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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automem-regression-drift-scout
by verygoodpluginsInspect AutoMem CI, benchmark health, and deployment drift as a read-only recurring automation; use for scheduled Codex maintenance runs before proposing issues or PR plans.
automem
by verygoodpluginsPersistent AutoMem memory via the legacy curl-based AutoMem skill.
automem
by verygoodpluginsPersistent AutoMem memory via mcporter-exposed AutoMem tools.
automem
by verygoodpluginsPersistent AutoMem memory via the native AutoMem OpenClaw plugin tools.
memory-management
by verygoodpluginsPersistent memory management for Claude Code via AutoMem. Use this skill when: - Starting a session (recall project context, decisions, patterns) - Making architectural decisions or library choices - Fixing bugs (store root cause and solution) - Learning user preferences or code style - Debugging issues (search for similar past problems)
automem
by verygoodpluginsDeprecated compatibility template. Prefer the OpenClaw plugin; use skill-mcp or skill-legacy only when you specifically need those modes.
streamdeck-designer
by verygoodpluginsDesign, theme, and author complete Stream Deck layouts for the user's hardware using the streamdeck-mcp tools. Use whenever the user wants a custom Stream Deck setup, asks for a themed deck (e.g. "hello-kitty Twitch deck", "retrowave music controls", "a dev deck for this repo"), wants buttons or dials configured for specific apps (OBS, Hue, Spotify, Home Assistant, Twitch, etc.), or asks Claude to "set up" / "build" / "make" / "configure" a Stream Deck page — even if they don't explicitly say "streamdeck-mcp" or "profile." Also triggers when they mention Stream Deck + / + XL dials, encoders, or the touch strip, or when they describe an aesthetic they want reflected on their deck.
release-wp-fusion-lite
by verygoodpluginsUse this skill whenever cutting, building, syncing, or deploying a new WP Fusion Lite release — pulling the latest code from the WP Fusion (Pro) plugin, stripping it down to the Lite feature set, curating the readme changelog, and shipping the release to wordpress.org via the SVN deploy workflow. Trigger on phrases like "release lite", "deploy wp-fusion-lite", "cut a lite release", "sync lite from pro", "push a new lite version", "update lite to match pro", "ship lite", or any task that involves copying Pro → Lite and publishing to the WordPress.org plugin directory.
time-tracking
by verygoodpluginsTime tracking with Toggl. Use this skill when: - Starting or stopping time entries - Checking current timer status - Generating time reports (daily, weekly, by project) - Reviewing productivity and time allocation - Managing projects and workspaces
memory-management
by verygoodpluginsPersistent memory management for Claude Code via AutoMem. Use this skill when: - Starting a session (recall project context, decisions, patterns) - Making architectural decisions or library choices - Fixing bugs (store root cause and solution) - Learning user preferences or code style - Completing significant work (store summary) - Debugging issues (search for similar past problems)
support-workflow
by verygoodpluginsSupport ticket workflow for FreeScout helpdesk. Use this skill when: - Processing support tickets (triage, analyze, respond) - Searching for tickets by status, assignee, or keywords - Managing ticket status and assignments - Drafting personalized customer responses - Adding internal notes for team collaboration
analytics-review
by verygoodpluginsWebsite analytics with Pirsch. Use this skill when: - Reviewing website traffic and engagement - Analyzing visitor trends and patterns - Checking top pages and referrers - Comparing performance across time periods - Understanding UTM campaign effectiveness
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.