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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vbaexcel
by lunasoft2001Extraer y reimportar codigo VBA de archivos Excel .xlsm en Windows usando Python (pywin32/oletools) o VBScript. Usar para exportar modulos .bas, refactorizar en VS Code y volver a importar al XLSM.
vba-access
by lunasoft2001Extract, refactor, and re-import VBA modules (standard modules and class modules) from Microsoft Access databases (.accdb/.mdb) on Windows using Python and COM automation. Use when: exporting Access VBA code to .bas files for version control or editing in VS Code, importing refactored .bas files back into an Access database, enabling VBA project access in Access. Always creates a verified backup before any import — flow stops if no backup exists. Note: for full database analysis (tables, queries, forms, reports), use the access-analyzer skill instead. Triggers on: export VBA Access, import VBA Access, vba-access, Access VBA modules, accdb VBA, extraer módulos VBA Access, importar VBA Access, refactorizar VBA Access, módulos VBA Access, Access automation.
vba-powerpoint
by lunasoft2001Extract, refactor, and re-import VBA code from PowerPoint macro-enabled presentations (.pptm) and templates (.potm) on Windows using Python and COM automation. Use when: exporting PowerPoint VBA modules to .bas files for version control, editing presentation macros in VS Code, importing refactored modules back into a .pptm, enabling VBA project access in PowerPoint. Always creates a verified backup before any import — flow stops if no backup exists. Triggers on: export VBA PowerPoint, import VBA PowerPoint, vba-powerpoint, PowerPoint macros, pptm VBA, extraer macros PowerPoint, importar VBA PowerPoint, refactorizar macros PowerPoint, módulos VBA PowerPoint, PowerPoint automation, backup pptm.
vba-word
by lunasoft2001Extract, refactor, and re-import VBA code from Word macro-enabled documents (.docm) and templates (.dotm) on Windows using Python and COM automation. Use when: exporting Word VBA modules to .bas files for version control, editing Word macros in VS Code, importing refactored modules back into a .docm, enabling VBA project access in Word. Always creates a verified backup before any import — flow stops if no backup exists. Triggers on: export VBA Word, import VBA Word, vba-word, Word macros, docm VBA, extraer macros Word, importar VBA Word, refactorizar macros Word, módulos VBA Word, Word automation, backup docm.
vbaexcel
by lunasoft2001Extract and re-import VBA code from Excel .xlsm files on Windows using Python (pywin32/oletools) or VBScript. Use when: exporting VBA modules from XLSM, refactoring Excel macros in VS Code, importing .bas files back into a workbook, enabling VBProject access. Triggers on: export VBA, import VBA, vbaExcel, extraer macros Excel, importar VBA, refactorizar VBA, módulos VBA, xlsm macros.
presentation-bundle-manager
by lunasoft2001Packages all presentation deliverables into a structured project folder, generates an index.xlsx inventory file, and writes a manifest.json with metadata. Use when the user wants to bundle presentation files, create a delivery package, produce a file index, generate a project manifest, or archive a completed presentation project. Triggers on: "bundle the presentation", "package the deliverables", "create the manifest", "generate the index", "finalize the presentation package", "empaqueta la presentación", "crea el índice de archivos", "genera el manifest", "arma el paquete final".
bowling-proshop
by lunasoft2001Virtual ball driller and lane coach for bowling pro shops. Uses Dual Angle layout system (Mo Pinel style) to recommend balls, layouts, surface prep, and adjustments. Triggers when users ask about: ball selection, drilling layouts, Dual Angle, pin-to-PAP, VAL angle, rev rate, axis rotation, axis tilt, PAP, ball surface, lane patterns, oil patterns, bowling equipment, spare ball, proshop fitting, layout recommendation, hook potential, ball motion, or any bowling-specific technical question. Also triggers on: "qué bola uso", "layout", "patrón de aceite", "taladrado", "perforación".
presentation-factory-orchestrator
by lunasoft2001End-to-end orchestrator for creating professional presentations. Routes the full pipeline across four stages — storyboard → pptx-builder → speaker-notes → bundle-manager — and validates minimum inputs before starting. Use when the user wants to create a complete presentation package, build a deck from scratch, or produce a full presentation bundle with slides and speaker guide. Triggers on: "create a presentation", "make a deck", "build slides", "full presentation package", "crea una presentación", "prepara un deck", "necesito diapositivas", "armá una presentación completa".
responsible-ai-skill-evaluator
by lunasoft2001Evaluates whether a skill (SKILL.md) complies with Microsoft's 6 Responsible AI principles (Fairness, Reliability & Safety, Privacy & Security, Inclusiveness, Transparency, Accountability) and with AgentSkills.io format and quality standards. Use when asked to audit, review, verify, certify, or check a skill for responsible AI compliance, or to assess if a skill is ready for public publishing. Triggers on: "evaluate this skill", "audit skill for responsible AI", "check skill compliance", "review SKILL.md", "is this skill RAI compliant", "skill certification", "verify skill quality", "skill ready to publish".
videotoobsidian
by lunasoft2001Proceso completo de captura de vídeo YouTube a nota técnica Obsidian: obtiene metadatos, descarga la transcripción (via TranscribeYoutube), analiza el contenido y genera una nota técnica completa con vídeo embebido, resumen, pasos o puntos clave, y wikilink a la transcripción. Usa cuando el usuario pida: capturar vídeo, crear nota técnica de YouTube, VideoToObsidian, documento técnico de vídeo, procesar vídeo a Obsidian.
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.