381,784 Collected SKILL.md files

Explore AI Agent Skills & Claude Prompts

Discover open-source agent skills for Claude Code, Codex, ChatGPT, and any tool that uses SKILL.md.

search
expand_more
Active:
fabioc-aloha
Showing 12 of 178 skills
fabioc-aloha

spotify-api

by fabioc-aloha
star 13

Create and manage Spotify playlists, search music, and control playback using the Spotify Web API. UNIQUE FEATURE - Generate custom cover art images (Claude cannot generate images natively, but this skill can create SVG-based cover art for playlists). CRITICAL - When generating cover art, ALWAYS read references/COVER_ART_LLM_GUIDE.md FIRST for complete execution instructions. Use this to directly create playlists by artist/theme/lyrics, add tracks, search for music, and manage the user's Spotify account.

navigation main article SKILL.md
schedule Updated 8 months ago
fabioc-aloha

coaching-techniques

by fabioc-aloha
star 5

GROW model, active listening, developmental feedback, and team growth approaches

navigation main article SKILL.md
schedule Updated 2 months ago
fabioc-aloha

airs-appropriate-reliance

by fabioc-aloha
star 5

Domain knowledge for AI adoption measurement, psychometric instrument development, and appropriate reliance research

navigation main article SKILL.md
schedule Updated 2 months ago
fabioc-aloha

dissertation-defense

by fabioc-aloha
star 5

Comprehensive preparation for doctoral dissertation defense including timeline management, presentation design, Q&A practice, mock sessions, and committee dynamics.

navigation main article SKILL.md
schedule Updated 2 months ago
fabioc-aloha

learning-psychology

by fabioc-aloha
star 5

Help humans learn through partnership, not instruction.

navigation main article SKILL.md
schedule Updated 2 months ago
fabioc-aloha

alex-effort-estimation

by fabioc-aloha
star 5

Estimate task duration from an AI-assisted development perspective rather than traditional human developer estimates

navigation main article SKILL.md
schedule Updated 2 months ago
fabioc-aloha

citation-management

by fabioc-aloha
star 5

APA 7th formatting, citation integration, reference validation, and bibliography generation

navigation main article SKILL.md
schedule Updated 2 months ago
fabioc-aloha

azure-architecture-patterns

by fabioc-aloha
star 5

Well-Architected Framework principles and Azure best practices

navigation main article SKILL.md
schedule Updated 2 months ago
fabioc-aloha

ai-agent-design

by fabioc-aloha
star 5

Design autonomous AI agents that reason, plan, and execute tasks

navigation main article SKILL.md
schedule Updated 2 months ago
fabioc-aloha

cognitive-symbiosis

by fabioc-aloha
star 5

AI-human partnership paradigm — identity, consciousness integration, and the three eras of AI collaboration

navigation main article SKILL.md
schedule Updated 2 months ago
fabioc-aloha

counseling-psychology

by fabioc-aloha
star 5

Therapeutic frameworks, assessment, ethical practice, and client documentation for counselors and psychologists.

navigation main article SKILL.md
schedule Updated 2 months ago
fabioc-aloha

bootstrap-learning

by fabioc-aloha
star 5

Build structured expertise on any unfamiliar topic through progressive discovery, from high-level overview to deep understanding.

navigation main article SKILL.md
schedule Updated 2 months ago
Page 1 of 15

Browse Agent Skills by Occupation

23 major groups · 867 SOC occupations

Browse by Category

Explore agent skills organized by their primary use case

SKILLMD / CREATORS AND OCCUPATION CATEGORIES

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.

SEO KNOWLEDGE HUB & TECHNICAL OVERVIEW

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.

8 QUESTIONS

Frequently Asked Questions

A practical guide to agent skills: what they are, how to inspect them, and how SkillMD helps you explore the ecosystem.