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...
run-test
by UI5Use when user asks to run tests, run qunit, execute unit tests, test this module, test this change, find test URL, test Button/Router/Table/Dialog/MessageBox/Input/Control, locate .qunit.html, search testsuite, can't find test file, where is qunit test, how to run UI5 module test, or needs test-resources URL for OpenUI5 modules
styling
by UI5How to customize and style UI5 Web Components. Covers CSS shadow parts, CSS custom states, CSS variables, and tag-level styling. Use when the user asks about changing component appearance, colors, spacing, theming, or overriding styles.
accessibility
by UI5How to make UI5 Web Components applications accessible. Covers accessibility APIs (accessibleName, accessibleNameRef, accessibleDescription, accessibleRole, accessibilityAttributes), label-input relationships, invisible messaging, keyboard handling, high contrast themes, and screen reader support. Use when the user asks about ARIA attributes, screen readers, keyboard navigation, accessibility properties, or making their app accessible.
analytical-table
by UI5Use ALWAYS for AnalyticalTable internals — react-table v7 plugin architecture, vendored react-table code at packages/main/src/components/AnalyticalTable/react-table/, tableHooks, AnalyticalTableHooks, useDynamicColumnWidths, useColumnResizing, useRowSelect, useF2CellEdit, useManualRowSelect, useIndeterminateRowSelection, useOnColumnResize, selectionMode, selectionBehavior, onRowSelect, onRowClick, onRowContextMenu, scaleWidthMode, infiniteScroll, isTreeTable, renderRowSubComponent, columnResizing, dynamic column widths, row virtualization, scroll-to-row freezes, deferred selection events, ARIA roles on grid/treegrid, aria-rowindex under virtualization, custom Cell/Header/Filter/Popover render-prop columns. Apply on ANY task that reads or modifies files under packages/main/src/components/AnalyticalTable/. SKIP for plain prop / event / ref-method / column-property lookups — those are in the ui5-wcr MCP `get_component_api`.
ui5wc-upgrade
by UI5Guide a complete UI5 Web Components version upgrade in the ui5-webcomponents-react monorepo. Updates root and peer dependencies, regenerates wrapper components, syncs theming parameters, updates version-info, detects new components and breaking changes, and verifies the build. Use when a new @ui5/webcomponents version is released and the monorepo needs upgrading.
ui5-fs
by UI5Work on the @ui5/fs package: the virtual file system abstraction layer providing Resource, Adapters (FileSystem, Memory), Reader Collections (ReaderCollection, ReaderCollectionPrioritized, DuplexCollection, WriterCollection), specialized readers (Filter, Link, Proxy), resource tagging, monitoring, and the resourceFactory API.
incremental-build
by UI5Work on the incremental (delta) build system in @ui5/project: build caching, resource indexing, hash trees, stage caching, build server, file watching, task execution caching, and delta builds.
ui5-best-practices-integration-cards
by UI5MUST be loaded before any UI Integration Cards (also called UI5 Integration Cards) task — creating, modifying, validating, previewing, or reviewing a card, its `manifest.json`, its Configuration Editor (`dt/Configuration.js`), or any analytical chart configuration. Provides the official guidelines, validation rules, supported chart types, and Configuration Editor patterns.
ui5-best-practices
by UI5UI5 development best practices and coding standards derived exclusively from official SAP UI5 guidelines. Use when writing UI5 applications to ensure modern, maintainable code following SAP standards. Covers: async module loading (sap.ui.define, ES6 imports, core:require), ComponentSupport initialization, data binding with OData types, i18n management, CSP compliance (no inline scripts), TypeScript event types (UI5 >= 1.115.0), MCP tooling (get_api_reference, run_ui5_linter), CAP integration patterns, and form creation rules (never SimpleForm, always Form with ColumnLayout). Keywords: ui5 coding standards, async loading, sap.ui.define, data binding, odata types, i18n translation, CSP no inline scripts, TypeScript event handlers, Button$PressEvent, ui5 linter, API reference, ComponentSupport, form layout, ColumnLayout, CAP integration, cds watch
ui5-typescript-conversion
by UI5A skill for converting UI5 (SAPUI5/OpenUI5) projects to TypeScript.
ui5-best-practices-opa5
by UI5This skill should be used in any OPA5 task - creating, modifying, extending, debugging, fixing or reviewing an integration test. Use when the user asks to "write an OPA5 test", "add an OPA5 journey", "fix the OPA5 test failure" or mentions OPA5 or its components - opaTest, page object, journey, waitFor.
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.