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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cold-call-scripts
by SalesablyCreates personalized cold call scripts using a proven 5-step framework. Use this skill when preparing for prospecting calls, coaching reps on call structure, or creating call templates for campaigns.
orchestrator
by SalesablyDiagnoses marketing needs and sequences appropriate skills for comprehensive campaigns. This skill should be used when unsure which marketing skill to use, planning multi-step marketing campaigns, creating integrated marketing strategies, or when a project spans multiple marketing disciplines.
email-sequences
by SalesablyCreates automated email sequences for every stage of the customer journey including welcome, nurture, conversion, and launch flows. This skill should be used when building automated email flows, launching products, improving email-driven conversions, or onboarding new customers.
lead-magnet
by SalesablyCreates high-converting lead magnets with compelling hooks, strategic format selection, and validation frameworks. This skill should be used when building email lists, launching new products, creating content upgrades, or when current opt-in rates are below 15-20%.
account-qualification
by SalesablyQualifies and tiers accounts based on signals, fit, and potential. Use this skill when building target lists, prioritizing accounts, identifying high-potential prospects, or defining ideal customer profile criteria.
call-analysis
by SalesablyAnalyzes sales call transcripts using the POWERFUL framework to extract insights and action items. Use this skill when reviewing call recordings, coaching reps, qualifying opportunities, or extracting deal intelligence from conversations.
powerful-framework
by SalesablyApplies the POWERFUL deal qualification framework to analyze sales opportunities. Use this skill when qualifying deals, assessing opportunity strength, identifying gaps in deal intelligence, or coaching sales teams on deal execution.
sales-orchestrator
by SalesablyDiagnoses sales needs and sequences appropriate skills for comprehensive deal execution. Use this skill when unsure which sales skill to use, planning multi-step deal strategies, coaching reps on process, or coordinating complex sales motions.
prospect-research
by SalesablyCreates comprehensive prospect profiles and knowledge capsules for sales preparation. Use this skill when researching new prospects, preparing for calls, onboarding to new accounts, or updating prospect intelligence.
follow-up-emails
by SalesablyCreates professional follow-up emails after sales calls that capture key points and drive next steps. Use this skill when sending post-call summaries, confirming action items, or maintaining deal momentum between conversations.
multithread-outreach
by SalesablyCreates role-specific messages for multiple stakeholders in a deal. Use this skill when engaging additional contacts, following up with people who weren't on calls, or executing account-based selling strategies.
content-atomizer
by SalesablyRepurposes single content pieces into multiple formats for maximum distribution while maintaining brand voice. This skill should be used when maximizing ROI from pillar content, filling content calendars efficiently, reaching audiences across multiple platforms, or when creating original content for every channel feels unsustainable.
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.