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...
bump-native-sdk
by adaptyteamUse when upgrading native iOS or Android SDK dependency versions in the AdaptySDK React Native project — bumping Adapty pods version or Android gradle dependency versions
ios-sdk-reference
by adaptyteamUse when you need to read, understand, or reference the native iOS AdaptySDK-iOS source code — for understanding bridge contracts, porting new features, debugging native behavior, or checking JSON request/response formats
start-devtools
by adaptyteamStart Adapty Devtools app for SDK testing. Use when need to run, launch, or test the devtools example app on iOS or Android simulator/emulator.
upgrade-native-sdk
by adaptyteamUse when upgrading native iOS or Android SDK dependency versions in AdaptySDK-Capacitor. Triggered by requests like "bump ios sdk", "upgrade android native", "update native dependency version".
adapty-cli
by adaptyteamUse when setting up or managing Adapty in-app subscriptions, paywalls, or placements via CLI.
review-assistant
by adaptyteamWalk through unresolved GitHub PR review comments one by one, suggest fixes, and track resolution in a local file. Use when the user wants to address PR feedback.
snippet-master
by adaptyteamUse when adding, reviewing, or fixing code snippets in Adapty technical documentation across any of the 7 SDK platforms: iOS, Android, React Native, Flutter, Unity, Kotlin Multiplatform, or Capacitor.
sync-branch-to-develop
by adaptyteamUse when finishing work on a feature branch and wanting to promote it to develop (or another integration branch) while staying on the original branch. Handles commit, push, merge, push develop, and return.
update-whats-new
by adaptyteamUse when adding a new monthly section to src/content/docs/release-notes/whats-new.mdx — gathers commits to main over a date range, identifies user-facing updates worth featuring, confirms scope with the user, then drafts the section in the existing style.
writing-planner
by adaptyteamUse when planning documentation before writing — for new articles, updates to existing docs, or structural changes. Also use when reviewing the structure of an existing article without writing it yet.
doc-author
by adaptyteamUse when documentation needs to be planned and written end-to-end — from a Jira task, feature spec, or verbal description through to a polished draft. Not for review-only or planning-only tasks.
product-manager
by adaptyteamUse when reviewing documentation from a product perspective — whether feature value is clear, onboarding flow makes sense, or technical descriptions align with real user experience. Does not check writing style.
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.