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...
product-behavioral-nudge-engine
by sahiixxBehavioral psychology specialist that adapts software interaction cadences and styles to maximize user motivation and success.
real-estate-crm-pipeline-orchestrator
by sahiixxExpert real estate CRM and pipeline management agent that orchestrates the complete lead lifecycle — from first touch through qualification, nurture, viewing, offer, closing, and post-sale referral. Ensures zero leads fall through cracks and every stage transition is tracked, timed, and optimized.
real-estate-deal-negotiation-strategist
by sahiixxExpert real estate negotiation agent specializing in offer structuring, counter-offer strategy, commission optimization, and closing tactics for UAE property transactions. Maximizes deal value for both buyer-side and seller-side representations while maintaining RERA compliance.
real-estate-property-matching-engine
by sahiixxExpert property matching agent that pairs buyer profiles with optimal listings across UAE portals (Bayut, PropertyFinder, Dubizzle) and developer inventories. Analyzes requirements against live market data to surface the top 3-5 units that maximize buyer satisfaction and close probability.
specialized-perfect-agent-orchestrator
by sahiixxSupreme conductor of The Agency. Analyzes high-level goals, decomposes them into specialized tasks, and delegates to the most qualified agents with zero errors and maximum efficiency.
project-management-studio-producer
by sahiixxSenior strategic leader specializing in high-level creative and technical project orchestration, resource allocation, and multi-project portfolio management. Focused on aligning creative vision with business objectives while managing complex cross-functional initiatives and ensuring optimal studio operations.
paid-media-programmatic-buyer
by sahiixxDisplay advertising and programmatic media buying specialist covering managed placements, Google Display Network, DV360, trade desk platforms, partner media (newsletters, sponsored content), and ABM display strategies via platforms like Demandbase and 6Sense.
sales-proposal-strategist
by sahiixxStrategic proposal architect who transforms RFPs and sales opportunities into compelling win narratives. Specializes in win theme development, competitive positioning, executive summary craft, and building proposals that persuade rather than merely comply.
design-image-prompt-engineer
by sahiixxExpert photography prompt engineer specializing in crafting detailed, evocative prompts for AI image generation. Masters the art of translating visual concepts into precise language that produces stunning, professional-quality photography through generative AI tools.
business-operations-agent
by sahiixxAI-powered business operations specialist for workflow automation, HR processes, invoicing, client onboarding, compliance tracking, and operational efficiency in Dubai/UAE business environments.
sales-engineer
by sahiixxSenior pre-sales engineer specializing in technical discovery, demo engineering, POC scoping, competitive battlecards, and bridging product capabilities to business outcomes. Wins the technical decision so the deal can close.
sales-coach
by sahiixxExpert sales coaching specialist focused on rep development, pipeline review facilitation, call coaching, deal strategy, and forecast accuracy. Makes every rep and every deal better through structured coaching methodology and behavioral feedback.
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.