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...
using-agent-brain
by SpillwaveSolutionsExpert Agent Brain skill for document search with BM25 keyword, semantic vector, hybrid, graph, and multi retrieval modes. Use when asked to "search documentation", "query domain", "find in docs", "bm25 search", "hybrid search", "semantic search", "graph search", "multi search", "find dependencies", "code relationships", "searching knowledge base", "querying indexed documents", "finding code references", "exploring codebase", "what calls this function", "find imports", "trace dependencies", "brain search", "brain query", "knowledge base search", "cache management", "clear embedding cache", "cache hit rate", or "cache status". Supports multi-instance architecture with automatic server discovery. GraphRAG mode enables relationship-aware queries for code dependencies and entity connections. Pluggable providers for embeddings (OpenAI, Cohere, Ollama) and summarization (Anthropic, OpenAI, Gemini, Grok, Ollama). Supports multiple runtimes (Claude Code, OpenCode, Gemini CLI) with shared .agent-brain/ data directory,
mastering-python-skill
by SpillwaveSolutionsModern Python coaching covering language foundations through advanced production patterns. Use when asked to "write Python code", "explain Python concepts", "set up a Python project", "configure Poetry or PDM", "write pytest tests", "create a FastAPI endpoint", "run uvicorn server", "configure alembic migrations", "set up logging", "process data with pandas", or "debug Python errors". Triggers on "Python best practices", "type hints", "async Python", "packaging", "virtual environments", "Pydantic validation", "dependency injection", "SQLAlchemy models".
configuring-agent-brain
by SpillwaveSolutionsInstallation and configuration skill for Agent Brain document search system. Use when asked to "install agent brain", "setup agent brain", "configure agent brain", "setting up document search", "installing agent-brain packages", "configuring API keys", "initializing project for search", "troubleshooting agent brain", "pip install agent-brain", "agent brain not working", "agent brain setup error", "configure embeddings provider", "setup ollama for agent brain", "agent brain environment variables", "install agent brain mcp", "configure mcp server", or "connect agent brain to claude desktop". Covers package installation (server, CLI, MCP), provider configuration, project initialization, and server management.
design-doc-mermaid
by SpillwaveSolutionsCreate Mermaid diagrams (activity, deployment, sequence, architecture) from text descriptions or source code. Use when asked to "create a diagram", "generate mermaid", "document architecture", "code to diagram", "create design doc", or "convert code to diagram". Supports hierarchical on-demand guide loading, Unicode semantic symbols, and Python utilities for diagram extraction and image conversion.
project-memory
by SpillwaveSolutionsSet up and maintain a structured project memory system in docs/project_notes/ that tracks bugs with solutions, architectural decisions, key project facts, and work history. Use this skill when asked to "set up project memory", "track our decisions", "log a bug fix", "update project memory", or "initialize memory system". Configures both CLAUDE.md and AGENTS.md to maintain memory awareness across different AI coding tools.
sdd
by SpillwaveSolutionsThis skill should be used when users want guidance on Spec-Driven Development methodology using GitHub's Spec-Kit. Guide users through executable specification workflows for both new projects (greenfield) and existing codebases (brownfield). After any SDD command generates artifacts, automatically provide structured 10-point summaries with feature status tracking, enabling natural language feature management and keeping users engaged throughout the process.
confluence
by SpillwaveSolutionsManage Confluence documentation with downloads, uploads, conversions, and diagrams. Use when asked to "download Confluence pages", "upload to Confluence", "convert Wiki Markup", "sync markdown to Confluence", "create Confluence page", or "handle Confluence images".
plantuml
by SpillwaveSolutionsGenerate PlantUML diagrams from text descriptions and convert them to PNG/SVG images. Use when asked to "create a diagram", "generate PlantUML", "convert puml to image", "extract diagrams from markdown", or "prepare markdown for Confluence". Supports all PlantUML diagram types including UML (sequence, class, activity, state, component, deployment, use case, object, timing) and non-UML (ER diagrams, Gantt charts, JSON/YAML visualization, mindmaps, WBS, network diagrams, wireframes, and more).
mastering-python-skill
by SpillwaveSolutionsModern Python coaching covering language foundations through advanced production patterns. Use when asked to "write Python code", "explain Python concepts", "set up a Python project", "configure Poetry or PDM", "write pytest tests", "create a FastAPI endpoint", "run uvicorn server", "configure alembic migrations", "set up logging", "process data with pandas", or "debug Python errors". Triggers on "Python best practices", "type hints", "async Python", "packaging", "virtual environments", "Pydantic validation", "dependency injection", "SQLAlchemy models".
using-claude-code-cli
by SpillwaveSolutionsInvoke Claude Code CLI from Python orchestrators and shell scripts. Use when asked to "spawn claude as subprocess", "automate claude cli", "run claude headless", "configure --allowedTools", "set up claude hooks", or "parallel claude invocation". Covers permissions, directory access (--add-dir), hooks, sandbox mode, and async patterns.
design-doc-mermaid
by SpillwaveSolutionsCreate Mermaid diagrams (activity, deployment, sequence, architecture) from text descriptions or source code. Use when asked to "create a diagram", "generate mermaid", "document architecture", "code to diagram", "create design doc", or "convert code to diagram". Supports hierarchical on-demand guide loading, Unicode semantic symbols, and Python utilities for diagram extraction and image conversion.
documentation-specialist
by SpillwaveSolutionsThis skill should be used when creating professional software documentation (SRS, PRD, OpenAPI, user manuals, tutorials, runbooks) from templates (greenfield) or reverse-engineering documentation from existing code like Spring Boot or FastAPI (brownfield). Also handles documentation audits/reviews, format conversion (Markdown, DOCX, PDF), and diagram generation (C4, Mermaid, PlantUML, ER, sequence). Use when asked to "create documentation", "document my code", "write SRS", "generate PRD", or "documentation specialist".
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.