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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add-deal
by cartaCreates one or more deal records in the Carta CRM via the Carta CRM MCP Server. Use this skill when the user says things like "add a deal", "create a deal", "log a deal", "add deal to CRM", "add deal to Carta CRM", or "/add-deal". Collects deal information conversationally, then creates it via the MCP server.
update-deal
by cartaUpdates an existing deal record in the Carta CRM. Use this skill when the user says things like "update a deal", "move deal to [stage]", "change deal stage", "edit deal", "update deal fields", "add a tag to deal", "assign deal lead", "update company info on deal", "link contacts to deal", or "/update-deal". Accepts a deal ID or company name (will search if no ID provided). Only the fields explicitly provided are changed — all other fields are left untouched.
carta-consolidating-pnl
by cartaFirm-wide consolidating P&L (Income Statement) across ALL entities of a firm for one month. Produces TWO Excel tabs: detailed P&L (Month + YTD Actual/Budget/Variance/%) and executive Summary P&L formula-linked to detail. Optional tag-view mode breaks Actuals down by ALL firm reporting-tag categories side by side with a three-row nested header (period > category > tag) and per-category subtotals; Budget/Variance omitted in tag-view (Carta budgets have no tag dimension). Sourced from Carta MCP. TRIGGER on "consolidating P&L for [firm] [month]", "P&L for all entities of [firm]", "firm-wide income statement", "P&L with executive summary", "P&L by department", "P&L by tag", "income statement by cost center", "P&L by project code". DO NOT TRIGGER for single-entity P&L, balance sheet (carta-consolidating-balance-sheet), new budgets (carta-create-budget), Carta budgets (carta-fetch-budget), actuals refresh (carta-budget-actuals), pacing (carta-budget-vs-actuals), or what-if (carta-budget-scenarios).
search-investors
by cartaSearches for and retrieves investor records from the Carta CRM. Use this skill when the user says things like "find an investor", "search investors", "look up an investor", "show me investor details for [name]", "get investor by ID", "list investors", "what investors do we have", or "/search-investors". Returns investor details including ID, name, and custom fields. The investor ID returned can be used with the update-investor skill.
update-investor
by cartaUpdates an existing investor record in the Carta CRM. Use this skill when the user says things like "update an investor", "edit investor", "update investor details", "change investor name", "update investor website", "update investor fields", "add a tag to investor", or "/update-investor". Accepts an investor ID or name (will search if no ID provided). Only the fields explicitly provided are changed — all other fields are left untouched.
add-investor
by cartaAdds one or more investor records to the Carta CRM via the Carta CRM MCP Server. Use this skill when the user says things like "add an investor", "/add-investor", "add investor to Carta CRM", "create investor record", "add this VC fund to the CRM", or "save investor data". Collects investor information conversationally, then creates it via the MCP server.
search-fundraisings
by cartaSearches for and retrieves fundraising records from the Carta CRM. Use this skill when the user says things like "find a fundraising", "search fundraisings", "look up a fundraising round", "show fundraising details for [name]", "get fundraising by ID", "list fundraisings", "what fundraisings do we have", or "/search-fundraisings". Returns fundraising details including ID, name, stage, and custom fields. The fundraising ID returned can be used with the update-fundraising skill.
update-fundraising
by cartaUpdates an existing fundraising record in the Carta CRM. Use this skill when the user says things like "update a fundraising", "edit fundraising", "update fundraising details", "change fundraising stage", "update fundraising fields", or "/update-fundraising". Accepts a fundraising ID or name (will search if no ID provided). Only the fields explicitly provided are changed — all other fields are left untouched.
add-contact
by cartaAdds one or more contact records to the Carta CRM via the Carta CRM MCP Server. Use this skill when the user says things like "add a contact", "create a contact record", "add contact to CRM", "save a contact", "upload contact to Carta CRM", or "/add-contact". Collects contact information conversationally, then creates it via the MCP server. Only name is required — all other fields are optional.
tutorial
by cartaInteractive ~5-minute walkthrough of the Carta CRM plugin. Covers plugin overview, setup verification, how to kick off each skill, and a demo walkthrough of 4 realistic CRM scenarios. Trigger phrases: "carta crm tutorial", "show me the crm tutorial", "how do I use carta crm", "walk me through carta crm", "getting started with crm", "demo carta crm", "crm tutorial"
carta-form-adv
by cartaFetches Form ADV Part 1A filing data and generates an interactive HTML filing guide + Excel filing reference. Covers Items 5.D/F/H, Schedule D §7.B.(1) per-fund detail, beneficial owner breakdown, asset class composition, and capital activity. Use when asked about Form ADV, regulatory AUM, Schedule D, Form PF Section 1, SEC filing data, or private fund disclosures. Do NOT use for general fund metrics, NAV lookups, or LP contribution history — use carta-explore-data instead.
search-notes
by cartaSearches for and retrieves note records from the Carta CRM. Use this skill when the user says things like "find a note", "search notes", "look up a note", "show me notes about [topic]", "list notes", "find notes mentioning [keyword]", or "/search-notes". Returns note details including ID, title, and text content.
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.