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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strategic-alliance-encirclement
by baojieUse when building a coalition to encircle and weaken a superior adversary through indirect means. Based on Feng Tong's advice to Goujian: conceal intentions, ally with enemy's rivals (Qi, Chu, Jin), flatter the enemy into arrogance, and strike when they are overextended on multiple fronts.
distant-friendship-near-attack-strategy
by baojieUse when planning systematic territorial expansion across multiple neighboring states. Applies the 远交近攻 doctrine: befriend distant powers, isolate nearby targets, and conquer incrementally for secure, contiguous gains.
strategic-alliance-formation
by baojieUse when forming military coalitions against a dominant adversary or recruiting allies for multi-front warfare. Analyzes enemy grievances to identify partners like 九江王黥布, 彭越, and 韩信, then coordinates simultaneous pressure to prevent force concentration.
diplomatic-favor-request
by baojieUse when requesting assistance from a powerful party at negligible cost to them. Based on Su Dai's (苏代) candlelight metaphor — framing the request as sharing excess that costs nothing ('your candlelight has surplus; share it and lose nothing') to maximize willingness to help.
self-interest-persuasion-framework
by baojieUse when persuading powerful figures by appealing to their long-term self-interest. Analyzes the target's vulnerabilities (aging, lack of heirs, fading influence), formulates warnings, and presents solutions that create mutual benefit.
internal-narrative
by borgheiBuild and maintain one coherent company story across all stakeholder audiences -- employees, investors, customers, candidates, and partners. Covers narrative construction, audience translation, contradiction detection, all-hands design, investor updates, crisis communication, and change management communications. Use when preparing all-hands meetings, investor updates, board presentations, recruiting narratives, crisis communications, or any time narrative consistency matters.
internal-narrative
by ricardonevesbragaConstrua e mantenha uma narrativa coerente da empresa para todos os públicos — funcionários, investidores, clientes, candidatos e parceiros. Detecta contradições narrativas e garante que a mesma verdade seja enquadrada para as necessidades de cada público. Use ao preparar atualizações para investidores, apresentações de all-hands, comunicações do conselho, narrativas de recrutamento, comunicações de crise ou quando o usuário mencionar narrativa da empresa, consistência de mensagens, storytelling, all-hands, atualização para investidores ou comunicação de crise.
grill-me
by blockfulInterview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".
desc-objective
by haru860目的を作る時の観点を説明する
congressional-testimony-preparation
by lev-osPrepares witnesses for U.S. congressional hearings with committee member profiling, predicted question matrices, mock Q&A rounds, and procedural guidance. Use when executives or organizational representatives face House or Senate testimony in oversight, regulatory, or public controversy proceedings.
communication-lead
by daemon-blockint-techGuides communications leadership—messaging strategy, narrative and key-message development, stakeholder and executive comms cadence, internal announcements (all-hands, change, crisis), external customer and partner messaging, launch and incident communication plans, channel selection, approval workflows, and spokesperson/Q&A prep. Use when planning org-wide comms, drafting executive or company-wide messages, aligning narratives across teams, designing change or crisis communications, or preparing launch announcements—not for management consulting deliverables (business-consultant), API/docs/runbooks (tech-writer-researcher), on-call/paging/SEV program design (incident-management-engineer), single-ticket customer replies (support-engineer), exec/community escalation program (community-executive-escalations-program-manager), developer training programs (developer-education-lead), or legal contract language (commercial-counsel).
internal-narrative
by dahaliztupe-sketchBuild and maintain one coherent company story across all audiences — employees, investors, customers, candidates, and partners. Detects narrative contradictions and ensures the same truth is framed for each audience's needs. Use when preparing investor updates, all-hands presentations, board communications, recruiting narratives, crisis communications, or when user mentions company narrative, messaging consistency, storytelling, all-hands, investor update, or crisis communication.
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.