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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macos-release
by fayazaraRelease a native macOS app to GitHub with DMG packaging and Sparkle appcast updates. Use this skill whenever the user wants to publish a new version, create a release, ship an update, push a release to GitHub, or update the appcast. Also trigger when the user mentions DMG creation, Sparkle signing, notarization, archiving, or anything related to distributing a new version of their macOS app. This covers the full release pipeline: archive, notarize, export, create DMG, sign with Sparkle EdDSA, update appcast.xml, git push, and GitHub release creation.
macos-settings-ui
by fayazaraBuild a proper macOS settings/preferences window with liquid glass support for macOS 26 (Tahoe). Use this skill whenever the user asks to create a settings window, preferences UI, settings view, or preferences pane for a macOS app. Also trigger when the user mentions "liquid glass settings", "NavigationSplitView settings", "grouped Form settings", "macOS settings layout", or wants to add/fix/rebuild a settings screen in any native macOS SwiftUI app. This includes phrases like "add settings to my app", "create a preferences window", "my settings look wrong", "fix my settings UI", or even just "I need a settings view". If the user is building a macOS app and mentions settings or preferences in any context, use this skill.
macos-auto-update
by fayazaraAdd Sparkle auto-update support to a native macOS app. Use this skill whenever the user wants to add auto-updates, implement Sparkle, set up an appcast feed, add "Check for Updates" to their app, or integrate automatic update checking. Also trigger when the user mentions Sparkle, appcast, SUFeedURL, EdDSA signing, or update notifications. This covers the full setup: adding the Sparkle SPM dependency, creating the UpdaterManager singleton, wiring it into the app delegate and UI, configuring Info.plist, and generating the initial appcast.xml.
macos-build
by fayazaraBuild a native macOS app using xcodebuild from the command line. Use this skill whenever the user asks to build, compile, or check if their macOS project compiles successfully. Also use it when the user asks to fix build errors, verify changes compile, or run a debug build. Trigger on phrases like "build the app", "does it compile", "run xcodebuild", "fix build errors", or even just "build".
macos-patterns
by fayazaraEssential native macOS development patterns that web developers don't know about. Use this skill whenever the user is building a macOS app and needs guidance on native patterns, or when they ask about menu bar apps, floating panels, window levels, keyboard shortcuts, file pickers, clipboard, drag and drop, screen capture, activation policy, Quick Look, launch at login, or any macOS-specific API. Also trigger when the user seems to be applying web development patterns to macOS (e.g., using z-index thinking for windows, expecting simple clipboard APIs, or not understanding focus/activation). This is the "how things actually work on macOS" reference that prevents the AI from generating confident but wrong code. Use this skill proactively whenever building any native macOS app.
macos-notch-ui
by fayazaraAdd a Dynamic Island-style notch UI to a macOS app. Use this skill whenever the user wants to create a notch overlay, notch extender, Dynamic Island for Mac, notch indicator, or any UI that extends from the MacBook notch area. Also trigger when the user mentions "notch shape", "notch window", "notch cutout", "notch panel", "recording indicator near the notch", "Dynamic Island style", or wants to show status/content that appears to emerge from the hardware notch. This covers the NSPanel setup, the NotchShape with concave Bezier ear curves, screen positioning math, spring animations, and show/hide choreography.
release-screendrop
by fayazaraRelease the Screendrop macOS app to GitHub using the screendrop-release CLI tool. Use this skill whenever the user wants to publish a new version, create a release, ship an update, cut a build, push a release to GitHub, or update the appcast. Also use when they mention archiving, notarization, DMG creation, Sparkle signing, bumping the version/build, or anything related to building and distributing a new Screendrop version.
build-openshot
by fayazaraBuild the Screendrop macOS app using xcodebuild. Use this skill whenever the user asks to build, compile, or check if the Screendrop project compiles successfully. Also use it when the user asks to fix build errors, verify changes compile, or run a debug build.
build-kaze
by fayazaraBuild the Kaze macOS app using xcodebuild. Use this skill whenever the user asks to build, compile, or check if the Kaze project compiles successfully. Also use it when the user asks to fix build errors, verify changes compile, or run a debug build.
release-kaze
by fayazaraRelease the Kaze macOS app to GitHub using the kaze-release CLI tool. Use this skill whenever the user wants to publish a new version, create a release, ship an update, push a release to GitHub, or update the appcast. Also use when they mention DMG creation, Sparkle signing, or anything related to distributing a new Kaze version.
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.