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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abp-entity-patterns
by thapaliyabikendraABP Framework domain layer patterns including entities, aggregates, repositories, domain services, and data seeding. Use when: (1) creating entities with proper base classes, (2) implementing custom repositories, (3) writing domain services, (4) seeding data.
abp-api-implementation
by thapaliyabikendraImplement REST APIs in ABP Framework with AppServices, DTOs, pagination, filtering, and authorization. Use when building API endpoints for ABP applications.
abp-service-patterns
by thapaliyabikendraABP Framework application layer patterns including AppServices, DTOs, Mapperly mapping, Unit of Work, and common patterns like Filter DTOs and ResponseModel. Use when: (1) creating AppServices, (2) mapping DTOs with Mapperly, (3) implementing list filtering, (4) wrapping API responses.
abp-integration-testing
by thapaliyabikendraGenerate integration tests for ASP.NET Core ABP Framework application services and HTTP APIs. Use when the user requests integration tests, end-to-end tests, API tests, or wants to verify ABP framework integration points (repositories, authorization, validation, multi-tenancy, unit-of-work, data filters). Trigger even if the user just says "add tests" for an ApplicationService — ask if they want unit or integration tests.
abp-infrastructure-patterns
by thapaliyabikendraABP Framework cross-cutting patterns including authorization, background jobs, distributed events, multi-tenancy, and module configuration. Use when: (1) defining permissions, (2) creating background jobs, (3) publishing/handling distributed events, (4) configuring modules.
abp-framework-patterns
by thapaliyabikendraMaster ABP Framework patterns including repository pattern, unit of work, domain services, application services, authorization, multi-tenancy, background jobs, and distributed events. Use when: (1) building ABP-based applications with DDD architecture, (2) creating CRUD services with Entity, AppService, DTOs, validators, (3) handling authorization/permissions, (4) generating ABP module code.
xunit-testing-patterns
by thapaliyabikendraMaster xUnit testing patterns for ABP Framework applications including unit tests, integration tests, test data seeders, and mocking strategies. Use when: (1) writing xUnit tests for ABP services, (2) creating test data seeders, (3) implementing integration tests, (4) setting up test infrastructure.
host-module-configuration
by thapaliyabikendraConfigure an ASP.NET Core ABP Framework HttpApiHost or Web host module for production-ready infrastructure. Use when the user requests host-level configuration, middleware pipeline changes, Swagger/OpenAPI wiring, health checks, reverse proxy support, CORS, Hangfire dashboard, API versioning, forwarded headers, feature-flagged host behavior, or related host module and middleware registration updates.
data-seeder-generator
by thapaliyabikendraGenerate ABP Framework data seeder contributors following project conventions. Auto-detects project structure, existing entities, namespaces, permission constants, and seeder patterns from the codebase — no manual configuration needed. Creates IDataSeedContributor implementations with proper dependency injection, logging, and tenant/feature awareness. Use when: (1) creating new seed data for entities, (2) adding initial/reference data, (3) scaffolding data initialization code, (4) maintaining data consistency across environments.
api-integration-testing
by thapaliyabikendraIntegration testing patterns for ABP Framework APIs using xUnit and WebApplicationFactory. Use when: (1) testing API endpoints end-to-end, (2) verifying HTTP status codes and responses, (3) testing authorization, (4) database integration tests.
crud-generator
by thapaliyabikendraGenerate complete CRUD application services for ABP Framework following DDD patterns. Creates interface in Contracts layer, implementation in AppServices, and DTOs in Contracts. Use when: (1) creating new entity services, (2) scaffolding CRUD operations, (3) implementing standard ABP service patterns, (4) accelerating feature development.
fluentvalidation-patterns
by thapaliyabikendraMaster FluentValidation patterns for ABP Framework including async validators, repository checks, conditional rules, localized messages, and custom validators. Use when creating input DTO validators for AppServices.
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.