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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cli-ux-designer
by sjunglingThis skill should be used when the user asks to "design a CLI", "improve command structure", "format terminal output", "review CLI usability", "design help text", or "add flags and arguments". Automatically activates when designing new CLI tools, improving command interfaces, formatting terminal output, or reviewing CLI usability. Not for GUI/web design, backend APIs, or shell scripting.
structured-logging
by sjunglingThis skill should be used when the user asks to "analyze data with SQLite", "query logs", "find patterns in test results", or "correlate errors across files". Automatically activates when parsing large output (>100 lines), correlating data from multiple sources, tracking state across operations, aggregating results (counts, averages, grouping), or querying the same dataset multiple times. Not for tiny datasets (<50 records) with a single simple query.
git-bisect-debugging
by sjunglingThis skill should be used when the user asks to "find which commit broke this", "debug a regression", "bisect to find the bug", or says "this used to work". Automatically activates for performance regressions, test failures that appeared recently, or any issue known to have worked at a previous commit. Can be invoked from systematic-debugging or used standalone. Not for general debugging without a known-good commit or regression history.
obsidian-excalidraw
by sjunglingThis skill should be used when the user asks to "create an excalidraw diagram", "generate a diagram in Obsidian", "add a diagram to my vault", "embed a diagram", "make a flowchart", "visualize relationships", "draw a network diagram", or wants to programmatically generate .excalidraw files for an Obsidian vault. Also use when the user asks to update or regenerate an existing diagram file.
ios-swift-expert
by sjunglingThis skill should be used when the user asks to "build an iOS app", "create a SwiftUI view", "fix Xcode build errors", "implement Core Data", "design app architecture", or "optimize Swift performance". Automatically activates when working with .swift files, Xcode projects (.xcodeproj, .xcworkspace), SwiftUI interfaces, or Apple platform frameworks (UIKit, Core Data, Combine, WidgetKit, App Intents). Not for cross-platform frameworks (React Native, Flutter), non-Apple platforms, or backend server development.
pdf-generation
by sjunglingThis skill should be used when the user asks to "generate a PDF from markdown", "create a printable book", "convert documentation to PDF", or "export chapters as a PDF". Automatically activates when producing a PDF from a directory of ordered markdown chapters using pandoc and weasyprint. Not for single-file markdown-to-PDF conversion or non-documentation use cases.
technical-writer
by sjunglingThis skill should be used when the user asks to "write a README", "create API documentation", "draft release notes", "write a tutorial", "structure documentation", or "review docs for clarity". Automatically activates when working with .md files in docs/ directories, README files, or when discussing documentation structure, style guides, or content organization. Not for creative/marketing writing, academic papers, code comments/docstrings, or internal chat.
tmux-aware
by sjunglingThis skill should be used when the user asks to "start a service in tmux", "check tmux pane output", "manage background processes", or "run a server in a pane". Automatically activates when running in a TMUX session (detected by SessionStart hook). Not for one-off commands that do not need a persistent pane.
obsidian-vault-manager
by sjunglingThis skill should be used when the user asks to "manage Obsidian vault", "create a daily note", "move notes without breaking links", "search vault content", or "organize Obsidian notes". Automatically activates when working with Obsidian vaults, markdown notes with [[wiki-links]], daily notes, templates, or tags. Not for general markdown editing outside Obsidian vaults.
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.