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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mental-health-analyzer
by vitaclawAnalyzes mental health data, identifies psychological patterns, evaluates mental health status, and provides personalized mental wellness recommendations. Includes PHQ-9/GAD-7 trend analysis, mood pattern recognition, therapy progress tracking, multi-level crisis risk assessment, and correlation analysis with sleep, exercise, nutrition, and chronic disease data. Use when the user wants to review mental health trends, assess crisis risk, or track therapy progress.
mental-wellness-companion
by vitaclawProvides daily mental health support by coordinating PHQ-9/GAD-7 assessment, crisis detection, sleep-mood correlation, exercise prescription, and behavioral activation. CRITICAL: Crisis detection runs FIRST every interaction. Use when the user tracks mood, reports stress, or needs psychological support.
stress-management-coach
by vitaclawAssesses stress levels, guides breathing exercises and mindfulness practices, analyzes HRV-based stress data, and provides personalized stress reduction strategies. Use when the user reports feeling stressed, wants relaxation guidance, or asks about stress management techniques.
oral-health-analyzer
by vitaclawAnalyzes oral health data, identifies dental problem patterns, assesses oral health status, and provides personalized dental care recommendations. Supports correlation analysis with nutrition, chronic disease, and medication data. Use when the user wants to evaluate their dental health or track oral conditions.
menstrual-cycle-tracker
by vitaclawTracks menstrual cycles, predicts ovulation and next period, logs symptoms and flow, and provides PMS management suggestions. Use when the user logs period data, asks about cycle predictions, or wants menstrual health insights.
pregnancy-health-tracker
by vitaclawProvides trimester-specific pregnancy health guidance, tracks prenatal appointments, monitors symptoms, and offers nutrition and exercise recommendations for each stage. Use when the user is pregnant, planning pregnancy, or asks about prenatal health.
cancer-nutrition-coach
by vitaclawPerforms nutritional assessment and diet plan generation for cancer patients using NRS-2002 scoring and LLM-based dietary recommendations. Tracks weight, albumin, caloric intake, and generates personalized meal plans based on cancer type and treatment phase. Use when the user wants nutrition guidance during cancer treatment.
posture-ergonomics-coach
by vitaclawProvides posture assessment guidance, workstation ergonomics setup advice, and recommends stretching and strengthening exercises to prevent musculoskeletal issues. Use when the user asks about posture, ergonomic setup, or reports desk-related discomfort.
eye-health-advisor
by vitaclawProvides eye health guidance including 20-20-20 rule reminders, screen time management, vision change tracking, and dry eye prevention tips. Use when the user asks about eye strain, screen time impact, vision health, or wants eye care reminders.
hydration-tracker
by vitaclawTracks daily water intake, calculates personalized hydration targets based on body weight, activity level, and weather conditions, and provides reminders. Use when the user logs water intake, asks about hydration needs, or wants to analyze drinking patterns.
annual-checkup-advisor
by vitaclawOrchestrates comprehensive annual checkup interpretation by coordinating report parsing, lab interpretation, family history analysis, genetic risk scoring, TCM constitution assessment, and guideline lookup. Use when the user uploads a checkup report or asks for help interpreting physical examination results.
chronic-condition-monitor
by vitaclawMonitors multiple chronic disease indicators (BP, glucose, HbA1c, lipids, uric acid, creatinine, eGFR, liver function) against Chinese clinical guidelines. Detects abnormal trends, metabolic syndrome, and generates visit summaries. Use when the user tracks lab results or manages multiple chronic conditions.
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.