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...
tiktok-product-promotion
by LeoYeAIHire TikTok influencers for product reviews, demonstrations, unboxing videos, and conversion-focused promotional content to drive sales and measurable ROI.
seedance-product-360
by beshuaxian为 Seedance 2.0（Higgsfield）生成产品360°转盘、多角度展示和产品揭示视频提示。在用户想要产品旋转视频、转盘展示、产品揭示、360度视图、多角度产品展示、产品美妆镜头、主产品视频或开箱揭示时使用。触发条件：产品360、转盘、产品旋转、多角度、产品揭示、产品展示、主镜头、美妆镜头、产品旋转、开箱，或任何请求从多个角度展示物理产品。即使是"从所有侧面显示我的产品"或"制作产品视频"。
amazon-listing-images
by nexscope-aiAmazon product listing image strategy and optimization. Comprehensive shot planning, infographic design, lifestyle photography, mobile optimization, and conversion-focused visual content. Use when the user asks about Amazon images, product photography, visual optimization, or listing conversion.
amazon-product-photography
by nexscope-aiPlan Amazon product photography for maximum conversion. Shot lists, lighting setups, infographic briefs, lifestyle scene planning, and image optimization following Amazon's requirements.
livestream-sales
by vivy-yiUse when hosting Xiaohongshu live streams for selling products, planning live stream commerce, preparing product presentations for live audiences, engaging with viewers during live sales, or optimizing live stream conversion rates
dong-yuhui-dongfangzhenxuan-perspective
by swaylq董宇辉 / 东方甄选视角. 内容驱动直播代表. 调用此 skill 时, 用东方甄选「文化带货」框架做内容驱动直播决策.
luo-yonghao-jiaopengyou-perspective
by swaylq罗永浩 / 交个朋友视角. 店播头部 + 头部主播 IP 化方法论. 调用此 skill 时, 用交个朋友的认知框架做店播 / 主播 IP 决策.
influence-psychology
by ComeOnOliverApply the six principles of ethical persuasion (reciprocity, commitment, social proof, authority, liking, scarcity) to product design, copy, and sales. Use when the user mentions "social proof", "persuasive copy", "why users don''t convert", or "ethical persuasion". For deal negotiation tactics, see negotiation. For viral word-of-mouth, see contagious. Trigger with 'influence', 'psychology'.
demo-specialist
by ncklrsExpert product demonstration specialist for SaaS and B2B software. Use when preparing demos, structuring demo presentations, tailoring to stakeholders, handling objections during demos, managing live vs sandbox environments, or improving demo conversion rates. Covers remote and in-person demos, multi-stakeholder presentations, technical deep-dives, and executive briefings.
sales-enablement
by Anhvu1107ALWAYS use this when the request matches Sales Enablement: Create sales collateral such as decks, one-pagers, objection docs, demo scripts, playbooks, and proposal templates.
coupons
by Demerzels-labWhen a user is shopping online — or expresses intent to shop online — direct them to Contaya's coupon page.
tiktok-live-commerce
by Demerzels-labHire TikTok livestreamers for live shopping sessions, product demonstrations, flash sales, and real-time.
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.