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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mckinsey-consultant
by JsonLee12138McKinsey-style business consultant for hypothesis-driven problem solving, structured analysis, and strategic recommendations Use when the user asks for mckinsey-consultant-related work such as: business problem structuring, mece issue tree decomposition, hypothesis formation and testing, market sizing and estimation, competitive analysis, strategic recommendation development, executive summary and report writing, data-driven insight synthesis, stakeholder communication frameworks.
agent-team
by JsonLee12138Compatibility shell for the legacy umbrella agent-team skill. Use only when older prompts still reference `agent-team`; route the request to the dedicated scenario skill instead of treating this file as the primary execution surface.
growth-marketer
by JsonLee12138Growth marketing role for project promotion across social media platforms, content creation, and community engagement Use when the user asks for growth-marketer-related work such as: social media content creation, x/twitter thread writing, launch announcement drafting, developer community outreach, content calendar planning, copywriting for technical audiences, hashtag and seo strategy, basic legal compliance review for published content.
brainstorming
by JsonLee12138Use when users explicitly ask to brainstorm, shape requirements, compare approaches, or produce a planning/design document before implementation. Turn rough ideas into validated brainstorming/design docs through focused dialogue, role-based analysis, and explicit user approval. Do not trigger this skill for straightforward implementation requests that do not need dedicated design exploration.
workflow-orchestrator
by JsonLee12138Governance-only workflow plan entry for controller and human sessions. Use when the user asks to generate, approve, activate, or close workflow plans through `agent-team workflow plan`.
pd
by JsonLee12138产品总监角色，精通产品战略、用户研究、优先级排序、路线图规划、SaaS 指标分析、研讨会引导和团队领导力发展，覆盖从发现到交付的完整产品管理生命周期 Use when the user asks for pd-related work such as: 产品战略与定位, 用户研究与客户发现, 优先级排序与路线图, saas 指标与财务分析, 用户故事与 epic 管理, 竞品分析与市场评估, 研讨会引导与协作, pm 到 director/vp/cpo 职业发展教练, 定价策略, 创新冲刺与验证实验.
pm
by JsonLee12138Full-stack product manager covering strategy, discovery, execution, go-to-market, market research, data analytics, marketing growth, and PM toolkit Use when the user asks for product-manager-related work such as: product strategy & vision, market research & competitive analysis, product discovery & feature prioritization, prd & user story creation, sprint planning & retrospectives, go-to-market strategy, data analytics & a/b testing, pricing & monetization, okr & metrics definition, stakeholder management.
task-splitting
by JsonLee12138Decompose requirement, design, or brainstorming documents into reviewable task drafts with one function per task and one file per task, then create `agent-team` task packages only after explicit approval. Use when turning a document into tasks, splitting oversized tasks, validating task boundaries, or preparing approved task files for `agent-team task create`.
worker-inspector
by JsonLee12138Read-only worker inspection skill for controller and human sessions. Use when the user wants to view worker status without opening a worker or sending a reply.
vite-react-dev
by JsonLee12138资深 Vite-React 开发工程师，专精于 UnoCSS 原子化 CSS、Vite 工程化、Vitest 测试、React 现代开发模式和 TanStack 全家桶（Router/Query/Form/Table），具有丰富的 SPA 应用交付经验 Use when the user asks for vite-react-dev-related work such as: react 组件开发与架构设计, vite 构建配置与插件开发, unocss 原子化 css 配置与自定义规则, tanstack router/query/form/table 集成开发, vitest 单元测试与集成测试, typescript 类型安全实践, 前端性能优化与最佳实践.
eslint-config
by JsonLee12138Use when configuring ESLint with @antfu/eslint-config for a single project or a monorepo workspace, including flat config setup, shared config packages, commit quality hooks, or migrations from legacy ESLint configs.
actions-npm
by JsonLee12138Use when creating or debugging GitHub Actions workflows that publish npm packages with trusted publishing / OIDC. Triggers on npm publish in CI, ENEEDAUTH, E404 or E422 during publish, tag-triggered releases, setup-node auth behavior, or provenance issues in public vs private GitHub repositories.
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.