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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microsoft-code-reference
by MicrosoftDocsFind working code samples, verify API signatures, and fix Microsoft SDK errors using official docs. Use whenever the user is writing, debugging, or reviewing code that touches any Microsoft SDK, .NET library, Azure client library, or Microsoft API—even if they don't ask for a "reference." Catches hallucinated methods, wrong signatures, and deprecated patterns. If the task involves producing or fixing Microsoft-related code, this is the right skill.
microsoft-docs
by MicrosoftDocsUnderstand Microsoft technologies by querying official documentation. Use whenever the user asks how something works, wants tutorials, needs configuration options, limits, quotas, or best practices for any Microsoft technology (Azure, .NET, M365, Windows, Power Platform, etc.)—even if they don't mention "docs." If the question is about understanding a concept rather than writing code, this is the right skill.
microsoft-skill-creator
by MicrosoftDocsCreate agent skills for Microsoft technologies using official documentation. Use whenever the user wants to build, generate, or scaffold a skill for any Microsoft technology (Azure, .NET, M365, VS Code, Bicep, etc.)—even phrased casually like "make a skill for Cosmos DB." Investigates the topic via official docs, then generates a hybrid skill with essential knowledge stored locally and dynamic lookups for depth.
microsoft-foundry-tools
by MicrosoftDocsExpert knowledge for Microsoft Foundry Tools (aka Azure AI services, Azure Cognitive Services) development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and integrations & coding patterns. Use when using Content Moderator, Content Understanding analyzers, document layout extraction, face detection, or REST/.NET APIs, and other Microsoft Foundry Tools related development tasks. Not for Microsoft Foundry (use microsoft-foundry), Microsoft Foundry Classic (use microsoft-foundry-classic), Microsoft Foundry Local (use microsoft-foundry-local).
microsoft-foundry-classic
by MicrosoftDocsExpert knowledge for Microsoft Foundry Classic (aka Azure AI Foundry classic) development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building Foundry agents, configuring Azure OpenAI deployments, RAG/search, model routing, or secure VNets/Private Link, and other Microsoft Foundry Classic related development tasks. Not for Microsoft Foundry (use microsoft-foundry), Microsoft Foundry Local (use microsoft-foundry-local), Microsoft Foundry Tools (use microsoft-foundry-tools).
microsoft-foundry-local
by MicrosoftDocsExpert knowledge for Microsoft Foundry Local (aka Azure AI Foundry Local) development including troubleshooting, decision making, configuration, and integrations & coding patterns. Use when calling Foundry Local REST/chat APIs, tools, transcription, LangChain apps, Olive HF compilation, or CLI, and other Microsoft Foundry Local related development tasks. Not for Microsoft Foundry (use microsoft-foundry), Microsoft Foundry Classic (use microsoft-foundry-classic), Microsoft Foundry Tools (use microsoft-foundry-tools), Azure Local (use azure-local).
microsoft-foundry
by MicrosoftDocsExpert knowledge for Microsoft Foundry (aka Azure AI Foundry) development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building Foundry agents with MCP tools, Agent 365, Azure OpenAI/Claude, VNet routing, or CI/CD deployments, and other Microsoft Foundry related development tasks. Not for Microsoft Foundry Classic (use microsoft-foundry-classic), Microsoft Foundry Local (use microsoft-foundry-local), Microsoft Foundry Tools (use microsoft-foundry-tools).
azure-data-share
by MicrosoftDocsExpert knowledge for Azure Data Share development including troubleshooting, decision making, security, configuration, and deployment. Use when estimating Data Share costs, managing invitations/RBAC, cross-region deployments, dataset mapping, or automation, and other Azure Data Share related development tasks. Not for Azure Data Box (use azure-data-box-family), Azure Import Export (use azure-import-export), Azure Open Datasets (use azure-open-datasets), Azure Data Explorer (use azure-data-explorer).
azure-database-migration
by MicrosoftDocsExpert knowledge for Azure Database Migration service development including troubleshooting, decision making, limits & quotas, security, integrations & coding patterns, and deployment. Use when planning Azure DMS migrations for SQL/MySQL/PostgreSQL, SSIS to Azure SQL/MI, or scripted PowerShell workflows, and other Azure Database Migration service related development tasks. Not for Azure Migrate (use azure-migrate), Azure SQL Database (use azure-sql-database), Azure SQL Managed Instance (use azure-sql-managed-instance), SQL Server on Azure Virtual Machines (use azure-sql-virtual-machines).
azure-oracle
by MicrosoftDocsExpert knowledge for Azure Oracle development including troubleshooting, security, configuration, and integrations & coding patterns. Use when configuring TDE with Key Vault, Oracle@Azure connectivity, AI DB VNets, Exadata log export, or Sentinel, and other Azure Oracle related development tasks. Not for Azure SQL Database (use azure-sql-database), Azure SQL Managed Instance (use azure-sql-managed-instance), SQL Server on Azure Virtual Machines (use azure-sql-virtual-machines), Azure VMware Solution (use azure-vmware-solution).
azure-redhat-openshift
by MicrosoftDocsExpert knowledge for Azure Red Hat OpenShift development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when creating ARO clusters, configuring networking/storage, securing with Entra/Key Vault, or integrating GPUs/NetApp, and other Azure Red Hat OpenShift related development tasks. Not for Azure Kubernetes Service (AKS) (use azure-kubernetes-service), Azure Container Apps (use azure-container-apps), Azure VMware Solution (use azure-vmware-solution), Azure Virtual Machines (use azure-virtual-machines).
azure-cloud-adoption-framework
by MicrosoftDocsExpert guidance for planning and executing cloud adoption using Azure Cloud Adoption Framework. Covers strategy, planning, readiness & landing zones, adoption patterns, governance, security, operations & management, organization & teams, and adoption scenarios. Use when planning AI/AKS landing zones, AVD/AVS setups, or SAP/Oracle migrations and governance, and other Azure Cloud Adoption Framework related development tasks.
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.