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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caregiving-physical-skills
by LeoYeAIPhysical caregiving techniques for assisting elderly, disabled, or recovering family members. Use when someone is caring for an aging parent, disabled family member, or recovering patient and needs hands-on physical care skills.
childcare-essentials
by LeoYeAIPractical physical childcare skills for ages 0-5. Use when someone is a new parent, babysitter, grandparent, or anyone suddenly responsible for a young child and needs immediate practical guidance.
chronic-followup
by XiaoLuoLYGFollow up on recurring health needs and medication routines.
nutrition-planning
by cosmicstack-labsMacronutrients, meal prep, dietary patterns, supplementation, hydration, and sustainable eating
nutrigx-advisor
by aAAaqwqNutrigenomics advisor — personalized nutrition guidance based on genetic profiles
contested-claims-in-nutrition
by TibsfoxA survey of the best-known active scientific controversies in nutrition — saturated fat and cardiovascular disease, dietary cholesterol, low-carb vs low-fat, ultra-processed foods, red meat and cancer, salt and blood pressure, and the replication status of popular single-nutrient claims. Use when a question asks whether a widely reported nutritional claim is settled, or when the department needs to distinguish "contested but plausible" from "settled" from "disproven."
dietary-assessment
by TibsfoxMethods for assessing what people actually eat — 24-hour recall, food frequency questionnaires, diet diaries, biomarkers, duplicate-plate studies, and controlled feeding. Covers the relative strengths and biases of each instrument, how to choose among them for a given question, and how to interpret results in the presence of measurement error. Use when a user wants to estimate population-level intake, individual-level intake, or evaluate the plausibility of a dietary claim that depends on how intake was measured.
feeding-pedagogy
by TibsfoxThe pedagogy of feeding — how to talk about food with children, what the Division of Responsibility model says, age-appropriate autonomy in eating, how to handle picky eating without creating disordered eating, and how to teach nutrition concepts to learners at different levels without either moralizing or oversimplifying. Use when a question is about raising, teaching, or advising a child or learner on eating, or when planning curriculum or parent guidance.
nutrient-metabolism
by TibsfoxBiochemical metabolism of macronutrients and key micronutrients — digestion, absorption, transport, utilization, and excretion — with emphasis on the pathways that matter for dietary-guideline debates (insulin response, lipoprotein metabolism, one-carbon metabolism, iron homeostasis). Use when a question asks what happens biochemically to a food after it is eaten, or when a claim about "metabolic effect" needs to be tested against mechanism.
nutrition-science-foundations
by TibsfoxFoundational concepts in nutrition science — macronutrients, micronutrients, energy balance, Atwater factors, reference intakes (DRI/RDA/AI/UL), food composition tables, and the methods of human nutrition research. Grounds the rest of the department in a shared vocabulary and in the measurement limits of the field, including controlled-trial history, observational-study limits, and the biochemical basis for calorie accounting. Use when a question asks what something "is" nutritionally, how energy and nutrients are measured, or what the reference numbers mean.
claude-ally-health
by diegosouzapwClaude Ally Health workflow skill. Use this skill when the user needs A health assistant skill for medical information analysis, symptom tracking, and wellness guidance and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
claude-ally-health-v2
by diegosouzapwClaude Ally Health workflow skill. Use this skill when the user needs A health assistant skill for medical information analysis, symptom tracking, and wellness guidance and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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.