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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innojini-huni-design-tokens
by skeeper75HuniPrinting Widget Admin design token reference for the violet-based design system. Provides complete CSS custom properties, Tailwind v4 utility mappings, component variant specifications, and accessibility guidance sourced from globals.css and Pencil MCP Color Palette frame FM2Gq. Use when building or styling any Widget Admin component, applying color tokens, selecting typography scales, or implementing button/badge/input/select/tabs variants consistent with the Huni design system.
huni-printing-estimator
by skeeper75후니프린팅 통합 관리 시스템: 자동 견적 + 외주 정산 자동화 🔹 견적/가격: "견적 계산", "가격 알려줘", "얼마야", "무선책자 100부" 🔹 조판/CTP: "CTP 몇 판?", "조판 어떻게?", "판수 계산" 🔹 옵션 검증: "이 옵션 가능해?", "박가공 선택하면?" 🔹 파일 가이드: "파일 어떻게 만들어?", "도련", "CMYK", "아웃라인" 🔹 후가공 파일: "박가공 파일", "칼선 레이어" 🔹 주문 시뮬레이터: "만들고 싶어요", "미리보기", "옵션 선택" 🔹 제품 프리뷰: "책 모양", "완성품 보여줘" ⭐ 정산 관리 (NEW): 🔹 정산 분석: "정산 분석", "비즈하우스 정산", "후지필름 정산" 🔹 매칭 검증: "데이터 매칭", "불일치 확인", "정산 대사" 🔹 금액 집계: "정산 금액", "VAT 계산", "총액" 🔹 정산서 생성: "정산서 만들어", "엑셀 출력" 지원 상품: 디지털인쇄, 스티커, 책자, 캘린더, 포스터, 아크릴, 굿즈, 파우치, 에코백 등 236개 MES상품 지원 외주사: 비즈하우스, 후지필름(롯데ON)
mycom-printing-estimator
by skeeper75마이컴프린팅(MycomP&C) 옵셋 인쇄 조판/견적 통합 시스템 v3. 표지 오시 계산(책등 두께, 힌지 간격, 날개, 펼침 크기), 접지별 페이지 배열(십자16P, 롤4단, 3단접지 등 9종), 조판 계산(7개 용지 규격, 자투리 추가배치 포함), 크립 보정(중철 40P+), 인쇄/코팅/오시/제본 단가 계산. 사용 시점 - 무선/중철 책자 견적, 표지 펼침 크기, CTP 판수, 조판 UP수, 접지 방법, 대수 계산
printing-foundation
by skeeper75인쇄 산업 공통 기술 지식 베이스. 조판 계산, CTP 판수, 접지 배열, 책등/오시, 크립 보정 등 인쇄 기초 지식 제공. 🔹 조판 계산: "UP수 계산", "판걸이", "조판 효율", "자투리 배치" 🔹 CTP 계산: "CTP 몇 판?", "판수 계산", "Work&Turn" 🔹 접지 배열: "십자접지", "3단접지", "페이지 순서", "대지" 🔹 책등/오시: "책등 두께", "오시 줄 수", "표지 펼침 크기" 🔹 크립 보정: "크립 계산", "중철 보정" 🔹 용지 규격: "국전", "46전", "롤 폭", "인쇄 영역" 사용 시점: 인쇄 견적/생산 시스템 개발, 조판 최적화, 제본 계산 필요 시 확장 스킬: huni-printing-estimator, mycom-printing-estimator에서 참조
innojini-huni-production-flow
by skeeper75후니프린팅 생산 공정 플로우 도메인 지식 베이스. 17가지 공정 케이스별 단계별 플로우, 인쇄 방식별 후가공 연결, 공정 단계 코드 체계를 포함. MES 연동 API 설계, 공정 상태 관리, 생산 팀 구성 파악 시 활용. Use when designing production APIs, MES integration, process status tracking, or building manufacturing workflow systems for HuniPrinting.
shopify-global-commerce
by skeeper75Shopify 기반 글로벌 D2C 이커머스 통합 가이드. 드랍쉬핑 비즈니스 운영을 위한 샵 구축, 마진 계산, CS 대응, 현지화 전략 제공. **스파미 오프라인 강의 기반 실전 노하우 포함 (2025.12 업데이트)** 🔹 샵 구축: "Shopify 설정", "도메인 연결", "배송 설정", "테마 커스터마이징", "로고 제작" 🔹 마진/수익: "마진 계산", "수수료", "실수령액", "수익률", "Shopify Payments", "GSK 정산" 🔹 현지화: "미국 주소", "미국 시장", "현지화 체크리스트", "USPS 배송", "OpenPhone" 🔹 상품 소싱: "뭘 팔까", "상품 선정", "드랍쉬핑 제품", "경쟁자 분석", "AutoDS", "CJ" 🔹 CS/운영: "차지백", "환불 대응", "CS 템플릿", "고객 응대", "Inbox", "플로리다 주의" 🔹 주소체계: "LA=Louisiana", "우편번호", "푸에르토리코", "라커 배송" 🔹 IP 대응: "상표권", "저작권", "신고 대응", "3일 규칙", "화이트라벨" 🔹 샵 확장: "5개 목표", "옆으로 확장", "예비 샵", "매몰 금지" 🔹 블로그: "Essential AI Blog", "SEO", "체류시간", "발행 전략"
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.