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...
dataviews-table-migration
by getdokanBuild new vendor dashboard DataViews list pages from scratch OR migrate legacy Filter/StatusFilter/DataViewTable components to the unified @wedevs/plugin-ui DataViews component. Covers fresh builds (types, hook, list, route, PHP nav) and legacy migration (Scenario A status tabs, Scenario B multi-list merge).
dokan-automation
by getdokanBuild, scaffold, and run the Dokan Lite/Pro Playwright suite. Use when the user asks to add tests for a feature, scaffold from test-cases.md, or run the automation suite (Lite Only / PR / Full). Knows the folderized format, tag system, Docker / wp-env preconditions, and the .env / license-key requirements for Pro runs.
dokan-backend-dev
by getdokanAdd or modify Dokan backend PHP code following project conventions. Use when creating new classes, methods, hooks, REST controllers, or modifying existing backend code. Invoke before writing PHP unit tests.
dokan-code-review
by getdokanReview Dokan code changes and pull requests for coding standards, security, and architectural compliance. Use when reviewing PRs, performing code audits, or checking code quality.
dokan-dev-cycle
by getdokanRun tests, linting, and quality checks for Dokan development. Use when running tests, fixing code style, building assets, or following the development workflow.
dokan-frontend-dev
by getdokanAdd or modify Dokan frontend code (React, TypeScript, Vue, Tailwind). Use when creating components, hooks, stores, or modifying webpack configuration.
dokan-git
by getdokanGuidelines for git and GitHub operations in the Dokan repository. Use when creating branches, commits, or pull requests.
dokan-run-test-suite
by getdokanExecute the Dokan Playwright test suite (E2E + API), locally or via GitHub Actions. Invoke when the user asks to run, kick off, trigger, re-run, debug, or inspect the automated test runs. Phrases such as "run the suite", "run e2e tests", "trigger CI", "execute the QA suite", or "check the failed run" should activate this skill.
storegrowth-backend-dev
by getdokanAdd or modify StoreGrowth (Sales Booster) backend PHP code following project conventions. Use when creating classes, services, hooks, REST controllers, ajax handlers, or modifying existing backend PHP. Read before writing backend PHP in this plugin.
storegrowth-code-review
by getdokanReview StoreGrowth (Sales Booster) code changes and pull requests for conventions, security, and architecture compliance. Use when reviewing PRs, auditing code, or checking quality before merge.
storegrowth-frontend-dev
by getdokanAdd or modify StoreGrowth (Sales Booster) frontend code — React, Ant Design, @wordpress/data stores, the admin settings SPA, and the Lerna/wp-scripts build. Use when creating components, stores, admin routes, or touching asset builds.
storegrowth-git
by getdokanStoreGrowth (Sales Booster) git, build, versioning, and release workflow — branching, commits/PRs, the SPSG_VERSION placeholder, makepot, and the WordPress.org deploy. Use when committing, opening PRs, bumping the version, or cutting a release.
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.