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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backstage-custom-resource
by kadelThis skill should be used when the user asks to "create Backstage CR", "create RHDH custom resource", "configure rhdh-operator", "create Backstage manifest", "modify Backstage CR", "configure RHDH deployment", "add dynamic plugins to CR", "configure Backstage database", "set up Backstage route", "configure app-config for RHDH", "create rhdh.redhat.com/v1alpha Backstage", or mentions creating or modifying a Backstage Custom Resource for the rhdh-operator.
ghostty
by kadelThis skill should be used when the user asks to "open a split", "show markdown", "preview markdown", "render markdown in ghostty", "open ghostty split", "show file in split", or wants to control Ghostty terminal via AppleScript commands.
address-pr-comments
by kadelUse when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
gws-calendar
by kadelThis skill should be used when the user asks to 'check calendar', 'show agenda', 'create event', 'list events', 'schedule meeting', 'find free time', 'manage calendar', 'delete event', 'update event', or mentions Google Calendar operations using the gws CLI.
gws-docs
by kadelThis skill should be used when the user asks to 'create a document', 'read a Google Doc', 'write to a doc', 'append text to doc', 'get document content', 'update document', or mentions Google Docs operations using the gws CLI.
obsidian-cli
by kadelThis skill should be used when the user works with notes, Obsidian, vault, daily notes, tags, tasks, bookmarks, or any note-taking operations.
obsidian-knowledge-base
by kadelThis skill should be used when the user asks to ingest, query, or maintain the knowledge base, or mentions knowledge base operations in the Obsidian vault.
obsidian-notes
by kadelThis skill should be used when the user asks about vault structure, note organization, where to put notes, or needs context about how the Obsidian vault is organized.
rhdh-catalog-index
by kadelExtract and inspect the RHDH plugin catalog index OCI image to discover available plugins, their OCI artifact references, versions, and default wiring configurations. Use when you need to find plugin package names, versions, pluginConfig examples, or create a dynamic-plugins.yaml from the catalog.
rhdh-frontend-dynamic-plugin-bootstrap
by kadelThis skill should be used when the user asks to "create RHDH frontend plugin", "bootstrap frontend dynamic plugin", "create UI plugin for RHDH", "new frontend plugin for Red Hat Developer Hub", "add entity card to RHDH", "create dynamic route", "add sidebar menu item", "configure mount points", "create theme plugin", or mentions creating frontend components, UI pages, entity cards, or visual customizations for Red Hat Developer Hub or RHDH. This skill is specifically for frontend plugins - for backend plugins, use the separate backend plugin skill.
create-skill
by kadelGuides creation of Claude Code skills following official Anthropic best practices, including SKILL.md authoring, frontmatter, progressive disclosure, and validation. This skill should be used when the user asks to "create a skill", "new skill", "build a skill", "scaffold a skill", "write a SKILL.md", "design a skill", "add a skill to a plugin", "skill authoring", or wants guidance on skill structure, frontmatter fields, description triggers, or skill development. Do NOT use for non-Claude-Code skill concepts (game skill trees, resume skills, etc.).
rhdh-context
by kadelThis skill should be used whenever the user mentions "RHDH", "Red Hat Developer Hub", or "Developer Hub" in any context — whether asking questions, developing plugins, debugging, deploying, or discussing architecture. It provides essential background context about what RHDH is, how it differs from vanilla Backstage, and key nuances that affect all RHDH-related work.
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.