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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xlsx
by henkisdabroComprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualisation. Use when working with spreadsheets (.xlsx, .xlsm, .csv, .tsv) for creating new spreadsheets with formulas and formatting, reading or analysing data, modifying existing spreadsheets while preserving formulas, data analysis and visualisation, or recalculating formulas. Do NOT use for plain CSV/TSV manipulation when no formulas, formatting, or multi-sheet workbook structure is needed - plain text tooling is faster. Do NOT use for BigQuery or warehouse-scale SQL analysis.
webapp-testing
by henkisdabroToolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behaviour, capturing browser screenshots, and viewing browser logs. Use when user asks to test a web app, verify UI, capture screenshots, check browser logs, or debug frontend issues. Do NOT use for Chrome DevTools MCP setup or live-browser console/network triage - use the devtools skill instead. Do NOT use for unit-level component testing (Vitest/Jest cover that).
pdf-extract
by henkisdabroFast, zero-AI text extraction from PDFs that have a text layer (digitally created PDFs from Word, Typst, WeasyPrint, wkhtmltopdf, LaTeX, etc). Uses pymupdf (fitz) - instant and deterministic. Use when you need to quickly pull raw text from a known text-layer PDF, e.g. "extract text from this PDF", "read this PDF", "get the content of", "what does this PDF say", "quickly read this PDF". Do NOT use for scanned/image PDFs or when you need structured output (tables, headings, OCR, AI analysis) - use the pdf-processing-pro skill in this plugin for those cases.
pdf-processing-pro
by henkisdabroProduction-ready PDF processing with forms, tables, OCR, validation, and batch operations. Use when working with complex PDF workflows in production environments, processing large volumes of PDFs, or requiring robust error handling and validation. Do NOT use for simple text extraction - use pdf-extract for quick reads.
ffmpeg-cli
by henkisdabroFFmpeg CLI reference for video and audio processing, format conversion, filtering, and media automation. Use when converting video formats, resizing or cropping video, trimming by time, replacing or extracting audio, mixing audio tracks, overlaying text or images, burning subtitles, creating GIFs, generating thumbnails, building slideshows, changing playback speed, encoding with H264/H265/VP9, setting CRF/bitrate, using GPU acceleration, creating storyboards, or running ffprobe. Covers filter_complex, stream selectors, -map, -c copy, seeking, scale, pad, crop, concat, drawtext, zoompan, xfade. Do NOT use for image-only processing (use ImageMagick), live-streaming server setup (use OBS/nginx-rtmp), or NLE-style timeline editing (use a video editor).
google-ads-scripts
by henkisdabroExpert guidance for Google Ads Script development including AdsApp API, campaign management, ad groups, keywords, bidding strategies, performance reporting, budget management, automated rules, and optimisation patterns. Use when automating Google Ads campaigns, managing keywords and bids, creating performance reports, implementing automated rules, optimising ad spend, working with campaign budgets, monitoring quality scores, tracking conversions, pausing low-performing keywords, adjusting bids based on ROAS, or building Google Ads automation scripts. Covers campaign operations, keyword targeting, bid optimisation, conversion tracking, error handling, and JavaScript-based automation in the Google Ads scripts editor. Do NOT use for the Google Ads API (Python/REST/gRPC) - this is Ads Scripts only. Do NOT use for Microsoft Ads, Meta Ads, or other non-Google ad platforms.
docx
by henkisdabroComprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. Use when working with professional documents (.docx files) for creating new documents, modifying or editing content, working with tracked changes, adding comments, or any other document tasks. Do NOT use for plain-text Markdown drafting, PDF work (use pdf-extract or pdf-processing-pro), or rich rendered email/WhatsApp drafts (use the message plugin).
message
by henkisdabroCreate and edit rich text message drafts for Gmail, Outlook, and WhatsApp with live browser preview. Runs on Bun for near-instant cold start and opens the preview automatically. Use when writing emails, drafting emails, composing replies, sending messages, writing WhatsApp messages, or when user mentions Gmail, Outlook, WhatsApp, "email to", "reply to", "draft an email", "write an email", "send a message". Do NOT use for reading emails, managing contacts, or calendar invitations.
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.