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...
linguistics-analysis
by beita6969Analyze language structures, typological features, and semantic change across languages
spider-application
by yogsoth-aiSOP: 应用 SPIDER 框架结构化定性研究问题
archaeology
by notactuallytreyanastasioTransform narratives into a queryable decision graph
literature-review
by lingzhi227Conduct comprehensive literature reviews using multi-perspective dialogue simulation. Generate diverse expert personas, conduct grounded Q&A conversations, and synthesize findings into structured knowledge. Use when starting a new research project or writing a survey section.
anthropologist-analyst
by rysweetAnalyzes events through anthropological lens using cultural analysis, ethnographic methods, kinship and social organization, symbolic systems, ritual and practice, and comparative ethnology. Provides insights on cultural meanings, social practices, symbolic structures, cultural change, and cross-cultural patterns. Use when: Cultural conflicts, identity issues, ritual significance, symbolic meanings, cultural change, cross-cultural comparison. Evaluates: Cultural systems, symbolic meanings, social practices, kinship structures, cultural adaptation, power-culture nexus.
indigenous-leader-analyst
by rysweetAnalyzes events through indigenous knowledge systems using relational thinking, seven generations principle, reciprocity, holistic integration, and traditional ecological knowledge frameworks. Provides insights on interconnectedness, long-term sustainability, collective wisdom, and decolonial perspectives. Use when: Environmental decisions, resource stewardship, community governance, decolonization, intergenerational planning. Evaluates: Relationships, sustainability, collective impact, indigenous rights, traditional knowledge integration.
single-document-review
by LazyAGIUse this skill when the user requests to review, analyze, critique, or summarize a SINGLE academic paper, general document, internal report, proposal, or web article. Supports comprehensive structured reviews covering methodology/logic assessment, strengths, weaknesses, and constructive feedback. Retrieves content using native tools (`url_fetch`, `kb_search`, `arxiv_search`) and outputs the analysis directly in the chat.
archaeology-discussion
by diegosouzapw고고학 발굴조사보고서 고찰 자동 작성 파이프라인. "고찰 작성해줘" 한 번의 명령으로 완료된 보고서+논문+주변유적 보고서를 분석하여 문화재청 표준양식 고찰을 생성. 폴더1(주보고서), 폴더2(논문), 폴더3(비교유적)을 자동 분석. Use for automated archaeological excavation report discussion writing pipeline: analyzes main report + papers + comparison sites to generate discussion following Korean Cultural Heritage Administration standards. One command processes all folders.
archaeology-orchestrator
by diegosouzapw고고학 발굴조사 고찰 작성 자동화 파이프라인 마스터 오케스트레이터
antiquities-extractor
by diegosouzapwExtract and structure data from documents about the illegal antiquities trade, including dealers, collectors, artifacts, locations, and relationships. Use when processing news reports, academic articles, legal documents, encyclopedia entries, or research materials pertaining to looted artifacts, antiquities trafficking, provenance research, or cultural heritage crimes. Returns structured JSON with entities (persons, organizations, artifacts, locations) and their relationships.
radiocarbon-dating
by xjtulycRadiocarbon (14C) dating calibration and Bayesian age modeling using IntCal20/SHCal20/Marine20 curves, sequence modeling with stratigraphic constraints, and uncertainty reporting.
consult-natural-history
by pjt222Reference Hildegard von Bingen's Physica natural history knowledge. Covers classification of plants, stones, animals, fish, birds, elements, and trees with their medicinal, symbolic, and practical properties. Enables cross- referencing between categories and application guidance. Use when exploring a specific plant, stone, or animal from Hildegard's perspective, researching medieval natural history and cosmology, cross-referencing properties across categories, or integrating Physica knowledge into health, spiritual, or creative practice.
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.