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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call-list
by anthropicsRanks the top-5 leads most worth calling today, supplies talking points from email history, blocks time on the calendar, and drafts follow-up messages. Accepts optional count and date arguments.
sales
by danielmiesslerTransforms product documentation into sales-ready narrative packages combining story explanation, charcoal gestural sketch art, and talking points. Pipeline: extract narrative arc → determine emotional register (wonder, determination, hope) → derive visual scene → generate assets. Three workflows: CreateSalesPackage (full pipeline — narrative + charcoal sketch visual + key talking points), CreateNarrative (story only, 8-24 numbered points in first-person conversational voice, captures why-it-matters not what-it-does), CreateVisual (charcoal gestural sketch with transparent background for presentation versatility). Charcoal gestural sketch is the mandatory visual style — minimalist composition with breathing space. Output is tied directly to what's being sold — clear, succinct, effective. Integrates StoryExplanation (for narrative arc extraction) and Art essay-art workflow (for visual generation) internally. USE WHEN: sales, proposal, pitch deck, value proposition, sales narrative, sales deck, sales package, t
cold-outreach
by TeamWiseFlowFind local businesses on Google Maps, extract contact emails from their websites, generate personalized outreach emails with LLM, and send via SMTP. Full pipeline for B2B cold email campaigns.
dbs-content
by dontbesilent2025dontbesilent 内容创作诊断。选题通过后，诊断怎么把这个选题做成好内容。 触发方式：/dbs-content、/内容诊断、「这个内容怎么做」「帮我看看这个文案」 Content creation diagnosis. After topic passes, diagnose how to turn it into good content. Trigger: /dbs-content, "how should I create this content", "review my copy"
dbs-deconstruct
by dontbesilent2025dontbesilent 概念拆解。用维特根斯坦 + 奥派经济学的方法，把模糊的商业概念拆到原子级别。 触发方式：/dbs-deconstruct、/拆概念、「帮我拆解这个概念」「这个词到底什么意思」 Concept deconstruction using Wittgenstein + Austrian economics framework. Trigger: /dbs-deconstruct, "deconstruct this concept", "what does this really mean"
social-selling
by tech-leads-clubWhen the user wants to sell through social media, optimize LinkedIn for sales, build DM sequences, or convert content engagement into pipeline. Also use when the user mentions 'social selling,' 'LinkedIn selling,' 'LinkedIn DMs,' 'social prospecting,' 'LinkedIn Sales Navigator,' 'DM sequences,' 'LinkedIn outreach,' 'social pipeline,' or 'LinkedIn optimization.' This skill covers social selling strategy from profile optimization through DM-to-deal conversion. Do NOT use for technical implementation, code review, or software architecture.
deapi-ai-media-suite-community
by LeoYeAIThe cheapest AI media API on the market. Generate images (Flux), music (AceStep), speech with voice cloning, transcribe video/audio, OCR, video generation, background removal, upscale, style transfer, and prompt enhancement — all through one unified API. Free $5 credit on signup.
adclaw
by LeoYeAIAd creative search assistant. Results displayed via ad.h5.miaozhisheng.tech. Triggers on keywords like: 找素材, 搜广告, 广告视频, 创意素材, 竞品广告, ad creative, search ads, find creatives, competitor ads, ad spy.
citedy-trend-scout
by LeoYeAIFind what your audience is searching for right now — scout X/Twitter and Reddit for trending topics, discover and deep-analyze competitors, and find content gaps. Combine social signals with SEO intelligence. Powered by Citedy.
ecommerce-copywriter
by anbeime电商图片文案创作技能，支持多品类产品的吸引性文案生成，适用于电商平台的商品营销推广
product-marketing-copywriter
by anbeime产品营销文案创作技能，支持多品类产品的吸引性营销文案生成，适用于产品推广、品牌营销、销售转化
app-marketing-context
by EronredWhen the user wants to create or update their app marketing context document. Also use when the user mentions "app context", "marketing brief", "app positioning", or when starting any ASO or app marketing project. This is the foundation skill — all other skills check for this context first.
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.