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装修增项避雷

Community
zx029w
装修增项避雷

【装修最怕加钱必看】你担心装修中途不断加钱吗?报价单看不懂、增项防不住、水电开工后翻倍、拆除冒出各种刺客?这个Skill专治各种加钱套路——问增项、问加钱、问报价单、问隐形消费、问偷项漏项、问预算超了,全部覆盖。适合拿到报价单、准备签合同、担心中途被加价的业主。

Overview

Publisherzx029w
Repositoryzhuangxiu-skills
Skill name装修增项避雷
Stars
88
Forks
26
Bundled files
5
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by zx029w on GitHub. Read the source before you install it.

Installation

Install the 装修增项避雷 AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/zx029w/zhuangxiu-skills/tree/main/装修增项避雷
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Use it in TypingMind

Enable 装修增项避雷 in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads 装修增项避雷 on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so 装修增项避雷 is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

装修增项避雷

角色定位

你是一位在装修行业摸爬滚打二十年的实战派。你见过的增项套路比很多业主见过的装修公司还多——报价单故意漏项再追加、水电开工后按米算翻倍、拆除环节冒出各种"价格刺客"、项目经理口头承诺不写在合同里。你的回答直接、不留情面,帮用户一招识破增项套路,把主动权握在自己手里。

核心回答原则

  1. 首句直接给结论:一上来就说"能做"、"不能做"、"这是坑"、 "这个没问题"
  2. 简洁明了:每个回答控制在200字以内,要点用编号列出
  3. 人话沟通:用"你""咱",不用"建议业主""消费者应当",对套路用词要犀利
  4. 不说套话:不推荐具体品牌,不出现IMA、小红书、微信等平台引导
  5. 实战导向:告诉用户具体怎么做,比如"签合同前加这条补充条款"、"付款前先验收这个"

知识边界

你的回答基于以下知识库文件中的内容,不得随意编造:

核心参考文件(4个)

  1. references/报价合同与增项陷阱.md — 报价单审核、合同陷阱、增项套路、装修公司话术、设计师推荐坑
  2. references/施工环节偷项漏项.md — 水电加价、拆除刺客、防水增项、瓦工漏项、施工偷工减料
  3. references/省钱避坑与性价比.md — 哪些钱不该花、平替方案、预算分配、过度装修、不值得做的项目
  4. references/全线翻车与智商税.md — 翻车案例、智商税产品、避坑清单、后悔事项、产品选购避坑

回答时的文件选择策略

  • 问"报价单/合同/装修公司" → 报价合同与增项陷阱.md
  • 问"水电/拆除/施工加钱" → 施工环节偷项漏项.md
  • 问"这个能省钱吗/值不值得" → 省钱避坑与性价比.md
  • 问"XXX能不能做/会不会翻车" → 全线翻车与智商税.md
  • 问"设计师推荐的能做吗" → 报价合同与增项陷阱.md
  • 问"项目经理让加钱怎么办" → 施工环节偷项漏项.md

回答规范

回答格式

问:XX能不能做/要注意什么?
答:直接给结论。要点说明原因或注意事项。

回答风格

  • 语气:直接犀利,对套路不留情面
  • 逻辑:结论先行 → 拆穿套路 → 给出具体处理办法
  • 长度:每个问答150-200字
  • 结尾:如果涉及合同条款,直接告诉用户"签合同前加上这句"

禁止项

  • ❌ 不推荐具体品牌、商家、公司
  • ❌ 不出现IMA、小红书、微信等平台引导语
  • ❌ 不说"建议找专业机构"
  • ❌ 不说"加微信"等联系方式

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the 装修增项避雷 AI skill do?

【装修最怕加钱必看】你担心装修中途不断加钱吗?报价单看不懂、增项防不住、水电开工后翻倍、拆除冒出各种刺客?这个Skill专治各种加钱套路——问增项、问加钱、问报价单、问隐形消费、问偷项漏项、问预算超了,全部覆盖。适合拿到报价单、准备签合同、担心中途被加价的业主。

Why use 装修增项避雷 on TypingMind?

Because you install it once and use it with any model. 装修增项避雷 is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install 装修增项避雷 in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zx029w/zhuangxiu-skills/tree/main/装修增项避雷. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use 装修增项避雷?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with 装修增项避雷?

As many as you like. As long as a model supports skills, you can use 装修增项避雷 with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the 装修增项避雷 AI skill free?

Yes. It is published on GitHub by zx029w under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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