests, UI tests, integration tests, snapshot tests, setting up test coverage, mocking dependencies, or implementing TDD. Part of the idea-to-App-Store workflow between development and CI/CD.
ios-swiftui-development
by jx1100370217Build modern iOS apps with SwiftUI. Use when creating UI components, implementing navigation, handling state management, building lists/forms, adding animations, or integrating with UIKit. Covers SwiftUI best practices, common patterns, and performance optimization for iOS/iPadOS/macOS/watchOS/visionOS.
ios-project-setup
by jx1100370217Initialize and configure iOS/SwiftUI projects with best practices. Use when creating new Xcode projects, setting up project structure, configuring dependencies (SPM), setting up git, configuring build settings, or establishing coding standards. Fifth step in the idea-to-App-Store workflow after UI/UX design.
ios-prd-generator
by jx1100370217Generate comprehensive Product Requirements Documents (PRD) for iOS apps. Use when defining app requirements, writing user stories, specifying features, documenting acceptance criteria, or creating technical specifications. Third step in the idea-to-App-Store workflow after competitor analysis.
voice-setup
by jx1100370217Set up free voice functionality (TTS + STT) for OpenClaw using Edge TTS and whisper-cpp. Use when: (1) User wants to add voice/audio capabilities, (2) Setting up speech-to-text transcription, (3) Configuring text-to-speech synthesis, (4) Enabling voice messages on Telegram/WhatsApp, (5) User asks about free TTS/STT solutions without API keys.
theme-to-blog-series
by jx1100370217Turn a technical theme/topic into a multi-article CSDN-style technical blog series with cinematic Gemini covers and ≤200-char abstracts. Use when the user gives you a *topic* (not a repo) — like "harness engineering", "context engineering", "MoE", "RAG" — and asks to "search the web for authoritative materials and write N deep articles with covers". Sister skill of repo-to-blog-series; same downstream pipeline (parallel subagents → Gemini covers → abstracts), but the upstream is *web research* instead of *code reading*. Trigger phrases: "检索全网关于X的资料整理成系列博客", "围绕主题X写N篇深度博客", "把这个技术写成系列文章 + 封面 + 摘要".
ios-idea-validation
by jx1100370217Validate iOS app ideas before development. Use when evaluating a new app concept, conducting market research, identifying target users, analyzing market size (TAM/SAM/SOM), validating problem-solution fit, or deciding whether to proceed with development. First step in the idea-to-App-Store workflow.
ios-competitor-analysis
by jx1100370217Analyze iOS app competitors comprehensively. Use when researching competing apps, understanding market positioning, identifying feature gaps, analyzing pricing strategies, or finding differentiation opportunities. Second step in the idea-to-App-Store workflow after idea validation.
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.