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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scienceworld-target-locator
by taomiaoThis skill determines the most likely location for a target object based on domain knowledge and environmental clues. Trigger this when the agent needs to find a specific item (like an animal) but it is not in the current room. It analyzes the environment description and suggests a room to teleport to for further investigation.
scienceworld-tool-user
by taomiaoUses a tool from inventory on a target object or location to perform a specific environmental interaction, such as digging or cutting. Activate this skill when a task requires modifying the environment or manipulating materials, like using a shovel to dig soil. It takes the tool and target as inputs and outputs the result of the interaction, enabling physical task progression.
scienceworld-environment-isolation
by taomiaoCloses doors or openings to create a contained environment for controlled processes. Trigger this when you need to isolate a space (like a greenhouse) to optimize conditions for pollination or other environmental-sensitive tasks. This modifies room connectivity to create optimal conditions for specific processes.
alfworld-receptacle-closer
by taomiaoCloses an open receptacle to maintain environment tidiness after inspection. Trigger this after you have finished searching a container and no longer need it open. It helps prevent clutter and is often used as a cleanup step following object searching inside drawers or similar containers.
webshop-initial-search
by taomiaoPerforms the first search on an e-commerce platform using keywords derived from parsed user requirements. Trigger this skill when starting product discovery or when previous search results are insufficient. It formulates a search query from the criteria (e.g., '24 pack of 7.5 ounce bottles of non-gmo classic tonic') and executes the search action, returning the initial result page.
webshop-product-detail-check
by taomiaoThis skill examines a specific product's detailed page to verify it matches the user's requirements, checking price, description, features, and reviews. Trigger when a candidate product is selected from search results. It confirms alignment with constraints and provides a final suitability assessment before purchase.
webshop-product-search
by taomiaoThis skill performs an initial product search using a web interface by generating appropriate search keywords based on interpreted query criteria. It is triggered when starting a product discovery task or when returning to search results. The skill inputs structured search parameters and outputs a list of candidate products from the search results page.
webshop-result-filter
by taomiaoThis skill filters search results by evaluating product listings against specific user constraints like price, features, or ratings. It should be triggered when reviewing a page of search results to identify items that match all given criteria. The skill takes a list of products with their details and outputs a subset that meets the defined requirements for closer inspection.
webshop-search-executor
by taomiaoExecutes a search on an e-commerce platform using parsed keywords. Trigger when you need to find products matching specific criteria from a user query. This skill takes structured search terms and performs a search action, returning a list of product results for evaluation.
scienceworld-measurement-taker
by taomiaoThis skill uses a measurement tool (like a thermometer) on a target substance or object to obtain a quantitative reading. It should be triggered when the task requires assessing a property (e.g., temperature) to make a conditional decision. The skill outputs the measured value, which determines subsequent actions such as classification or placement.
scienceworld-process-monitor
by taomiaoThis skill observes the state of an active apparatus and its contents to track progress. It should be triggered periodically during a heating or reaction process to check for state changes (e.g., solid to liquid). The skill uses 'look at' or 'examine' actions on the apparatus and substance.
scienceworld-tool-validator
by taomiaoThis skill performs a basic functionality check on a tool in the agent's inventory. It should be triggered after acquiring a tool and before its first use in a critical task step to ensure it is operational. The skill typically uses a 'focus' or 'examine' action on the tool and confirms its readiness state.
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.