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...
zero-build-frontend
by jamditisZero-build frontend development with CDN-loaded React, Tailwind CSS, and vanilla JavaScript. Use when building static web apps without bundlers, creating Leaflet maps, integrating Google Sheets as database, or developing browser extensions. Covers patterns from rosen-frontend, NJCIC map, and PocketLink projects.
data-journalism
by jamditisData journalism workflows for analysis, visualization, and storytelling. Use when analyzing datasets, creating charts and maps, cleaning messy data, calculating statistics or building data-driven stories. Essential for reporters, newsrooms and researchers working with quantitative information.
electron-dev
by jamditisElectron desktop application development with React, TypeScript, and Vite. Use when building desktop apps, implementing IPC communication, managing windows/tray, handling PTY terminals, integrating WebRTC/audio, or packaging with electron-builder. Covers patterns from AudioBash, Yap, and Pisscord projects.
academic-writing
by jamditisAcademic writing, research methodology, and scholarly communication workflows. Use when writing papers, literature reviews, grant proposals, conducting research, managing citations, preparing for peer review, choosing OA routes under Plan S / 2026 OSTP Nelson Memo, posting preprints, working with persistent identifiers (ORCID, DOI, ROR), assigning CRediT contributor roles, preregistering analyses on OSF / AsPredicted, or disclosing LLM use to journals and funders. Essential for researchers, graduate students, and academics across disciplines.
accessibility-compliance
by jamditisWeb accessibility patterns for news sites, journalism tools, and academic platforms. Use when building accessible interfaces, auditing existing sites for WCAG compliance, writing alt text for news images, creating accessible data visualizations, or ensuring content reaches all readers including those using assistive technologies. Essential for newsroom developers and anyone publishing web content.
mobile-debugging
by jamditisRemote JavaScript console access and debugging on mobile devices. Use when debugging web pages on phones/tablets, accessing console errors without desktop DevTools, testing responsive designs on real devices, or diagnosing mobile-specific issues. Covers Eruda, vConsole, Chrome/Safari remote debugging, and cloud testing platforms.
python-pipeline
by jamditisPython data processing pipelines with modular architecture. Use when building content processing workflows, implementing dispatcher patterns, integrating Google Sheets/Drive APIs, or creating batch processing systems. Covers patterns from rosen-scraper, image-analyzer, and social-scraper projects.
test-first-bugs
by jamditisThis skill should be used when the user reports a bug, describes unexpected behavior, says something is "broken", "not working", "failing", mentions an "error", "issue", or "problem" in code, or asks to "fix" something. Enforces test-driven bug fixing workflow.
vibe-coding
by jamditisMethodology for effective AI-assisted software development. Use when helping users build software with AI coding assistants, debugging AI-generated code, planning features for AI implementation, managing version control in AI workflows, or when users mention "vibe coding," Claude Code, Cursor, GitHub Copilot, Aider, Continue, Cline, Codex, Windsurf, or similar AI coding tools. Provides strategies for planning, testing, debugging, and iterating on code written with LLM assistance.
web-scraping
by jamditisWeb scraping with anti-bot bypass, content extraction, undocumented APIs and poison pill detection. Use when extracting content from websites, handling paywalls, implementing scraping cascades or processing social media. Covers requests, trafilatura, Playwright with stealth mode, yt-dlp and instaloader patterns.
web-ui-best-practices
by jamditisSigns of taste in web UI. Use when building or reviewing any user-facing web interface — dashboards, SaaS apps, marketing sites, internal tools. Covers interaction speed, navigation depth, visual restraint, copy quality, and the small details that separate polished products from rough ones.
ai-writing-detox
by jamditisEliminate AI-generated writing patterns that erode reader trust. Activate when writing articles, documentation, press releases, or any content where AI patterns would undermine credibility. For journalists using AI assistance who need human-sounding output.
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.