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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financial-overview
by norman-financeGet a complete financial overview of the business including balance, recent transactions, outstanding invoices, and upcoming tax obligations. Use when the user asks about their financial status, dashboard, summary, or "how is my business doing?"
categorize-transactions
by norman-financeReview and categorize uncategorized bank transactions, match them with invoices, and verify bookkeeping entries. Use when the user wants to review transactions, categorize expenses, do bookkeeping, or reconcile their bank account.
monthly-reconciliation
by norman-financePerform a complete monthly financial reconciliation - review all transactions, match invoices, check outstanding payments, and prepare for tax filing. Use when the user wants to close the month, do monthly bookkeeping, or perform a Monatsabschluss.
ta-tax-compliance
by norman-financeTax compliance check for a client company. Checks all tax periods, identifies unfiled or overdue reports, verifies tax registration, and generates a compliance summary. Use when a tax advisor asks about tax deadlines, compliance status, or filing obligations.
tax-report
by norman-financeReview and manage German tax reports including VAT (Umsatzsteuer), income tax prepayments, and Finanzamt submissions. Use when the user asks about taxes, Steuern, VAT, USt, Finanzamt, or tax filing.
ta-company-review
by norman-financeFull company review for tax advisors. Generates a structured health report covering financials, document completeness, tax compliance, and action items. Use when a tax advisor asks for an overview, health check, or status of a client company.
suggest-category
by norman-financeFind the right SKR account code for a bookkeeping category (SME only). Search the full SKR03/SKR04 chart of accounts by code or use AI to match by name or description. Use when an SME user needs help finding a category code, wants to add a new custom category, or asks "what account number is X?"
ta-missing-receipts
by norman-financeFind and collect missing receipts for a client company. Identify high-priority items, suggest a ping strategy, and bulk-notify the client. Use when a tax advisor asks about missing documents, Belege, or requests receipts from a client.
find-receipts
by norman-financeFind and attach missing receipts for business transactions. Search Gmail, email, or other sources for invoices and receipts, then upload them to Norman. Use when the user asks about missing receipts, Belege, attaching documents, or finding invoices from emails.
expense-report
by norman-financeGenerate a detailed expense breakdown by category for a given period. Use when the user asks for an expense report, spending summary, Ausgabenübersicht, cost analysis, or wants to understand where their money is going.
overdue-reminders
by norman-financeFind overdue invoices and send payment reminders (Zahlungserinnerungen / Mahnungen) to clients. Use when the user asks about unpaid invoices, overdue payments, payment reminders, Mahnung, or chasing payments.
manage-clients
by norman-financeManage business clients - list, search, create, or update client information. Use when the user mentions clients, contacts, customers, Kunden, or needs to manage their client database.
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.