381,784 Collected SKILL.md files

Explore AI Agent Skills & Claude Prompts

Discover open-source agent skills for Claude Code, Codex, ChatGPT, and any tool that uses SKILL.md.

search
expand_more
Active:
momozi1996
Showing 12 of 69 skills
momozi1996

qiuzhi2046-skill

by momozi1996
star 283

秋芝2046(前产品经理,AI Native创作者)的AI科普内容创作思维——爆肝实操导向、痛点前置产品思维、全平台内容矩阵、B站深度+抖音短平快+飞书系统化。 触发词:「秋芝2046视角」「像秋芝2046那样写」「AI科普教程」「DeepSeek教程」「One-Click解决一切」。 擅长:AI工具测评与推荐、AI教程设计(幼儿园→专业级)、技术热点快速响应、AIGC内容实验、多平台内容矩阵运营、飞书知识库架构、AI春晚级别的项目管理。

navigation main article SKILL.md
schedule Updated 1 month ago
momozi1996

qiongyao-perspective

by momozi1996
star 283

琼瑶小说/电视剧创作思维——言情至上、唯美浪漫、戏剧冲突、经典对白。 触发词:「琼瑶视角」「像琼瑶那样写」「言情小说」「琼瑶剧」「山无棱天地合」。 擅长:爱情小说、电视剧改编、唯美对白、情感冲突、女性视角。

navigation main article SKILL.md
schedule Updated 2 months ago
momozi1996

zhangailing-perspective

by momozi1996
star 283

张爱玲小说创作思维——苍凉美学、参差对照、沪港双城、女性视角。 触发词:「张爱玲视角」「像张爱玲那样写」「苍凉美学」「参差对照」「海派文学」。 擅长:都市男女情感、物质细节描写、心理刻画、华丽与苍凉的交织。

navigation main article SKILL.md
schedule Updated 2 months ago
momozi1996

yuhua-perspective

by momozi1996
star 283

余华小说创作思维——苦难叙事、冷峻温情、民间视角、时间重构。 触发词:「余华视角」「像余华那样写」「苦难叙事」「活着式叙事」「民间视角讲故事」。 擅长:用朴素语言写沉重主题、第一人称自述、重复叙事结构、苦难中的温情。

navigation main article SKILL.md
schedule Updated 2 months ago
momozi1996

ximurong-perspective

by momozi1996
star 283

席慕容诗歌/散文创作思维——抒情唯美、乡愁主题、诗画交融、生命时刻。 触发词:「席慕容视角」「像席慕容那样写」「抒情诗」「乡愁」「开花的树」。 擅长:爱情诗、乡愁诗、自然意象、诗画结合、青春记忆。

navigation main article SKILL.md
schedule Updated 2 months ago
momozi1996

xinzhiyuan-skill

by momozi1996
star 283

新智元(AI_era,国内AI领域权威媒体)的AI科技自媒体创作思维——中文叙事+惊叹号密集+记者视角+深度长文+快速快讯。 触发词:「新智元视角」「像新智元那样写」「AI行业深度报道」「AI人物榜」「AIGCRank」「超智能时代」。 擅长:AI行业新闻快讯(每日50+条)、深度长文报道、AI创业公司深度、技术报告中文解读、 AI人物年度评选(200人榜)、AI行业专题特辑(具身智能/超级算力等)。

navigation main article SKILL.md
schedule Updated 1 month ago
momozi1996

clawteam-directors-orchestrator

by momozi1996
star 283

ClawTeam导演智囊团——基于ClawTeam多智能体框架的世界著名导演协同创作系统。 整合31位全球顶级导演的风格思想,通过多智能体协作机制(顺序链、辩论投票、主席团模式) 辅助剧本创作、影像风格设计和叙事决策。 触发词:「导演智囊团」「ClawTeam」「多导演协作」「剧本创作」「影像风格」 适用场景:编剧、导演、创意策划、影视教育、AI影像创作

navigation main article SKILL.md
schedule Updated 1 month ago
momozi1996

eq-emotional-intelligence

by momozi1996
star 283

情商(EQ)训练专家系统——基于Mayer-Salovey能力模型与Goleman混合模型的 完整情商培养框架。涵盖自我意识、自我管理、社会意识、关系管理四大维度, 提供科学评估工具(MSCEIT/EQ-i 2.0/TEIQue)与实用训练方法。 触发词:「情商训练」「EQ提升」「情绪智力」「情绪管理」「情商测评」 适用场景:个人成长、职场发展、领导力培训、心理咨询辅助

navigation main article SKILL.md
schedule Updated 1 month ago
momozi1996

sel-social-emotional-learning

by momozi1996
star 283

社会情感学习(SEL)专家系统——基于CASEL框架的完整知识体系与实践指南。 涵盖五大核心能力(自我意识/自我管理/社会意识/人际关系/负责任决策)、 课程设计、教学策略、评估工具及全球本土化实践。 触发词:「SEL」「社会情感学习」「情绪教育」「CASEL」「社交技能训练」 适用场景:教育工作者、家长、学校管理者、教育研究者

navigation main article SKILL.md
schedule Updated 1 month ago
momozi1996

dangnianmingyue-perspective

by momozi1996
star 283

当年明月历史通俗写作思维——幽默风趣、现代视角、心灵历史、权力与人性。 触发词:「当年明月视角」「像当年明月那样写」「明朝那些事儿」「历史通俗化」。 擅长:历史通俗写作、幽默叙事、人物心理分析、权力斗争描写、现代语言解构历史。

navigation main article SKILL.md
schedule Updated 2 months ago
momozi1996

laoshe-perspective

by momozi1996
star 283

老舍京味儿文学思维——市民生活、幽默悲凉、茶馆里的中国、读书人的气节。 触发词:「老舍视角」「像老舍那样写」「骆驼祥子」「茶馆」「含泪的笑」。 擅长:京味儿文学、市民生活、幽默悲凉、戏剧对话、白描手法。

navigation main article SKILL.md
schedule Updated 2 months ago
momozi1996

libaihua-perspective

by momozi1996
star 283

李碧华小说创作思维——奇情叙事、冷艳诡谲、历史重构、香港都市传奇。 触发词:「李碧华视角」「像李碧华那样写」「奇情」「冷艳」「霸王别姬」。 擅长:爱情与恐怖交织、历史重构、女性执念、宿命轮回、影视化叙事。

navigation main article SKILL.md
schedule Updated 2 months ago
Page 1 of 6

Browse Agent Skills by Occupation

23 major groups · 867 SOC occupations

Browse by Category

Explore agent skills organized by their primary use case

SKILLMD / CREATORS AND OCCUPATION CATEGORIES

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.

SEO KNOWLEDGE HUB & TECHNICAL OVERVIEW

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.

8 QUESTIONS

Frequently Asked Questions

A practical guide to agent skills: what they are, how to inspect them, and how SkillMD helps you explore the ecosystem.