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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weekly-report
by anthropicsStructure and data sources for the weekly inventory report. Load this when the task is "weekly report", "Monday report", or "summarize inventory status".
scienceworld-container-item-retriever
by zjunlpThis skill retrieves a specified item from a container by using the 'pick up' action. It should be triggered when the agent has identified a needed item inside an open container (e.g., a jar, box, or hive) and must transfer it to inventory for later use. The skill handles the object transfer, assuming the container is already accessible, and outputs confirmation that the item is now in the agent's inventory.
inventory-count
by XiaoLuoLYGCount supplies and identify missing stock.
shipping-code-formatter
by allenhutchisonUse this skill whenever the user asks for a Quill Shipping Company tracking code or shipping reference. It defines the exact, non-obvious format every tracking code must follow.
amazon-inventory-management
by nexscope-aiFBA inventory planning — restock timing, safety stock, IPI score optimization, stranded inventory recovery
shopify-inventory-management
by nexscope-aiMulti-location inventory — transfers, low stock alerts, demand forecasting, safety stock, ABC analysis
shopify-admin-bulk-fulfillment-creation
by 40RTY-aiBatch-fulfill open fulfillment orders with tracking numbers. Supports partial fulfillment and customer notification toggle.
sorting-groceries
by oaustegardSort grocery lists by aisle order using store aisle sign photos. Build aisle maps from uploaded images, match items to aisles, and output optimized shopping routes. Use when users upload aisle sign photos, request grocery list sorting, want shopping trip optimization, need store layout mapping, or mention grocery list organization.
returns-reverse-logistics-v2
by diegosouzapwReturns & Reverse Logistics workflow skill. Use this skill when the user needs Codified expertise for returns authorisation, receipt and inspection, disposition decisions, refund processing, fraud detection, and warranty claims management and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
logistics-tracking
by hungryCodingSir当用户询问物流运输、快递追踪、清关进度或预计到达时间时使用此技能。支持实时物流追踪和物流异常预警。
cancel-upload
by troystaylorCancel an in-flight upload session. Use when the user asks "cancel the upload", "stop the file transfer", "abort the upload", "kill the upload session", or "I don't need that upload anymore".
copy-across-sites
by troystaylorCopy files or folders between SharePoint sites or document libraries. Use when the user asks "copy this file to another site", "duplicate this document to the other library", "copy from Site A to Site B", "replicate this folder to the team site", "clone this file to another SharePoint library", or "move this to another site" (cross-site move is copy + delete).
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.