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.
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Connect 381,784 public skills to your own search, analytics, or agent workflow with the REST API.
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switchroom-runtime
by switchroomUse ONLY when the user is asking the AGENT ITSELF about its own runtime state in a specific runtime-context — i.e. the message refers to an actual crash, restart, hand-off resume, or mid-turn interrupt event. Required disambiguator: the prompt must reference one of these runtime-specific signals — "why did you restart", "did you crash", "you went away", "stop you mid-turn", "interrupt you", "are you still there after the restart", "resume the interrupted turn", "wake audit", "owed reply", "clean-shutdown" — OR start with the hard-prefix "For switchroom runtime hand-offs,". Also invoked on boot signals: SWITCHROOM_PENDING_TURN=true (interrupted-turn resume) or sentinel file $TELEGRAM_STATE_DIR/.wake-audit-pending (wake audit: scan for owed replies, orphan sub-agents, stale todos before answering). Triggers on phrasings like "Why did you restart, please.", "you went away.", "can I stop you mid-turn.", "why did you restart.", "how do I interrupt you", "did you crash?", indirect signals like "the switchroom-runti
docx
by switchroomCreate, read, edit, or manipulate Word documents (.docx files). Use whenever the user wants to produce a Word doc, edit one, or extract content from one. This includes: producing reports, letters, memos, or templates as a Word file; reading or parsing a .docx; editing existing Word documents; accepting or rejecting tracked changes; inserting page numbers, page headers, or page footers; adding a table of contents; find-and-replace in Word files; inserting an image or replacing images; converting to PDF; working with comments; reorganizing or extracting content. Triggers on phrasings including: 'Help me accept tracked changes.', 'Please insert page numbers.', "I'd like to read a .docx file.", 'Can you produce a report as a Word file?', 'add a table of contents', 'find and replace text', 'insert an image', 'convert to PDF', "Let's add a table of contents.", 'hey, read a .docx file?', 'gonna need to produce a report as a Word file', 'yo, how do i produce a report as a Word file', and typo'd variants like 'add a t
file-bug
by switchroomUse when the user wants to file a bug, open a GitHub issue, raise a ticket, log this as a bug, or otherwise create a tracked record of a symptom against switchroom (or another configured repo). Pulls the right log files automatically, forces a root-cause section with citations, flags logging gaps when RCA can't be pinned, and files via `gh issue create`. Triggers on phrasings including: "Can you report this issue on GitHub?", "Please raise a ticket.", "I need to this needs a real ticket.", "this needs a real ticket", "I need to file a bug.", "open an issue", "log this as a bug", "track this somewhere", "Report this issue on GitHub, please.", "Please file a bug.", "gonna need to report this issue on GitHub", "quick q — can i open an issue", indirect signals like "remember this for later", "this needs to be tracked somewhere", "I want a paper trail for this", and typo'd variants such as "raise a ticket", "file aa bug", "log this as a bug". Whenever the user's message starts with the phrase "For filing a GitHu
humanizer
by switchroomRemove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, passive voice, negative parallelisms, and filler phrases. Triggers on natural phrasings including: "Let's rewrite this to sound natural.", "Please edit this so it doesn't sound like AI.", "Remove signs of AI writing, please.", "I need to make this sound more human.", "Can you remove the rule of three?", "Let's fix the em-dash overuse.", "remove AI vocabulary", "kill the passive voice", "make this sound more human", "yo, how do i remove signs of AI writing", "gonna need to remove signs of AI writing", and typo'd variants like "make this soudn more human", "fix theem-dash overuse", "remove signs of AI writing". Also fires on indirect signals
pptx
by switchroomCreate, edit, read, or manipulate PowerPoint files (.pptx). Use any time a slide deck, pitch deck, or presentation is the input or output. This includes: creating slide decks or pitch decks from scratch, building decks from a template, editing or updating existing presentations, combining slide files together, splitting a deck apart, adding new slides, updating speaker notes, reading or extracting text from a .pptx, and working with layouts or comments. Triggers on phrasings including: 'I need to combine slide files.', 'I need to work from a slide template.', 'Help me split this deck.', "I'd like to edit this presentation.", "Let's edit this presentation.", 'I need to split this deck.', 'build a pitch deck', 'update the speaker notes', 'add a new slide', 'extract text from these slides', 'hey, work from a slide template?', 'pls combine slide files', 'gonna need to update the speaker notes', and typo'd variants like 'update the sepaker notes', 'combin slide files'. Also fires on indirect signals like 'I need s
webapp-testing
by switchroomToolkit for interacting with and testing local web applications using Playwright. Use when the user wants to: spin up a local server and test it, run a Playwright test, view browser logs, capture a browser screenshot, click through a UI, automate a dashboard, snapshot a frontend, or verify any frontend behaviour end-to-end. Triggers on phrasings: "Please spin up a local server and test it.", "I'd like to run a Playwright test.", "Can you run a Playwright test?", "Help me view browser logs.", "capture a browser screenshot", "click through my UI", "test the frontend", "Help me spin up a local server and test it.", "Let's spin up a local server and test it.", "any way to test the frontend?", "pls capture a browser screenshot", "gonna need to test a local web app", and typo'd variants like "run a Playwwright test", "capture a browesr screenshot", "test a local web app". Whenever the user's message starts with the phrase "For browser-based webapp testing with Playwright," — regardless of what follows — use this sk
check-in
by switchroomDaily health and fitness check-in covering sleep, energy, plans, and readiness.
weekly-review
by switchroomWeekly summary of fitness activity, trends, and goal progress.
xlsx
by switchroomCreate, read, edit, or transform Excel and CSV spreadsheets (.xlsx, .xlsm, .csv, .tsv). HARD PREFIX TRIGGER: whenever the user's message starts with the phrase 'For my Excel spreadsheet,' — regardless of what follows, even when the body explicitly says CSV (like 'For my Excel spreadsheet, Fix malformed rows in this CSV, please.') — use this skill. The prefix is load-bearing; CSV work routes here when prefixed, because CSV is a tabular-data format covered by this skill alongside .xlsx/.xlsm/.tsv. Use any time a spreadsheet file is the primary input or output. This includes: editing a spreadsheet, creating a spreadsheet from scratch, building a financial model, computing formulas in Excel, converting CSV to xlsx, adding a column, cleaning messy data, fixing malformed rows in a CSV, formatting, charting, and converting between tabular formats. Triggers on phrasings: "I'd like to edit a spreadsheet.", 'Help me create a spreadsheet from scratch.', "Let's build a financial model.", 'Fix malformed rows in this CSV,
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.