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...
sw-phpstan-shopware
by zone1987PHPStan-Extension für Shopware-Plugins. Aktiviere wenn: phpstan-shopware, PHPStan-Regeln für Shopware, statische Analyse Shopware Plugin, shopwarelabs/phpstan-shopware, rules.neon einbinden, Shopware spezifische PHPStan Fehler verstehen oder beheben.
sw-phpstan
by zone1987PHPStan für Shopware-6-Plugins: phpstan.neon einrichten, Level, Bootstrap/Autoload des Shopware-Kernels, Baseline, composer phpstan. Trigger: "PHPStan shopware", "phpstan.neon plugin", "phpstan level", "phpstan baseline shopware", "Typprüfung plugin". Shopware 6.7.
sw-cms-element-storefront
by zone1987Das Storefront-Template eines Shopware-6 CMS-Elements: cms-element-<name>.html.twig, Zugriff auf element.data/ element.config, Block-/Slot-Rendering. Trigger: "CMS Element Storefront", "cms-element twig", "element.data template", "cms element rendern storefront", "slot template cms". Shopware 6.7.
playwright-browsers
by zone1987Playwright Browser-Management: Chromium/Firefox/WebKit, Channels (chrome/msedge), npx playwright install mit allen Flags, isolierte BrowserContexts (alle newContext()- Optionen), mehrere Pages/Popups/Tabs, Chrome-Extensions (launchPersistentContext), WebView2-Anbindung per CDP, Speicherpfade, hermetic Install, Proxy-Env-Variablen. Playwright browsers, contexts, pages, extensions, WebView2.
shadcn-vue-mcp
by zone1987shadcn-vue MCP-Server: Setup fuer Claude Code, Cursor, VS Code, Codex, Opencode per npx shadcn-vue@latest mcp init --client <name>. .mcp.json-Format, components.json registries, Auth mit Env-Variablen, Beispiel-Prompts, Troubleshooting. Skills: npx skills add unovue/shadcn-vue, project-detection via components.json, context injection via shadcn-vue info --json. shadcn-vue MCP server setup for Claude Code/Cursor/VS Code/Codex/Opencode, .mcp.json config, components.json registries with namespaces, auth, example prompts, troubleshooting, skills.sh install (npx skills add unovue/shadcn-vue).
shadcn-vue-overview
by zone1987Was ist shadcn-vue, Abgrenzung zu shadcn/ui (React), reka-ui-Basis, Prinzipien (Open Code, Composition, Distribution, Beautiful Defaults, AI-Ready), Credits, Lizenz. Triggers: "was ist shadcn-vue", "shadcn vue overview", "shadcn-vue introduction", "shadcn vue vs shadcn ui", "reka-ui basis", "shadcn vue prinzipien", "what is shadcn-vue", "shadcn vue about", "unovue", "shadcn vue license"
shopware-apps
by zone1987Comprehensive guide for developing Shopware 6 Apps, covering manifest configuration, webhooks, authentication, app scripts, storefront/admin customization, payments, custom data, flow actions, gateways, and in-app purchases.
shopware-6-7-migration
by zone1987Use when migrating Shopware plugins from 6.6 to 6.7, upgrading admin components from sw-* to mt-* (Meteor), migrating from Webpack to Vite, converting Vuex to Pinia, adopting Vue 3 Composition API, or updating PHP code with constructor property promotion. Trigger on "6.6 to 6.7", "6.7 migration", "migrate plugin", "upgrade shopware", "meteor components", "sw- to mt-", "mt-button", "mt-text-field", "mt-select", "mt-banner", "mt-card", "mt-tabs", "webpack to vite", "vuex to pinia".
shopware-readme
by zone1987Generiert und aktualisiert README.md-Dateien für Shopware 6 Plugins nach einem einheitlichen Schema. Verwende diesen Skill wenn der User eine README erstellen, aktualisieren oder generieren möchte, "README schreiben", "Plugin dokumentieren", "Dokumentation erstellen", "readme.md" oder ähnliche Anfragen stellt. Triggert auch bei "Beschreibe das Plugin" oder "Was macht das Plugin?" im Kontext eines Plugin-Verzeichnisses.
adt-shopware-dal
by zone1987Comprehensive reference for Shopware 6 Data Abstraction Layer (DAL). Covers Entity, EntityDefinition, EntityCollection, EntityRepository, all Field types, Flags, Associations, Search/Criteria with Filters/Sorting/Aggregations, Write system with Events, Indexing, Versioning, EntityExtension, EntityProtection, Pricing, and PHP Attribute-based definitions. Includes real-world examples from Product, Category, and Media entities.
sw-api-flows
by zone1987Shopware 6 API End-to-End-Flows: Produkt anlegen (Admin API) → Store API lesen → Warenkorb → Kunde registrieren → Bestellung aufgeben → Zahlung. Alle Schritte mit curl/bash-Beispielen. Trigger: "api flow", "produkt anlegen api", "warenkorb api", "bestellung api", "checkout api", "customer register api", "end to end api", "order placed api", "product create admin api", "store api checkout", "handle-payment api", "create product api flow". Shopware 6.7.
playwright-evaluating
by zone1987Playwright JavaScript-Ausfuehrung im Browser: page.evaluate/evaluateHandle, JSHandle/ElementHandle, Argument-Uebergabe, addInitScript, Events mit waitForEvent/on/once, page.exposeFunction, Unterschied Test- vs. Browser-Kontext. Playwright JS evaluation: page.evaluate/evaluateHandle, JSHandle/ElementHandle, argument passing rules, addInitScript, events waitForEvent/on/once, exposeFunction.
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.