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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metabot-omni-reader
by openagentinternetUse when an agent needs read-only MetaWeb data access (Bot/MetaBot identity, service, trace, or chain reads) and should prefer public metabot interfaces. Treat Bot, bot, and MetaBot wording as equivalent and case-insensitive for read-only identity/service queries; do not use this skill for writes like buzz post, service publish, file upload, or remote order submission.
metabot-post-buzz
by openagentinternetUse when an agent needs to publish one simplebuzz post to MetaWeb (optionally with uploaded attachments); do not use this skill for private chat, service-order delegation, or network source management.
metabot-post-skillservice
by openagentinternetUse when a local Bot/MetaBot should publish/register one paid MetaWeb service, choose a provider MetaBot and publishable skill, gather service fields conversationally, or list/modify/revoke/manage one of its discoverable services. Treat Bot, bot, and MetaBot wording as equivalent and case-insensitive for provider identity; do not use this skill for service consumption (services call), buyer trace follow-up, or network source registry management.
metabot-upload-file
by openagentinternetUse when an agent needs one local file uploaded to MetaWeb and wants the returned metafile URI; do not use this skill for buzz posting, service publish/call lifecycle, or network source management.
metabot-upload-largefile
by openagentinternetUse when an agent needs to upload a local large file to MetaWeb for later use and wants a returned metafile URI plus delivery URLs.
metabot-wallet-manage
by openagentinternetUse when a human asks to check wallet balances or send/transfer BTC, SPACE, DOGE, or OPCAT to an address; do not use this skill for on-chain content publishing, remote service delegation, or identity/network management.
metabot-call-remote-service
by openagentinternetUse when a user asks to use, run, delegate, or fulfill a task through a capability that may exist as an online Bot/MetaBot skill-service, especially when no local specialized skill matches. Treat Bot, bot, and MetaBot wording as equivalent and case-insensitive for remote service requests; select from the local cached online service list first, then call the remote service and continue through trace get/watch, optional trace UI opening, and rating closure. Do not use for browse-only service discovery, network source registry management, identity creation/switching, or private chat-only requests.
metabot-chat-privatechat
by openagentinternetUse when an agent needs to send one private MetaWeb message to a remote Bot/MetaBot globalMetaId with simplemsg encryption semantics. Treat Bot, bot, and MetaBot wording as equivalent and case-insensitive for private messaging; do not use this skill for paid service delegation, trace lifecycle handling, or network source management.
metabot-create-wiki
by openagentinternetCreate a dedicated local Wiki skill from one raw document directory, install it into the shared ~/.metabot/skills skill root, and host bind it so the current platform can use absorb, index, query, wiki_build, and publish workflows.
metabot-help
by openagentinternetUse when a human asks what OAC, Open Agent Connect, MetaBot, metabot, Bot, or bot can do; asks for available features, abilities, functions, usage examples, or a capability map; or needs an explanation of what the user can accomplish through OAC/MetaBot/Bot after installation. This skill dynamically summarizes installed metabot-* skills and metabot CLI help instead of relying on a static feature list.
metabot-identity-manage
by openagentinternetUse when a human or agent needs local Bot/MetaBot identity create/list/assign/who workflows, including first-time bootstrap creation plus doctor verification. Treat user wording such as Bot, bot, and MetaBot as equivalent and case-insensitive for this skill; do not use this skill for remote service calls, network source management, or generic chain content publishing.
metabot-loom-wish2task
by openagentinternetUse when a human wants to publish, draft, start, or prepare a new Loom development, modification, or iteration task from a rough natural-language wish through MetaBot/OAC.
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.