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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Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms. When Claude needs to fill in a PDF form or programmatically process, generate, or analyze PDF documents at scale.
document-converter-suite
by dkyazzentwatwaConvert PDFs, Office docs, markdown, HTML, and tables between editable formats. Use for best-effort document conversion, PDF utilities, form filling, and table extraction.
pr
by javimoschConvert text files for printing
nighthawk-pdf-export
by microsoftgbbExport Nighthawk markdown reports to PDF on macOS. Use this skill when the user asks to generate, export, or produce a PDF from a Nighthawk notes file.
screenshot
by 0xDarkMatterFind and display recent screenshots. Triggers: screenshot, check screenshot, show screenshot, recent screenshot, last screenshot.
manage-tcg-collection
by pjt222トレーディングカードゲームのコレクションを整理、追跡、評価する。インベントリ 方法、保管のベストプラクティス、グレードに基づく評価、ウォントリスト管理、 Pokemon、MTG、Flesh and Blood、Kayouカードのコレクション分析を網羅する。 新しいコレクションを始めてインベントリ追跡を設定する時、カジュアルな知識を 超えて成長した既存のコレクションをカタログ化する時、保険や売却のためにコレクション を評価する時、または価値の可能性に基づいてプロフェッショナルグレーディングに 提出するカードを決定する時に使用する。
office-to-pdf
by bighardpersonConvert office files to pdf
tag
by chungchihhanAdd a tag to a session (current session or by number from list)
inkjet
by nordeimPrint text, images, and QR codes to a cheap wireless Bluetooth thermal printer from a MacOS device. Use `inkjet print` for output, `inkjet scan` to discover printers.
single-page-pdf-export
by cyberelfUse when the user asks to export a local HTML file, web page, or invitation page to a single-page PDF, a no-pagination PDF, a long PDF with auto-calculated height, or a PDF without headers and footers. Trigger on phrases like 单页 PDF, 不分页, 自动计算长度, 长图 PDF, 去掉页眉页脚, export HTML to single-page PDF, or print page to one PDF page.
bundle-binder
by danielrosehillConcatenate a configured list of SOPs and flowcharts into a single printable PDF binder, with optional cover page, table of contents, and consistent page numbering across the bundle. The set of documents and binder metadata (title, cover image, footer text) is defined in `binders.yaml` in the project root. Use when the user wants to produce a printed binder — e.g. "household emergency binder", "kitchen procedures", "first-aid kit reference".
paper
by seolcodingUse this skill when the user asks to "print markdown", "print document", "pretty print", "paper", "export to print", "markdown to printer", "print conversation", "print chat", or wants to print Claude's output beautifully. Also triggers on Korean commands like "프린트해줘", "뽑아줘", "출력해줘", "인쇄해줘", "마크다운 출력", "문서 뽑기", "예쁘게 출력", "프린터로 보내줘", "대화 프린트", "대화 출력", "대화 뽑기", "채팅 출력", or any Korean request for printing documents or conversations.
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.