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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cli-command-development
by SAP-samplesCreate or update CLI commands, routes, utilities, and tests in this repo. Use when adding or modifying bin/*, routes/*, utils/*, or related tests.
mcp-server-workflows
by SAP-samplesCreate or update MCP server tools, JSON-RPC handlers, and registrations. Use when working in mcp-server/src/**.
docs-automation
by SAP-samplesAutomate docs updates and command documentation generation. Use for generate-command-docs, enhance-command-docs, sidebar generation, and VitePress build checks.
scrape-and-load
by SAP-samplesRun the Wookieepedia scraper, convert data, load into SQLite, and verify with migration and full tests.
cap-change-workflow
by SAP-samplesUse for end-to-end CAP change workflows: modify CDS/handlers, regenerate artifacts, and run a short verification checklist for this repository.
load-and-test
by SAP-samplesRebuild CDS artifacts, reload SQLite fixture data, and run the full test suite. Use after schema or service changes.
btp-cli
by SAP-samplesComprehensive SAP BTP command line interface (btp CLI) assistant for generating commands, automating multi-step workflows, and troubleshooting errors. Use this skill whenever the user mentions "btp", "BTP CLI", "SAP BTP command line", subaccount management via CLI, entitlement assignment via terminal, service instance creation with btp, role collection assignment from the command line, or any task involving the SAP Business Technology Platform CLI — even if they just say something like "set up my BTP subaccount" or "how do I log in to my global account from the terminal". Also trigger when the user asks about scripting or automating SAP BTP operations, parsing btp output with jq, or managing Cloud Foundry / Kyma environments through the btp CLI.
joule-cli
by SAP-samplesComprehensive SAP Joule CLI (formerly sapdas CLI) assistant for managing digital assistants from the command line — compiling capabilities, deploying assistants, running BDD tests, linting, and troubleshooting errors. Use this skill whenever the user mentions "joule cli", "sapdas", "joule compile", "joule deploy", "joule test", "joule login", "joule lint", digital assistant deployment, capability compilation, DAAR files, RTA artifacts, or any task involving the Joule command line interface — even if they just say something like "deploy my assistant" or "how do I log in to Joule from the terminal". Also trigger when the user asks about testing Joule capabilities with Cucumber, linking AI assistants, managing deployed assistants, or automating Joule workflows in CI/CD pipelines.
joule-a2a-agent
by SAP-samplesGenerate and deploy a pro-code AI agent using LangGraph and SAP GenAI Hub, deploy it to SAP BTP Cloud Foundry, create a Joule capability with A2A (Agent-to-Agent) action, and deploy it to Joule. Supports TypeScript (Express or CAP) and Python. Use this skill whenever the user mentions: building a custom agent for Joule, deploying an AI agent to BTP Cloud Foundry, A2A protocol integration with Joule, pro-code agent extensibility, LangGraph agent on SAP BTP, connecting an external agent to Joule, "bring your own agent" for Joule, creating a Joule capability with A2A action, CAP agent, MTA deployment, or any combination of LangGraph/A2A/Joule/BTP/Cloud Foundry/CAP in an agent development context. Also trigger when the user wants to scaffold, modify, or redeploy an existing A2A agent project.
cf-cli
by SAP-samplesComprehensive Cloud Foundry CLI (cf CLI v8) assistant for generating commands, automating app deployments, managing services, and troubleshooting errors. Use this skill whenever the user mentions "cf", "cf cli", "Cloud Foundry", "cf push", "cf login", "cf target", app deployment to CF, service binding, buildpacks, routes, domains, orgs and spaces, manifests, or any task involving the Cloud Foundry command line — even if they just say something like "push my app" or "how do I bind a service". Also trigger when the user asks about scaling apps, managing environment variables in CF, creating user-provided services, rolling deployments, SSH into app containers, or writing CF manifests.
parity-sync
by SAP-samplesAdd or update a method across hdb/hdbext packages with ESM/CJS/type parity. Use when changing runtime API in either package.
doc-sync
by SAP-samplesAudit AI guidance files (CLAUDE.md, copilot-instructions.md, .github/agents/, .github/prompts/) for consistency. Use after updating any AI-facing documentation.
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.