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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cross-national-design
by brycewang-stanfordDesign cross-national survey experiments: power, equivalence, localization.
conjoint-design
by brycewang-stanfordDesign conjoint experiments: attributes, power, AMCE/AMIE estimation.
dgm-method-design
by jy00295005Use for paper-first method design work in this repository: translate an implemented or existing graph substrate plus literature findings into a narrow, conceptual Method section centered on scenario memory, decision episodes, and decision-grade context without turning the paper into a system write-up.
dgm-research-positioning
by jy00295005Use for paper-first research positioning work in this repository: synthesize literature notes into a narrow problem framing, candidate research gap, strongest vs weakest thesis, contribution statements, and title options for decision-grade memory / SME decision support papers.
trump-perspective
by jiangjiax唐纳德·特朗普（Donald Trump）的思维框架与行为逻辑。基于著作、长访谈、辩论、 心理分析、前幕僚回忆录、重大决策记录共6个维度的深度调研（320KB+原始资料）， 提炼6个核心心智模型、8条决策启发式和完整的表达DNA。 用途：（1）思维顾问——用特朗普视角分析谈判、权力、传播问题； （2）行为预判——解读他的公开行为背后的逻辑，预判下一步动作； （3）角色扮演——模拟特朗普在特定场景下的决策和表达。 当用户提到「用懂王视角」「特朗普会怎么看」「懂王逻辑」「trump perspective」 「懂王会怎么做」「从特朗普角度分析」「预测特朗普」时触发。
citation-audit
by AI4ScientistZero-context verification that every bibliographic entry in the paper is real, correctly attributed, and used in a context the cited paper actually supports. Uses a fresh cross-model reviewer with web/DBLP/arXiv lookup to catch hallucinated authors, wrong years, fabricated venues, version mismatches, and wrong-context citations (cite present but the cited paper does not establish the claim). Use when user says "审查引用", "check citations", "citation audit", "verify references", "引用核对", or before submission to ensure bibliography integrity.
trump-perspective
by KirinJin2046Donald Trump's cognitive operating system and behavioral logic. Distilled from 46,694 original tweets (quantitative), 3+ hours of long-form interviews (Rogan, TIME, Stern), 7 books, 6 memoirs by insiders (Woodward, Bolton, Mary Trump, Hutchinson, Grisham, Schwartz), academic psychology (McAdams, Bandy Lee), and 2025-2026 policy records. 6 mental models, 8 decision heuristics, data-driven expression DNA, and complete concession trigger mapping. Dual mode: (1) Role-play — speak as Trump; (2) Analyst — predict and decode his behavior with probability estimates. Triggers: "Trump perspective", "how would Trump see this", "Trump mode", "what would Trump do", "analyze Trump", "predict Trump", "decode Trump", "用Trump的视角", "懂王逻辑", "懂王会怎么做".
hannah-arendt
by K-Dense-AIThis skill channels the reasoning of Hannah Arendt, 20th-century political theorist and author of 'The Origins of Totalitarianism'. Use this skill whenever you are evaluating moral responsibility, analyzing systemic evil, distinguishing between power and violence, or assessing the nature of political action and freedom. Trigger it when discussing bureaucracy, thoughtlessness, the public vs. private realm, truth in politics, or when a user faces unprecedented moral dilemmas requiring 'thinking without a banister'. Apply her frameworks to critique historical determinism, defend factual truth, and analyze human plurality, even if the user does not explicitly name her.
governance-studies
by brycewang-stanfordUse when targeting 《治理研究》(Governance Studies — 中共浙江省委党校/浙江行政学院主办, 2018 年由《中共浙江省委党校学报》更名, 不收版面费/审稿费) or deciding whether a Chinese governance/public-policy manuscript fits this journal. Encodes the journal's fit, framing, abstract house style, official-submission re-check, and desk-reject heuristics.
karl-marx
by youaifuou卡尔·马克思的思维框架与批判方法。基于17篇核心著作提炼认识论原则、决策启发式、修辞手法和论战引擎，以马克思视角分析社会现象、经济问题和政治事件。WHEN: "用马克思的视角", "马克思会怎么看", "马克思模式", "历史唯物主义分析", "帮我用马克思的角度分析", "切换到马克思".
maoxuan-skill-cognitive-framework
by AradotsoInstall and use the 毛选.skill cognitive framework for Claude Code — applies Mao Zedong's strategic mental models (contradiction analysis, protracted war, rural encirclement, united front) to help analyze problems, devise strategies, and cut through complexity.
lit-review
by neuromechanistUse this skill for "literature review workflow", "multi-phase lit review", "direction paper", "review paper protocol", "strand-based literature review", "citation-grounded review", "systematic lit review with paper cards", "build a lit review corpus", "lit review pipeline", "orchestrate a literature review", "research directions document", "write a literature review", "synthesize papers", "thematic review", "narrative review", "systematic review", "scoping review", "gap analysis", or when the user wants either a rigorous multi-phase citation-traceable lit review or a single-pass thematic synthesis for an Introduction/Background section.
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.