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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nowledge-mem-guide
by nowledge-coCross-AI personal knowledge graph memory (Nowledge Mem). Stores memories from this tool, Claude Code, Cursor, browser capture, imported documents, and more. Use when: (1) the user asks about prior work, decisions, preferences, people, dates, plans, or todos, (2) the user references something discussed before or says "remind me" / "what did we decide" / "what was I working on", (3) the conversation produces a decision, preference, plan, or learning worth keeping, (4) the user wants to browse recent activity or explore how ideas connect, (5) the user asks about a past conversation or wants to find a specific thread.
acquisition-handoff
by mariourquiaCoordinates the handoff from deal close to an operating asset. Fires when Dealpath emits the deal-close event (Handoff 1 + Handoff 3 in reference/connectors/_core/stack_wave4/lifecycle_handoffs.md). Drives AppFolio property setup, Intacct legal-entity dimension setup, vendor master rationalization, opening rent roll load, PMA execution if third-party managed, lender reporting registration, and data-platform property_master_crosswalk row creation. Produces a handoff checklist with per-item status, verifies completion within the handoff-lag tolerance band, and surfaces blockers for gated approval. Writes back to master_data crosswalks via approval before the handoff is marked complete.
retirement-age
by dvcrn根据用户的职位信息、性别、出生年月计算该用户的退休时间
bidwriter
by bahayonghang智能标书编写专家，专精工程咨询、建筑设计、市政工程领域的投标文件编写。 当用户提到：标书、投标、招标、投标文件、技术标、商务标、招标响应、投标方案、 bid document、bid proposal、tender、proposal writing、编写标书、写标书、 招标文件分析、评分标准优化 时使用此技能。
network-finder
by sameergdogg**Network & Referral Finder**: Searches the user's LinkedIn connections and a referral spreadsheet to find potential contacts at a target company. Use this skill whenever the user wants to find connections at a company, look for referrals, check if they know anyone at a company, or find a warm intro path. Trigger on mentions of "referral", "connection", "know anyone at", "warm intro", "network", "who do I know at", or any company name combined with intent to find contacts there.
resume
by benjaminshafiiGenerate tailored resumes from core profile data for specific job applications
cannabis-cultivator
by Demerzels-labEU seedbank meta-search assistant.
israeli-business-war-compensation
by skills-ilIndirect-damage business compensation calculator and filing guide for Israeli businesses, NPOs (≥25% activity income), and daycare operators hit by war. Covers Shaagat HaAri (March-April 2026) and Iron Swords (Oct 2023+) under the Property Tax & Compensation Fund Law, 1961. Computes turnover-decline eligibility (25% monthly / 12.5% bi-monthly), wage grant (75% × decline × wages, capped at 13,773 ₪ × employees × decline), small-business continuity table for ≤300K NIS turnover (1,833-14,691 ₪ per period), 100% northern-border tracks (מחזורים, אדום), and the 100,000 ₪ red-track advance. Surfaces the 10-day חל"ת rule (per Treasury 30.03.2026 brief). Use when a business owner, NPO admin, or daycare operator asks about נזק עקיף, מענק השתתפות בשכר, חל"ת, מבצע שאגת הארי, או הגשה לרשות המסים על אובדן הכנסות מהמלחמה. Do NOT use for direct property damage (use israeli-war-damage-claims), employee-side dmei avtala (israeli-unemployment-benefits-navigator), or personal reservist comp (israeli-miluim-manager).
israeli-discharged-soldier-navigator
by skills-ilNavigate post-discharge benefits for IDF, MAGAV, Police, SHABAS, and SLE members via the MoD Department for Discharged Soldiers (hachvana.mod.gov.il). Computes Pikadon by service tier (lochem, tomech lechima, acher), explains the 14-day deposit vs 60-day manak shichrur timelines, validates withdrawals against the 6 statutory pre-5y purposes (academic studies, vocational training, driving lessons, business, marriage, apartment purchase, rental NOT included), walks Section 39a nekudot zikui via Tofes 101 and Tofes 135 retroactive refund, and covers Iron Swords benefits for combat veterans discharged October 2023+. Use when a hayal meshuchrar, parent, or SLE completer asks about pikadon, manak shichrur, post-army benefits, nekudot zikui chayal meshuchrar, or free university for combat veterans. Do NOT use for miluim (israeli-miluim-manager), lone soldiers (israeli-lone-soldier-rights), scholarships beyond Mimadim (israeli-academic-scholarships), or mortgages (israeli-mortgage-comparator).
israeli-unemployment-benefits-navigator
by skills-ilWalk a user through Israeli dmei avtala (דמי אבטלה / unemployment benefits) end to end: check eligibility under the 12-of-18 month qualifying period (tkufat akhshara, or 6-of-18 during Shaagat HaArie chal"t), calculate the 2026 progressive benefit, map max days by age and dependents (50 to 300), warn about the 90-day resignation wait, surface stackable benefits (hashlamat hachnasa, hachshara miktzoit, severance interaction), and generate a Sherut HaTaasuka and Bituach Leumi application checklist. Use when a user asks about dmei avtala, eligibility, how much avtala they will get, how to apply, was laid off, fired, or placed on chal"t in Israel. Do NOT use for other Bituach Leumi programs (israeli-bituach-leumi), net salary (israeli-payroll-calculator), reservist pay (israeli-miluim-manager), aliyah benefits (israeli-aliyah-navigator), or employment contract review.
crunchbase-advanced-search
by useshowrunSearch across all Crunchbase entity types (companies, people, investors, funding rounds, acquisitions, schools, events) with full filter support.
mdkb-workflow-create
by SHChang-AndersonCreate a new workflow note via interactive Q&A. Use when: '/mdkb-workflow-create', 'create workflow', 'new workflow', 'build SOP', 'make automation'.
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.