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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clerk-cost-tuning
by jeremylongshoreOptimize Clerk costs and understand pricing. Use when planning budget, reducing costs, or understanding Clerk pricing model. Trigger with phrases like "clerk cost", "clerk pricing", "reduce clerk cost", "clerk billing", "clerk budget".
cost-tracker
by rohitg00Track session costs, set budget alerts, and optimize token spend. Use to check costs mid-session or set spending limits.
budget-standard-checker
by revfactoryMethodology for verifying government R&D project budget cost category standards and appropriateness. Use this skill for 'budget standard verification', 'cost category allocation', 'government project budget regulations', 'personnel cost standards', 'equipment allocation', 'indirect cost calculation', and other government project budget verification tasks. Note: actual accounting processing, tax calculation, and evidence document issuance are outside the scope of this skill.
budget-standard-checker
by revfactory정부 R&D 사업 예산 편성의 비목별 기준과 적정성을 검증하는 방법론. '예산 기준 확인', '비목별 편성', '정부과제 예산 규정', '인건비 기준', '연구장비 편성', '간접비 계산' 등 정부사업 예산 검증 시 사용한다. 단, 실제 회계 처리, 세금 계산, 증빙 서류 발급은 이 스킬의 범위가 아니다.
budget-rule-engine
by revfactory정부 보조금/지원사업의 예산 편성 규정과 비목별 산정 기준을 체계적으로 제공하는 전문 스킬. budget-designer 에이전트가 예산을 편성할 때 비목별 상한선, 산출 근거 작성법, 정산 규정을 적용하는 데 활용한다. '예산 편성 규정', '비목별 기준', '예산 상한', '정산 가이드', '대응자금' 등의 맥락에서 자동 적용한다. 단, 실제 회계 처리나 세금 신고는 이 스킬의 범위가 아니다.
budget-variance-analysis
by mohitagw15856Produce a structured budget variance analysis from actual vs budget figures. Use when asked to analyse budget variances, explain underspend or overspend, write a variance commentary, or investigate why actuals differ from plan. Produces a categorised variance table with root cause analysis and management commentary.
antraege-zahlen-schwellen-und-berechnung
by KlotzketteAntraege: Zahlen, Schwellenwerte und Berechnung im Plugin dfg foerderantrag; schärft Rollen, Belege, Fachnormen, Risiken, Gegenargumente und nächsten verwertbaren Schritt statt austauschbarer Standardprüfung im DFG-Förderantrag: prüft konkret die einschlägigen Tatbestandsmerkmale, Fristen, Belege und Rechtsprechung. Liefert priorisierten Output mit Norm-Pinpoints, Risikoampel und nächstem Arbeitsschritt.
antraege-zahlen-schwellenwerte-berechnung
by KlotzketteAntraege: Zahlen, Schwellenwerte und Berechnung im DFG-Förderantragstellung: 1. Welche Rolle hat die fragende Person und wer ist Gegenüber? 2. Welches konkrete Ziel soll erreicht oder verhindert werden? 3. Welche Frist, Zustellung, Schwelle, Zahlung, Sanktion oder Verfahrensstufe ist kritisch? 4. Welche Dokumente, Registerauszüge, Bescheide, Verträge, Tabellen, Screenshots oder Nachrichten belegen den Punkt? 5.
landeshaushalt-nordrhein-westfalen-les
by KlotzketteHaushaltsrecht BHO Bund und Länder: Landeshaushalt Nordrhein-Westfalen lesen. Landeshaushalt Nordrhein-Westfalen lesen im Fachgebiet Haushaltsrecht BHO Bund und Länder als geführten Arbeitsgang mit Fragen, Dokumentenlogik und Ausgabeformat bearbeiten im Haushaltsrecht (BHO/LHO): prüft konkret die einschlägigen Tatbestandsmerkmale, Fristen, Belege und Rechtsprechung. Liefert priorisierten Output mit Norm-Pinpoints, Risikoampel und nächstem Arbeitsschritt.
landeshaushalt-rheinland-pfalz-lesen
by KlotzketteHaushaltsrecht BHO Bund und Länder: Landeshaushalt Rheinland-Pfalz lesen. Landeshaushalt Rheinland-Pfalz lesen im Fachgebiet Haushaltsrecht BHO Bund und Länder als geführten Arbeitsgang mit Fragen, Dokumentenlogik und Ausgabeformat bearbeiten im Haushaltsrecht (BHO/LHO): prüft konkret die einschlägigen Tatbestandsmerkmale, Fristen, Belege und Rechtsprechung. Liefert priorisierten Output mit Norm-Pinpoints, Risikoampel und nächstem Arbeitsschritt.
landeshaushalt-saarland-lesen
by KlotzketteHaushaltsrecht BHO Bund und Länder: Landeshaushalt Saarland lesen. Landeshaushalt Saarland lesen im Fachgebiet Haushaltsrecht BHO Bund und Länder als geführten Arbeitsgang mit Fragen, Dokumentenlogik und Ausgabeformat bearbeiten im Haushaltsrecht (BHO/LHO): prüft konkret die einschlägigen Tatbestandsmerkmale, Fristen, Belege und Rechtsprechung. Liefert priorisierten Output mit Norm-Pinpoints, Risikoampel und nächstem Arbeitsschritt.
landeshaushalt-sachsen-anhalt-lesen
by KlotzketteHaushaltsrecht BHO Bund und Länder: Landeshaushalt Sachsen-Anhalt lesen. Landeshaushalt Sachsen-Anhalt lesen im Fachgebiet Haushaltsrecht BHO Bund und Länder als geführten Arbeitsgang mit Fragen, Dokumentenlogik und Ausgabeformat bearbeiten im Haushaltsrecht (BHO/LHO): prüft konkret die einschlägigen Tatbestandsmerkmale, Fristen, Belege und Rechtsprechung. Liefert priorisierten Output mit Norm-Pinpoints, Risikoampel und nächstem Arbeitsschritt.
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.