This repository contains a collection of advanced agentic skills modeled after professional business consulting frameworks and methodologies. Specifically, these skills draw heavily from former McKinsey Analyst Xiao Jing's strategic models presented in his best-selling book How to Quickly Understand an Industry. 本项目包含一系列仿效专业商业咨询框架和方法论的高级智能体技能（Agentic Skills）。具体而言，这些技能深度借鉴了前麦肯锡咨询顾问肖璟在其畅销书《如何快速了解一个行业》中提出的战略模型。
🏆 About the Book
- Douban 2025 Annual Book (Economics & Management Top 6)
- WeChat Reading 2025 Annual Book Top 9
- WeChat Reading Masterpiece List
🏆 关于本书
- 豆瓣2025年年度图书·经管Top6
- 微信读书2025年年度榜单Top9
- 微信读书神作榜
These skills are designed to empower AI agents to perform complex business analyses, market sizing, strategic evaluations, and professional communication. 这些技能旨在赋能 AI 智能体，让其能够执行复杂的商业分析、市场规模估算、战略评估以及专业的商业沟通。
The project is organized into modular skills, each containing its own instructions (SKILL.md), reference cases, and execution scripts.
本项目采用模块化的技能组织形式，每个技能都包含其独立的指令说明（SKILL.md）、参考案例文件以及执行脚本。
This skill acts as a geo-spatial data intelligent assistant, empowering agents to autonomously fetch, process, and analyze real-world location data to support physical business decisions. 该技能相当于一个地理空间数据智能助手，赋能智能体自主获取、处理和分析真实的物理位置数据，以支持实体商业的经营决策。
- Core Capabilities:
- Automatically handles AMAP API authentication and geocoding.
- Scans surrounding POIs (Points of Interest) based on specified radius and industry keywords.
- Generates competitive density reports and identifies market gaps/blue oceans based on "heat logic" (proximity to traffic hubs, offices, residential areas).
- 核心功能:
- 全自动处理高德开放平台的 API 鉴权和地理编码转换。
- 根据指定的辐射半径和行业关键词，自动爬取和扫描周边的兴趣点（POI）。
- 生成区域商业竞争密度报告，并基于“热点逻辑”（如靠近交通枢纽、写字楼、住宅区）自动识别市场断层与“蓝海”区域。
This skill provides a structured calculation engine that prevents AI hallucination or arithmetic errors when estimating market sizes or company revenues. 该技能提供了一个结构化的商业计算引擎，专门用于在估算市场规模或公司营收时，防止 AI 产生幻觉或算术错误。
- Core Capabilities:
- Executes precise calculations for TAM, SAM, and SOM using bundled Python scripts.
- Demand Model: Calculates market ceilings based on target demographics, penetration rates, and purchasing frequencies.
- Supply Model: Estimates maximal output or revenue for single entities (e.g., a store or factory) by analyzing systemic bottlenecks.
- Matching Model: Derives mature market sizes using established industry proxy ratios.
- 核心功能:
- 调用内置的 Python 脚本，精确执行计算总潜在市场、可服务市场和可获得市场（TAM/SAM/SOM）的过程。
- 需求端测算模型: 结合目标受众、渗透率和购买频次估算市场天花板。
- 供给端测算模型: 通过分析系统瓶颈节点，测算单体（如一家门店或工厂）的最大产能/营收极限。
- 对标测算模型: 利用成熟的行业代理比例映射关系推导市场规模。
This skill turns the AI into a strict strategic auditor, using a rigid framework to evaluate a company's true defensibility while filtering out superficial business results. 该技能将 AI 转化为一位严苛的战略审计师，使用死磕定义的框架来评估一家公司真正的防御护城河，同时过滤掉表面的商业繁荣。
- Core Capabilities:
- Systematically parses business descriptions against the "5 Factors" (Land, Labor, Capital, Tech, Data) and "4 Relations" (Government, Peers, Suppliers, Customers).
- Enforces strict category boundaries (e.g., stopping the AI from confusing a government license with natural land resources, or labeling "low costs" as a moat instead of a result).
- Outputs a standardized, structured audit report detailing the exact nature of a company's monopolies.
- 核心功能:
- 将复杂的商业描述系统性地拆解映射到“5大生产要素”（土地、劳动、资本、技术、数据）与“4大生产关系”（政府、同行、企业、供应商）。
- 强制执行严格的分类边界（例如，阻止 AI 错将政府牌照等同于自然地理资源，或纠正其将“低成本”这种结果误判为护城河）。
- 最终输出一份标准化、结构化的战略审计报告，精确指出企业在哪些关键节点构筑了垄断优势。
This skill functions as a presentation architect, forcing unstructured thoughts into persuasive, tailored narratives suited for different professional contexts. 该技能充当一个商业演示架构师，负责将松散枯燥的想法强制转换成针对不同专业场合量身定制的、具有说服力的商业叙事。
- Core Capabilities:
- Restructures raw information using the SCQR (Situation-Complication-Question-Resolution) framework.
- Dynamically switches narrative templates based on target audiences: from high-hook short video scripts (C-Q-S-R) to direct executive summaries (R-S-C-Q).
- Ensures outputs focus on logical business implications rather than chronological accounting.
- 核心功能:
- 使用经典的 SCQR（空雨湿伞）模型对原始商业信息进行骨架重构。
- 能够根据目标受众动态切换表达模板：从强冲突开场的短视频脚本（C-Q-S-R），到结论先行的高管汇报大纲（R-S-C-Q）。
- 确保输出内容始终聚焦于商业逻辑推演，彻底摒弃按时间顺序推进的流水账文风。
To use these skills, simply provide this repository's link (https://github.com/raphaelxiao/mck_skills) to an AI agent like OpenClaw (小龙虾) and instruct it to install and use the skills directly.
要使用这些技能，只需将本项目的链接（https://github.com/raphaelxiao/mck_skills）发送给像 OpenClaw（小龙虾） 这样的 AI 智能体，直接让它安装并调用即可。