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...
bom-sop-check
by GeorgeDoors888BOM与SOP对比校对技能。支持多个BOM文件合并后与SOP对比，检测名称规格、位号、数量差异，在SOP文件中标注差异、追加BOM数据并生成报告。校对报告包含：SOP独有物料、BOM独有物料、数量差异明细三个表格。触发场景：用户发送BOM和SOP文件要求对比校对。
structs-exploration
by GeorgeDoors888Explores new planets and manages fleet movement in Structs. Use when discovering new planets, moving fleet to a new location, expanding territory, relocating to a different planet, or checking fleet status (onStation vs away).
clawfight
by GeorgeDoors888Raise and battle a unique lobster pet with evolving personality. Hatch, feed, patrol, fight other lobsters in PvP. Each lobster has a soul with distinct personality traits that evolve through experience. Idle automation with heartbeat integration. Triggers on: lobster, clawfight, 龙虾, 巡逻, 战斗, pet, battle, idle, "lobster status", "how is my lobster", "patrol report", "lobster battle", "hatch lobster", "feed lobster", "龙虾状态", "养龙虾", "龙虾对战", "virtual pet", "电子宠物", "leaderboard", "排行榜".
pet-sitter-intake
by GeorgeDoors888Generate professional PDF client intake forms for pet sitting businesses. Use when a pet sitter, dog walker, pet boarder, or pet care professional needs a client intake form, onboarding questionnaire, or pet information sheet. Trigger phrases: "create intake form", "new client form for my pet sitting business", "pet sitter questionnaire", "boarding intake form". Supports fillable PDFs, custom color themes, multi-pet forms, home access sections, and service-specific templates.
lead-gen-pipeline
by GeorgeDoors888Automated lead generation pipeline with AI-powered lead scoring and personalized follow-up generation. Score leads 0-100 with reasoning, generate context-aware follow-ups in multiple tones. Integrates with any CRM. Use for sales automation, cold outreach, and pipeline management.
cocktail-advisor
by GeorgeDoors888鸡尾酒顾问 Skill。触发条件：用户描述风味偏好、列出手中原材料、表达饮酒需求。覆盖六大基酒，提供精确配比、调制步骤和个性化推荐理由。
themoltpub
by GeorgeDoors888The first virtual pub for AI agents. Three venues, real drinks, social pressure. Your human pays.
pipeworx-fruityvice
by GeorgeDoors888Nutritional data for fruits — calories, sugar, fat, protein, and carbs per 100g from Fruityvice
olo-sec-scanner
by GeorgeDoors888SEC EDGAR filing analysis for M&A due diligence — extract financials, detect risks, and track corporate events from 10-K, 10-Q, and 8-K filings
fennec-seo-audit-en
by GeorgeDoors888Uses Fennec SEO Auditor results to audit a URL. Invoke when user wants a quick on‑page/technical SEO health check or to verify favicon/meta/schema and GEO readiness.
villain-mint
by GeorgeDoors888Mint a Fellow Villain NFT from CHUM's agent-only collection on Solana. 0.001 SOL mint fee + network fees (~0.015 SOL).
superrare-mint
by GeorgeDoors888Mint art to a SuperRare-compatible ERC-721 collection on Ethereum or Base via Bankr. Requires an explicit mint mode so aaigotchi can clearly choose between an artist-given collection and an own-deployed SR factory collection before minting.
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.