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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adm-aluminum-design
by gogohkmADM2020 알루미늄 설계 매뉴얼(Specification, Commentary, Design Guide, Examples)을 검색하고 구조계산을 수행하며, 설계 워크플로우를 제공합니다. 알루미늄 구조설계, 6061-T6/6063-T5 합금, 템퍼 지정, 열영향부(HAZ), 좌굴상수, ASD 설계 관련 질문에 즉시 활성화되며, 공식 추출, 예제 매칭, 합금별 계산, 용어 설명, 기호 정의를 지원합니다.
aci-318-concrete-design
by gogohkmACI 318-25 콘크리트 구조설계 기준(Building Code for Structural Concrete)을 검색하고 설계 계산을 수행하며, 설계 워크플로우를 제공합니다. 콘크리트 구조설계, 철근콘크리트, 프리스트레스트 콘크리트, 노출등급, 내진설계, 부재 설계 관련 질문에 즉시 활성화되며, 공식 추출, 노출등급 선택, SDC 요구사항, 설계 검증을 지원합니다.
aisc-steel-design
by gogohkmAISC 강구조 기준(360-22 Specification) 및 설계 예제집(v16.0 Design Examples)을 검색하고, 구조계산을 수행하며, 설계 워크플로우를 제공합니다. 미국 강구조 설계 관련 질문에 즉시 활성화되며, 공식 추출, 예제 매칭, 계산 수행, 용어 설명, 기호 정의를 지원합니다.
aisi-cold-formed-steel
by gogohkmAISI S100-16 Cold-Formed Steel Design (Specification, Commentary, Design Manual with 74 examples). Search specification chapters A-M, calculate member capacities using ASD/LRFD/LSD methods, apply Effective Width Method (EWM) or Direct Strength Method (DSM), lookup steel grades (ASTM A1003, A653, A792), analyze buckling modes (local, distortional, global), design connections (welds, bolts, screws), access 74 worked examples. Activates for cold-formed steel, light-gauge steel, C-section, Z-section, deck, joist, stud, purlin, girt, standing seam roof, metal building, steel framing, 냉간성형강, 경량형강, 좌굴, 유효폭 questions.
asce7-loads-design
by gogohkmASCE 7-22 loads and load combinations skill for structural design. Covers wind, seismic, snow, and other environmental loads per US building standards.
basepl-connection-design
by gogohkmAISC Design Guide 1 expert for steel column base plate and anchor rod connection design. Use when users ask about base connections, base plates, anchor rods, column-to-foundation connections, concrete bearing strength, eccentricity, small vs large moment classification, shear transfer, or AISC Design Guide 1. Supports both LRFD and ASD design methods with 15 worked examples covering axial, moment, shear, and biaxial loading.
castellated-cellular-design
by gogohkmAISC Design Guide 31 (Castellated and Cellular Beam Design) 검색 및 구조계산 수행, 설계 워크플로우 제공. 허니컴보, 비렌딜굽힘, 웹포스트좌굴, CB/LB 설계 관련 질문에 즉시 활성화. 공식 추출, 예제 매칭, 기하학 계산, 용어 설명, 기호 정의 지원.
gfrp-structural-design
by gogohkmASCE/SEI 74-23 GFRP 구조설계 표준(Specification, Commentary)을 검색하고 구조계산을 수행하며, 설계 워크플로우를 제공합니다. GFRP 복합재료 설계, 펄트루전, 직교이방성, 환경조정계수, 시간효과계수, 연결부 설계 관련 질문에 즉시 활성화되며, 공식 추출, 물성값 조회, 환경보정, 연결부 다중파괴모드 계산을 지원합니다.
kds-building-standards
by gogohkm한국 건축구조기준(KDS) 75개 문서를 검색하고 구조계산을 수행하며, 설계 워크플로우를 제공합니다. 내진설계, 콘크리트/강구조, 기초, 하중, 가설구조 등 모든 KDS 기준을 지원하며, 공식 추출, 이미지 분석, 용어 설명, 기준 비교를 제공합니다. 모든 문서와 이미지 설명이 스킬에 포함되어 있어 독립적으로 사용 가능합니다.
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.