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...
automation
by ai-ecoverseUse this when setting up event-driven automation in SLICC — webhooks, cron tasks, or filesystem watchers that route events to scoops. Covers `webhook`, `crontask`, and `fswatch` shell commands. Read this BEFORE wiring up anything that should fire on a schedule, an HTTP call, or a VFS change.
dips
by ai-ecoverseUse this whenever a response could benefit from richer visualization, guided interaction, or a touch of fun — pickers, calculators, sliders, mini explorers, charts, animated demos, choose-your-own-adventure prompts, anything that lands better as a hydrating widget than as plain prose. Dips are ephemeral `shtml` code blocks rendered inline in chat (no state persistence, lick-only). Reach for them generously: every interactive moment the user gets is a moment they don't have to type a clarifying message. For persistent dashboards, editors, or multi-page apps use sprinkles instead.
oryx
by ai-ecoverseInteract with the ZSA Oryx keyboard configurator (oryx.zsa.io, configure.zsa.io) via its GraphQL API — list, inspect, edit, and compile layouts for ZSA Voyager, Moonlander, and ErgoDox EZ keyboards. Use when the user wants to automate ZSA / Oryx, dump a keyboard layout, edit layers or keys without clicking through the configurator UI, fork a revision, change layout privacy, set tags, trigger a firmware compile, download .bin / .zip firmware bundles, manage combos, or run any GraphQL query against the Oryx backend. Activate on mentions of zsa, oryx, voyager, moonlander, ergodox, keyboard layout, keymap, qmk, layer, combo, key code (KC_*), firmware compile, hex file, or related workflows.
mixtape
by ai-ecoverseCreate themed music playlists and mixtapes with curated song lists, descriptions, and cover art prompts. Use when the user asks to build a playlist, create a mixtape, curate songs around a theme, or wants music recommendations organized as a cohesive collection. Triggers on requests like "make me a playlist", "build a mixtape", "curate songs about...", "themed playlist for...".
icloud
by ai-ecoverseInteract with iCloud Calendar and Notes from a signed-in iCloud browser tab. Use when the user asks about their calendar, upcoming events, schedule, or wants to read/search their Apple Notes. Triggers on phrases like "what's on my calendar", "upcoming events", "my notes", "search notes", "read note", "iCloud calendar", "iCloud notes".
world
by ai-ecoverseA second minimal demo skill used to show that x927's Tessl target auto-expands a skills-directory pointer into the per-skill record form Tessl expects.
hello
by ai-ecoverseA minimal demo skill for x927's app-builder example. Says hello — use when the user greets the agent and asks for a friendly reply.
gh-monday
by ai-ecoverseRanked GitHub triage — show what needs attention right now. Scans open PRs, issues, local repos, and AI coding sessions, then prioritizes by who acted last. Use when: (1) starting the day or week, (2) triaging GitHub notifications, (3) checking what needs attention, (4) reviewing PR queue, (5) finding stale work. Triggers on: "what should I work on", "Monday morning", "triage my GitHub", "what needs my attention", "check my PRs", "review queue", "It's Monday again", "weekly triage", "what's waiting on me", "GitHub status", "open PRs", "clean my inbox", "dismiss noise", "notification triage", "unread notifications".
gh-monday
by ai-ecoverseRanked GitHub triage — show what needs attention right now. Scans open PRs, issues, local repos, and AI coding sessions, then prioritizes by who acted last. Use when: (1) starting the day or week, (2) triaging GitHub notifications, (3) checking what needs attention, (4) reviewing PR queue, (5) finding stale work. Triggers on: "what should I work on", "Monday morning", "triage my GitHub", "what needs my attention", "check my PRs", "review queue", "It's Monday again", "weekly triage", "what's waiting on me", "GitHub status", "open PRs", "clean my inbox", "dismiss noise", "notification triage", "unread notifications".
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.