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...
inverse
by Jack5316Inverse thinking — compute reversely for problems, decisions, actions, and confusions. Inspired by linear algebra's inverse matrix and Charlie Munger's "invert, always invert." Use when you want to flip a problem, reverse a decision, undo an action, or dissolve confusion.
mole
by Jack5316Mole Mac Storage Cleaner - Clean your Mac storage by removing temporary files, caches, logs, and other unnecessary files. Inspired by https://github.com/tw93/Mole. Use when user asks to clean Mac storage, free up disk space, or clean cache/log files.
deep-research
by Jack5316Deep Research (8-step methodology) — Transform vague topics into high-quality, deliverable research reports. Systematic fact extraction, source tiering (L1>L2>L3>L4), time-sensitivity assessment, and verifiable "Fact→Conclusion" chains. Use when: deep research, comprehensive report, thorough investigation, concept comparison, decision support, trend analysis. Inspired by wshuyi/deep-research + OpenAI Deep Research + HKUDS.
thinking-partner
by Jack5316Collaborative thinking partner for exploring complex problems through questioning
zen
by Jack5316Create space for stillness, presence, and intentional focus. Use when feeling overwhelmed, scattered, before deep work, or when user says /zen.
article
by Jack5316Summarize a web article/blog post into an Obsidian note. Use when user asks for article summary or /article.
ai-insight
by Jack5316Gain self-knowledge from vault data. Analyzes your notes across mindset, cognitive models, exploration frameworks, and key influences. Use when you want to understand yourself better, get a self-knowledge report, inner conflicts, values clarification, MBTI analysis, CBT/ACT insights, or /ai-insight.
pdf-document-translation
by Jack5316Translate full PDF documents between English and Simplified Chinese while preserving the original layout, figures, and tables. Use whenever the user wants to translate a PDF, localize a report or paper, produce a bilingual document, or rebuild a translated PDF that looks like the source. Triggers on phrases like "translate this PDF", "把这份PDF翻译成英文", "localize this whitepaper", "produce a Chinese version of this document".
xlsx
by Jack5316Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
dictionary
by Jack5316Search Longman Dictionary of Contemporary English (LDOCE) for word meaning, etymology (origin), and corpus examples. Use when user asks to look up a word, check definition, etymology, or /dictionary.
school
by Jack5316Discover interesting facts and celebrate your alma maters - Xi'an Jiaotong-Liverpool University (XJTLU) and University College London (UCL). Use when you want to learn about your schools, their history, notable alumni, achievements, or just feel a sense of school pride.
hn
by Jack5316Create Hacker News newsletter digest. Use when user asks for HN digest or /hn.
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.