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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igniteui-angular-grids
by IgniteUIProvides guidance on all Ignite UI for Angular data grid types (Flat Grid, Tree Grid, Hierarchical Grid, Grid Lite, Pivot Grid) including setup, column configuration, sorting, filtering, selection, editing, grouping, summaries, toolbar, export, paging, remote data, and state persistence. Use when users ask about grids, tables, data grids, tabular data display, cell editing, batch editing, row selection, column pinning, column hiding, grouping rows, pivot tables, tree-structured data, hierarchical data, master-detail views, or exporting grid data. Do NOT use for non-grid UI components (forms, dialogs, navigation, charts) — use igniteui-angular-components instead. Do NOT use for theming or styling — use igniteui-angular-theming instead.
igniteui-angular-linting
by IgniteUIQuick-reference for linting the core Ignite UI for Angular library. Covers the combined lint command (`lint:lib`), ESLint for TypeScript and templates, and Stylelint for Sass/SCSS styles. Use when an agent needs to run the main linters, fix lint errors, or understand the primary lint configuration. Do NOT use for building — use igniteui-angular-build instead. Do NOT use for running tests — use igniteui-angular-testing instead.
igniteui-angular-testing
by IgniteUIQuick-reference for running Ignite UI for Angular test suites. Covers the full test run (`test:lib`), grid-specific suites (grid, tree-grid, hierarchical-grid, pivot-grid), non-grid tests, watch mode, and auxiliary test suites (schematics, styles, i18n). Use when an agent needs to run, select, or understand the test infrastructure. Do NOT use for building — use igniteui-angular-build instead. Do NOT use for linting — use igniteui-angular-linting instead.
igniteui-angular-components
by IgniteUICovers all non-grid Ignite UI for Angular UI components: application scaffolding and setup, form controls (inputs, combos, selects, date/time pickers, calendar, checkbox, radio, switch, slider), layout containers (tabs, stepper, accordion, splitter, navigation drawer), data-display components (list, tree, card, chips, carousel, paginator, progress indicators, chat), feedback overlays (dialog, snackbar, toast, banner), directives (button, icon button, button group, ripple, tooltip, drag-and-drop), Dock Manager, Layout Manager, Tile Manager, and Charts. Use when users ask about any Ignite UI Angular component that is NOT a data grid — such as forms, dropdowns, pickers, dialogs, navigation, lists, trees, cards, charts, or initial project setup. Do NOT use for data grids, tables, or tabular data — use igniteui-angular-grids instead. Do NOT use for theming or styling — use igniteui-angular-theming instead.
igniteui-angular-generate-from-image-design
by IgniteUIImplement Angular application views from design images using Ignite UI Angular components. Uses MCP servers (igniteui-cli, igniteui-theming, angular-cli) to discover components, generate themes, and follow best practices. Triggers when the user provides a design image (screenshot, mockup, wireframe) and wants it built as a working Angular view with igniteui-angular components. Also triggers when the user asks to "implement this design", "build this UI", "convert this mockup", or "create a page from this image" in an Ignite UI Angular project.
igniteui-angular-theming
by IgniteUIGenerates and customizes Ignite UI for Angular themes including color palettes, typography, elevations, and component-level styles using the Sass theming system and the igniteui-theming MCP server. Use when users ask to theme, restyle, or style Ignite UI components, change colors or the color palette, switch between light and dark themes, create or apply a global theme, customize typography or elevation shadows, adjust spacing, sizing, or roundness, or configure per-component design tokens. Do NOT use for component behavior, APIs, or data binding — use igniteui-angular-components or igniteui-angular-grids instead.
igniteui-angular-build
by IgniteUIQuick-reference for building the core Ignite UI for Angular library and related packages. Covers the full production build (`build:lib`), individual partial builds (styles, extras, migrations, schematics, i18n, elements), and the combined build-all command. Use when an agent needs to compile the library, produce a dist output, or verify that code changes compile cleanly. Do NOT use for running tests — use igniteui-angular-testing instead. Do NOT use for linting — use igniteui-angular-linting instead.
igniteui-wc-optimize-bundle-size
by IgniteUIOptimize application bundle size by importing only necessary components and using tree-shaking effectively
igniteui-wc-integrate-with-framework
by IgniteUIIntegrate Ignite UI Web Components packages into React, Angular, Vue, or vanilla JS applications with framework-specific configurations
igniteui-wc-generate-from-image-design
by IgniteUIImplement application views from design images using Ignite UI Web Components. Uses MCP servers (igniteui-cli, igniteui-theming) to discover components, generate themes, and follow best practices. Triggers when the user provides a design image (screenshot, mockup, wireframe) and wants it built as a working view with Ignite UI Web Components. Also triggers when the user asks to "implement this design", "build this UI", "convert this mockup", or "create a page from this image" in an Ignite UI Web Components project.
igniteui-wc-choose-components
by IgniteUIIdentify and select the right Ignite UI Web Components for your app UI, then navigate to official docs, usage examples, and API references
igniteui-wc-customize-component-theme
by IgniteUICustomize Ignite UI Web Components styling using CSS custom properties, optional Sass, and the igniteui-theming MCP server for AI-assisted theming
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.