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H And M
by
hanxueyuan
· GitHub ↗
· v1.0.0
· MIT-0
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Install in OpenClaw
/install h-and-m
Description
瑞典快时尚巨头，全球第二大服装零售商，主打平价潮流，正积极推进可持续时尚转型和数字化布局。
README (SKILL.md)
H&M (Hennes & Mauritz) — 民主时尚的瑞典巨人
一句话
从一家瑞典女装小店成长为全球第二大服装零售商，H&M以平价时尚改变大众穿衣方式，如今正经历从"快时尚"向"可持续时尚"的艰难转型。
历史时间线
- 1947：Erling Persson在瑞典韦斯特罗斯开设首家女装店"Hennes"（瑞典语"她的"）
- 1968：收购狩猎用品店Mauritz Widforss，更名为Hennes & Mauritz，开始销售男装
- 1974：斯德哥尔摩证券交易所上市
- 1998：入驻纽约第五大道，开启全球化扩张
- 2004：推出首个明星联名系列（Karl Lagerfeld），开创快时尚×设计师合作先河
- 2007：全球门店突破2,000家
- 2013：与麦当娜、David Beckham合作，名人联名成为品牌战略核心
- 2018：库存危机 — 43亿美元积压库存，暴露快时尚模式瓶颈
- 2019：推出"Conscious"可持续系列，回收旧衣计划覆盖全球门店
- 2021：新疆棉花事件引发中国市场危机，门店从高峰期的500+缩减至不足100
- 2023：加速数字化转型，电商收入占比突破25%
- 2024：关闭亏损门店，聚焦核心市场和盈利门店
商业模式
- 垂直整合供应链：自主设计+外包生产+自营零售，从设计到上架最快2-3周
- 多品牌矩阵：COS（极简高端）、& Other Stories、Arket、Monki、Weekday，覆盖不同价格带和风格
- 联名策略：每年与设计师/明星合作10+系列，制造稀缺感和话题
- 全渠道零售：全球约4,200家门店 + 电商覆盖70+市场
护城河分析
- 规模经济：全球近4,000家门店带来的采购议价能力和物流网络
- 多品牌覆盖：通过不同子品牌覆盖从大众到轻奢的全价格带
- 数据驱动的设计：基于销售数据快速调整产品组合，降低滞销风险
- 品牌认知度：全球品牌知名度超90%
关键数据
- 2023年营收约1,860亿瑞典克朗（约180亿美元）
- 全球约4,200家门店，覆盖约70个市场
- 员工约10万人
- COS等高端子品牌增速超过主品牌，贡献约15%营收
- 目标2030年实现100%可回收或可持续来源材料
有趣事实
- H&M的创始人Erling Persson是在美国旅行时看到超低价女装后获得灵感 — 他注意到美国女性服装比瑞典便宜很多
- H&M曾是全球最大的棉花采购企业之一，每年消耗全球约1%的棉花产量
- 2021年新疆棉事件后，H&M在中国的销售额暴跌约40%，这是地缘政治对商业品牌影响力的经典案例
Usage Guidance
This skill is an informational H&M company profile and appears coherent and low-risk. If you install it, understand that content may be static or out of date and comes without cited sources — verify any facts you rely on against authoritative or up-to-date sources if accuracy matters. No credentials or system access are requested, so there is no obvious security exposure from installing this skill.
Capability Analysis
Type: OpenClaw Skill
Name: h-and-m
Version: 1.0.0
The skill bundle contains purely informational and educational content regarding the history, business model, and market analysis of the fashion retailer H&M. There are no executable code snippets, shell commands, network requests, or prompt injection attempts within the SKILL.md or _meta.json files.
Capability Assessment
Purpose & Capability
The skill name/description match the content: it's a company profile of H&M. There are no unrelated environment variables, binaries, or install actions requested.
Instruction Scope
SKILL.md is purely informational (history, business model, facts) and its read_when hints describe appropriate contexts. It does not instruct the agent to read files, access environment variables, call external endpoints, or collect/transmit user data.
Install Mechanism
No install spec and no code files — lowest-risk form (instruction-only). Nothing will be written to disk or fetched during install.
Credentials
The skill requires no environment variables, credentials, or config paths; requested access is proportional (none).
Persistence & Privilege
Default autonomy settings apply (agent-invocable, not always: true). There is no request for permanent presence or modification of other skills or system settings.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install h-and-m - After installation, invoke the skill by name or use
/h-and-m - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of the “h-and-m” skill:
- 提供H&M公司简史、关键里程碑和发展历程，高度浓缩“快时尚”到“可持续”转型要点
- 分析H&M商业模式，包括供应链、子品牌架构、联名与全渠道零售
- 梳理核心竞争优势与护城河
- 提供最新的核心经营数据和转型目标
- 补充有趣行业事实与公司趣闻，帮助理解品牌影响力及挑战
Metadata
Frequently Asked Questions
What is H And M?
瑞典快时尚巨头，全球第二大服装零售商，主打平价潮流，正积极推进可持续时尚转型和数字化布局。 It is an AI Agent Skill for Claude Code / OpenClaw, with 72 downloads so far.
How do I install H And M?
Run "/install h-and-m" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is H And M free?
Yes, H And M is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does H And M support?
H And M is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created H And M?
It is built and maintained by hanxueyuan (@hanxueyuan); the current version is v1.0.0.
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