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.
Querying local SQLite index...
hr-compensation-benefits
by tuanductranHelp HR managers with compensation and benefits programs. Use when asked to "analyze compensation data", "design a bonus plan", "create benefits programs", "conduct a job evaluation", "write a compensation philosophy", "calculate pay rates", "develop retention strategies", or any compensation and benefits task.
hr-leadership-development
by tuanductranHelp HR managers with leadership development programs. Use when asked to "create a leadership program", "develop leadership competencies", "conduct leadership assessments", "design executive coaching", "create a leadership succession plan", "develop cross-cultural leadership training", or any leadership development task.
hr-training-development
by tuanductranHelp HR managers with learning and development programs. Use when asked to "design a training program", "create an e-learning course", "develop a coaching plan", "conduct a needs assessment", "write a competency model", "design a mentorship program", "create a learning plan", or any training and development task.
hr-content
by tuanductranHelp maintain and generate consistent HR skill content and metadata for the hr-skills repository. Triggers: "Create a SKILL.md", "Update skill metadata", "Fix blank lines", "Validate skill frontmatter", "Sync skill metadata".
hr-ai
by tuanductranHelp HR managers, recruiters, and talent acquisition teams understand Artificial Intelligence (AI), Machine Learning (ML), Generative AI, LLM Engineering, AI Infrastructure, and modern AI product development workflows. Use when asked to "explain AI engineering", "screen AI engineers", "understand machine learning roles", "compare AI and data science", "evaluate AI skills", "create AI interview questions", "understand LLM systems", or any AI and machine learning hiring and recruiting task.
hr-analytics
by tuanductranHelp HR managers with HR analytics and data management. Use when asked to "analyze employee data", "create HR metrics", "build an HR dashboard", "analyze turnover data", "develop HR reports", "build predictive analytics models", "create a data governance strategy", or any HR data and analytics task.
hr-compliance
by tuanductranHelp HR managers with HR compliance and workplace policies. Use when asked to "write an employee handbook", "develop OSHA compliance", "manage EEO compliance", "handle FMLA", "conduct a compliance audit", "create background check policies", "develop immigration compliance strategies", or any HR compliance task.
hr-data
by tuanductranHelp HR managers, recruiters, and talent acquisition teams understand Data Engineering, Data Analytics, Data Science, Business Intelligence, Machine Learning, and modern data ecosystems. Use when asked to "explain data roles", "screen data engineers or data scientists", "understand analytics workflows", "compare data engineering and data science", "evaluate data skills", "create data interview questions", "understand AI and machine learning teams", or any data and analytics hiring and recruiting task.
hr-diversity-inclusion
by tuanductranHelp HR managers with diversity, equity, and inclusion initiatives. Use when asked to "develop a diversity and inclusion strategy", "create inclusive job descriptions", "conduct unconscious bias training", "build employee resource groups", "measure diversity metrics", "develop a DEI scorecard", or any diversity and inclusion task.
hr-employee-engagement
by tuanductranHelp HR managers with employee engagement strategies. Use when asked to "improve employee engagement", "design recognition programs", "conduct engagement surveys", "boost employee morale", "reduce burnout", "develop a culture strategy", "create team-building activities", or any employee engagement task.
hr-employee-relations
by tuanductranHelp HR managers with employee relations matters. Use when asked to "handle a grievance", "conduct an exit interview", "manage workplace investigations", "create a remote work policy", "write employee contracts", "manage accommodations", "conduct satisfaction surveys", or any employee relations task.
hr-frontend
by tuanductranHelp HR managers, recruiters, and talent acquisition teams understand Frontend Engineering concepts, hiring requirements, frontend ecosystems, candidate evaluation, and modern frontend workflows. Use when asked to "explain frontend development", "screen frontend candidates", "understand React/Vue/Angular", "compare frontend frameworks", "evaluate frontend skills", "create frontend interview questions", "understand frontend architecture", or any frontend hiring and recruiting task.
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.