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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ad-hoc-post
by AI-SDR-SaaSPost ad-hoc content to Jonathan's Instagram + TikTok via the publisher service. Use when Jonathan sends photos/video and asks to post.
hank-x-drafter
by AI-SDR-SaaSDraft tight X (Twitter) posts for Hank the Pro. Enforce 220-char hard limit, lowercase fragments, stripped narration. Use structural templates, verify char counts, batch-update to Airtable Drafts table.
hank-x-scheduler
by AI-SDR-SaaSSchedules approved X drafts from the Airtable Drafts table to post in optimal engagement windows throughout the day. Sets the Scheduled For field on records, queueing them for the publisher to pick up at the right time. Goal: roughly 5 posts/day spaced across high-engagement windows, never bursting. Default windows for trades + founder X audience (Eastern Time): 8am, 11am, 1pm, 4pm, 7pm. Adjustable. Skips weekends by default. Use this skill when the user says "schedule the queue", "spread out the posts", "schedule today's drafts", "queue the day", or similar scheduling commands. Also runs automatically via cron when enabled. Do not use for: drafting (use hank-x-drafter), publishing (use hank-x-publisher), or trend scanning (use hank-x-trend-watcher). IMPORTANT: This skill assigns post times to approved drafts. The publisher reads Scheduled For and posts when due. Cron is DISABLED by default.
hank-smartlead-operator
by AI-SDR-SaaSOperates Smartlead campaigns from Telegram. Pauses and resumes campaigns via the Smartlead REST API. Future expansion will add reading campaign analytics for Optimizer mode and pushing approved drafts from the Cold Email Drafts Airtable table directly into Smartlead campaigns. Tonight's scope: pause and resume only. Other actions are stubbed and will be added in future skill updates. Campaign matching: Jonathan refers to campaigns by vertical or partial name (e.g., "the HVAC campaign", "the roofer campaign", "the electrician one"). The skill calls GET /campaigns/ to list all campaigns, fuzzy matches against name, shows the match for confirmation before any destructive action. Pause action ALWAYS requires explicit confirmation in chat. Skill shows campaign details (name, status, sent count if available) and waits for Jonathan's "yes" or "confirmed" before firing the PATCH. Resume action confirms once and fires. Use this skill when Jonathan says "pause the [vertical] campaign", "resume the [vertical] campa
hank-x-publisher
by AI-SDR-SaaSPosts approved X drafts from Airtable to Jonathan Sherman's personal X account (@jonathan_sherm) via the X API. Polls the Airtable Drafts table for records with Platform=X and Status=Approved, posts them to X using OAuth 1.0a, then updates the record with Posted At timestamp, Post URL, and Status=Published. Handles single posts and threads (drafts split on
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.