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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msal-obo-flow
by AzureADOn-Behalf-Of (OBO) Flow for web APIs to call downstream APIs while preserving user identity in MSAL.NET
msal-client-credentials
by AzureADClient Credentials Flow for service-to-service (daemon) authentication in MSAL.NET without user involvement
msal-auth-code-flow
by AzureADAuthorization Code Flow for web applications using MSAL.NET confidential client to sign in users and access APIs on their behalf
entra-id-aspire-provisioning
by AzureADProvision Entra ID (Azure AD) app registrations for .NET Aspire applications and update configuration. Use after adding Microsoft.Identity.Web authentication code to create or update app registrations, configure scopes, credentials, and update appsettings.json files. Triggers: "provision entra id", "create app registration", "register azure ad app", "configure entra id apps", "set up authentication apps".
entra-id-aspire-authentication
by AzureADGuide for adding Microsoft Entra ID (Azure AD) authentication to .NET Aspire applications. Use this when asked to add authentication, Entra ID, Azure AD, OIDC, or identity to an Aspire app, or when working with Microsoft.Identity.Web in Aspire projects.
incident-investigator
by AzureADSystematically investigate IcM incidents and customer-reported authentication issues for Android Broker/MSAL. Use this skill when asked to investigate an incident, troubleshoot auth failures, analyze customer logs, diagnose PRT/SSO issues, or review IcM tickets. Triggers include "investigate incident", "troubleshoot IcM", "analyze these logs", "what's wrong with this auth flow", "diagnose this issue", or any request involving incident investigation with evidence-based diagnosis.
pbi-creator
by AzureADCreate Azure DevOps work items from a feature plan produced by the `feature-planner` skill. Handles ADO metadata discovery (area path, iteration, assignee), work item creation, and dependency linking. Use this skill when PBIs have been planned and approved, and you need to create them in ADO. Triggers include "create the PBIs", "create work items", "push PBIs to ADO", or approval of a feature plan.
pbi-dispatcher
by AzureADDispatch Azure DevOps PBIs to GitHub Copilot coding agent for autonomous implementation. Use this skill when PBIs have been created (by the `pbi-creator` skill or manually) and you want to send them to Copilot coding agent to generate PRs. Triggers include "dispatch PBIs to agent", "assign to Copilot", "send work items to coding agent", "kick off agent implementation", "dispatch these work items", or any request to have Copilot coding agent implement ADO work items.
prompt-refiner
by AzureADRefine rough prompts into structured, high-quality prompts. Use this skill when the user has a vague request and wants to turn it into a well-structured prompt with clear objectives, constraints, and acceptance criteria. Triggers include "refine this prompt", "make this prompt better", "structure this request", or "help me write a better prompt".
release-helper
by AzureADUnderstand, navigate, and troubleshoot the Android Auth Client CI/CD pipeline system. Use this skill when asked about pipelines, release processes, build pipelines, hotfix workflows, daily validation, cron schedules, pipeline templates, release branches, RC testing, publishing to Maven Central, or any ADO/GitHub Actions pipeline question. Triggers include "how does the release pipeline work", "what pipeline does X", "where is the cron job for releases", "how do hotfixes work", "trace the monthly release flow", "pipeline template for Y", "how are broker apps built".
test-planner
by AzureADCreate, manage, and export E2E test plans for Android Auth features. Use this skill when asked to: write test cases, create a test plan, add tests to ADO, export tests as a document, review existing test plans, or create manual test cases for sign-off. Triggers include 'write test cases for', 'create a test plan', 'add tests to ADO', 'export test plan', 'create E2E tests for', or any request to produce manual test cases for an Android Auth feature.
threat-modeler
by AzureADCreate threat model diagrams for Android Auth features. Supports three output modes: (A) new .tm7 file for Microsoft Threat Modeling Tool, (B) add diagram to existing .tm7, (C) Markdown export with Mermaid diagram for users without TMT. Optional STRIDE threat analysis. Triggers: 'create a threat model', 'threat model for', 'add threat diagram', 'threat model diagram', 'export threat model', 'STRIDE analysis for', 'security diagram for', or any request to create or update a threat model diagram.
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.