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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weightloss-analyzer
by huifer分析减肥数据、计算代谢率、追踪能量缺口、管理减肥阶段
nutritional-specialist
by ailabs-393This skill should be used whenever users ask food-related questions, meal suggestions, nutrition advice, recipe recommendations, or dietary planning. On first use, the skill collects comprehensive user preferences (allergies, dietary restrictions, goals, likes/dislikes) and stores them in a persistent database. All subsequent food-related responses are personalized based on these stored preferences.
kay-tee-khaw
by K-Dense-AIUse this skill whenever you need to reason about public health, epidemiology, preventive medicine, healthy aging, longevity, lifestyle vs. genetics, or dietary patterns. Kay-Tee Khaw, an epidemiologist at the University of Cambridge, focuses on population health and how modest lifestyle changes impact chronic disease. Trigger this skill when evaluating health interventions, discussing longevity, analyzing real-world health data, or giving advice on diet and lifestyle. Apply her frameworks to shift focus from extreme interventions and isolated nutrients toward whole-food patterns, population-level risk shifts, and the compression of morbidity.
calorie-counter
by malue-aiTrack daily calorie and protein intake, set nutrition goals, and generate diet reports. Data stored locally.
analyze-symptoms
by richardblythman**Digestive Symptom Analyzer**: Correlates Bristol scale and symptom log entries with meals consumed in the preceding 24-48 hours to identify potential food triggers and patterns. Use this skill whenever the user wants to investigate digestive patterns, identify food triggers, analyze their symptom log, check correlations between meals and gut health, review their Bristol scale data, or look for patterns in eczema/ear symptoms alongside food intake. Also trigger when the user says "what's causing my symptoms", "analyze my gut health", "which foods are triggering me", "symptom patterns", "Bristol scale analysis", or mentions investigating food sensitivities.
plan-weekly-meals
by richardblythman**Meal Plan Builder & Nutrition Analyzer**: Takes your meal selections for the week and produces a complete meal plan with day-by-day breakdown, full nutritional analysis (macros, micros, daily averages), and preparation notes. Use this skill whenever the user wants to plan meals for a week, analyze the nutrition of selected meals, check if their diet has gaps, get suggestions for meal improvements, or create a weekly meal plan. Also trigger when the user mentions "what should I eat this week", "plan my meals", "nutrition analysis", "is my diet balanced", "meal plan", "weekly meals", or describes a set of meals they want to eat over multiple days.
managing-nutrition-support
by CaseMarkAssesses nutritional status and coordinates enteral/parenteral nutrition protocols. Use when evaluating nutritional needs, initiating feeding protocols, or managing TPN orders.
assess-holistic-health
by pjt222Conduct temperament-based health assessment from Hildegard von Bingen's Causae et Curae. Evaluates the four temperaments (sanguine, choleric, melancholic, phlegmatic), elemental correspondences (air, fire, earth, water), and provides dietary and lifestyle recommendations for rebalancing. Use when understanding constitutional type in Hildegardian terms, experiencing imbalance (fatigue, digestive issues, mental fog) needing holistic guidance, seeking dietary recommendations by temperament, or researching medieval humoral medicine.
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.
caffeine-sleep-advisor
by vitaclawAnalyzes the relationship between caffeine consumption and sleep quality by coordinating caffeine tracking, sleep analysis, and trend correlation. Identifies personal sensitivity thresholds and optimal caffeine cutoff times. Use when the user wants to understand how coffee affects their sleep.
caffeine-tracker
by vitaclawTracks daily caffeine intake from beverages, models residual caffeine using half-life decay (t1/2=5.7h), and predicts safe sleep time. Use when the user logs coffee, tea, or energy drink consumption, asks about caffeine levels, or wants to know when it is safe to sleep.
gut-health-advisor
by vitaclawAssesses gut health through symptom tracking, provides FODMAP dietary guidance, recommends probiotics and prebiotics, and monitors digestive patterns. Use when the user reports digestive issues, asks about gut health, or wants dietary guidance for GI wellness.
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.