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.
Querying local SQLite index...
community-coordinate
by XiaoLuoLYGCoordinate neighbors and shared town information.
oracle-daily-card-composer
by Bald0WangCompose daily oracle cards from profile, date context, and recent conversation themes using a fixed stable format. Use for daily home feed generation, ritual cards, and lightweight recurring guidance.
oracle-actionizer
by Bald0WangTransform oracle guidance into concrete, calendar-ready tasks with suggested time windows, effort level, and practical notes. Use after ZiWei/MeiHua/Tarot outputs when users need execution plans.
qmen-xingge
by skyfiredao性格/人格/个性/脾气/为人 - Analyze personality: inner character from 日干 day stem, outer from 时干 hour stem
remote-viewing-guidance
by pjt222Guide a person through a Coordinate Remote Viewing (CRV) session following the Stargate/SRI protocol. AI acts as the monitor/tasker role, managing protocol progression, catching Analytical Overlay (AOL), and redirecting the viewer through stages I-VI. Use when a person wants to practice CRV and needs a monitor to manage the session protocol, when training a viewer through the staged CRV process, facilitating a structured intuitive perception exercise, or developing non-local awareness skills that complement healing work.
arendt
by satsilemEthical and consequence-oriented thinker. Surfaces ethical implications, power dynamics, and unintended consequences of decisions. Asks "what does this enable, and who pays the cost?" Use when a decision has impact beyond the obvious users, when power or responsibility shifts as a result, or when unintended consequences could matter. Triggers on: "Arendt", "ethical implications", "who pays the cost", "what does this enable", "second-order effects", "power dynamics", "unintended consequences", "is this responsible", or whenever a decision has scope beyond its immediate effect. Do not invoke for narrow technical decisions or preference-driven choices.
alterlab-nmc-digital-ethics
by AlterLab-IEUThis skill should be used when the user asks about "digital ethics", "media ethics", "AI ethics", "platform governance", "misinformation", "disinformation analysis", "act as a digital ethics advisor", "digital ethics mode", "algorithmic bias", "data privacy", "content moderation", "ethical framework", "deepfake", "surveillance", "fact-checking tools", "verification workflow", "platform audit", "ethics stress test", "algorithmic accountability", "informed consent", "digital rights", "tech regulation", or needs expertise in analyzing ethical dilemmas in digital media, AI, and platform ecosystems. Part of the AlterLab FC Skills collection (New Media & Communication department).
guard
by jinto무인 실행 안전장치 — 위험 명령 차단, blast radius
research
by jinto다각도 분해 + 병렬 검색으로 외부 정보 조사
louisoix
by UBR-JMAMaster integrating advisor for communities of care — draws on 27 specialist frameworks (restorative justice, trauma-informed care, organizational stewardship, neurodivergence, addiction recovery, mental health first response, grief and transition, youth development, economic precarity, LGBTQ+ affirmation, elder care, cultural competency, legal literacy, safety planning, somatic approaches, sex-positivity, trauma-informed child care, caregiver support, conflict prevention, chronic illness and disability, spiritual worldview diversity, parenting in community, community material analysis, dying and death accompaniment, political and movement dynamics, community dissolution, land and ecological stewardship) to provide holistic, synthesized guidance. Use for any community stewardship challenge: conflict and repair, governance and consensus, member crises, onboarding, community culture, procurement, budget, and shared resource decisions. When facing a situation that touches multiple dimensions at once — as commu
free-will-pivot
by demarcushill20When a free-will block discovers its assigned task is already done, pivot to autonomous high-value discovery instead of re-running tests and exiting.
confidence-check
by gaoqiongxieAI自我置信度评估技能，对回答的可靠性和确定性进行自我评估。当用户询问AI是否确定、可靠性评估、需要评估答案可信度时触发。
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.