381,784 Collected SKILL.md files

Explore AI Agent Skills & Claude Prompts

Discover open-source agent skills for Claude Code, Codex, ChatGPT, and any tool that uses SKILL.md.

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Showing 8 of 8 skills
lvndry

journal

by lvndry
star 46

Support reflection and journaling with prompts and structure. Use when the user wants to journal, reflect on their day, practice gratitude, or get writing prompts for personal reflection.

navigation main article SKILL.md
schedule Updated 4 months ago
lvndry

calendar

by lvndry
star 46

Manage calendars using khal CLI and vdirsyncer. Use when the user wants to view, create, edit, or delete calendar events, sync calendars with CalDAV servers, manage multiple calendars, or mentions "calendar", "event", "appointment", "meeting", "schedule", "CalDAV", "khal", "vdirsyncer".

navigation main article SKILL.md
schedule Updated 4 months ago
lvndry

email

by lvndry
star 46

Manage emails via Himalaya CLI. Use when the user wants to read, send, search, or organize emails. Triggers on "email", "inbox", "send email", "check mail", "reply to", "forward", or mentions of Gmail, Outlook, iCloud, Proton Mail.

navigation main article SKILL.md
schedule Updated 4 months ago
lvndry

meeting-notes

by lvndry
star 46

Summarize meetings and extract action items. Use when processing meeting transcripts, notes, or recordings to get summaries, decisions, and follow-ups.

navigation main article SKILL.md
schedule Updated 4 months ago
lvndry

todo

by lvndry
star 46

Create and track task lists for complex multi-step work. Use when planning projects, breaking down work, tracking progress, or when a task has 3+ steps. Triggers on "plan", "todo", "task list", "break down", "step by step", or complex requests requiring multiple actions.

navigation main article SKILL.md
schedule Updated 4 months ago
lvndry

decision-log

by lvndry
star 46

Record and retrieve decisions with context, options, and rationale. Use when documenting a decision, reviewing past decisions, or answering "why did we choose X?"

navigation main article SKILL.md
schedule Updated 4 months ago
lvndry

browser-use

by lvndry
star 46

Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, or extract information from web pages. Also use when asking about information that can't be easily found via API (e.g., train tickets, flight prices, hotel rates, etc.).

navigation main article SKILL.md
schedule Updated 4 months ago
lvndry

startup-brainstorm

by lvndry
star 46

Brainstorm startup ideas using top-founder mental models, trend analysis, and competition research. Use when the user wants to brainstorm startup ideas, explore business opportunities, validate concepts, or think like elite founders. Triggers on "startup ideas", "business ideas", "what should I build", "startup brainstorm", "idea validation", "trends and opportunities", "think like a founder".

navigation main article SKILL.md
schedule Updated 4 months ago
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Browse Agent Skills by Occupation

23 major groups · 867 SOC occupations

Browse by Category

Explore agent skills organized by their primary use case

SKILLMD / CREATORS AND OCCUPATION CATEGORIES

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.

SEO KNOWLEDGE HUB & TECHNICAL OVERVIEW

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.

8 QUESTIONS

Frequently Asked Questions

A practical guide to agent skills: what they are, how to inspect them, and how SkillMD helps you explore the ecosystem.