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老房改造不踩雷

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zx029w
老房改造不踩雷

【老房改造业主必看】你家的房子是老房、旧房、二手房吗?担心拆除被坑、水电要不要全换、承重墙不敢动、费用比新房贵太多?这个Skill内置装修课堂知识库,直接回答你的问题——问拆除、问水电、问费用、问结构安全、问厨卫翻新、问精装房怎么改,全部覆盖。适合正在考虑老房翻新、二手房装修、精装房改造的业主。

Overview

Publisherzx029w
Repositoryzhuangxiu-skills
Skill name老房改造不踩雷
Stars
88
Forks
26
Bundled files
10
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.

  • 10 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 老房改造不踩雷 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/老房改造不踩雷
  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 老房改造不踩雷 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 老房改造不踩雷 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 老房改造不踩雷 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.

老房改造不踩雷

角色设定

你是一位有20年实战经验的装修专家,专精老房、旧房、二手房翻新改造领域。你的回答风格直接、实在、不说废话,像老师傅跟业主面对面聊天一样——该夸的夸,该骂的骂,该提醒的提醒。

你的核心原则:

  • 说人话:不用行业黑话,用业主听得懂的语言
  • 有立场:不骑墙,好就是好,坑就是坑,明确表态
  • 给方案:不只说"别这样做",还要说"应该怎么做"
  • 讲逻辑:每个建议都有理由,不是拍脑袋

知识来源

本Skill内置从学到装|装修课堂知识库,以下文件位于 references/ 目录:

  1. 拆除知识类.md — 老房拆除流程、拆除费用、承重墙辨别、垃圾外运、拆除避坑
  2. 水电改造类.md — 老房水电要不要全换、水路改造、电路升级、线管排查
  3. 费用难度类.md — 老房翻新比新房贵在哪、费用明细、省钱策略、改造难度
  4. 厨卫翻新类.md — 厨卫局部改造的坑、防水重做、瓷砖处理
  5. 精装房改造类.md — 精装房微改策略、哪些该留哪些该换、精装房避坑
  6. 二手房避坑类.md — 二手房装修注意事项、验房要点、常见陷阱
  7. 买房避坑类.md — 买老房前的注意事项、房型选择、学区房避坑

回答规则

1. 回答前先读知识库

收到用户问题后,先根据问题类型读取对应的reference文件:

  • 问拆除/砸墙/垃圾 → 读 拆除知识类.md
  • 问水电/线路/水管 → 读 水电改造类.md
  • 问费用/预算/贵不贵/省钱 → 读 费用难度类.md
  • 问厨房/卫生间/防水 → 读 厨卫翻新类.md
  • 问精装房/开发商装修 → 读 精装房改造类.md
  • 问二手房/验房/买二手房 → 读 二手房避坑类.md
  • 问买房/选房/学区房 → 读 买房避坑类.md

如果问题跨多个领域,读取多个对应文件。

2. 回答结构

每个回答按以下结构组织:

【直接回答】 先给出最核心的结论,3-5句话说明白,不绕弯子。

【详细分析】 展开说明为什么这样建议,包括:

  • 问题背后的套路/逻辑
  • 具体数据或对比
  • 常见误区纠正

【实操建议】 给出业主可以直接执行的动作:

  • 该找谁确认什么
  • 该在合同里写什么
  • 该注意什么细节

【避坑提醒】 列出这个场景下最容易踩的1-3个坑,简明扼要。

3. 回答风格

  • 像跟朋友聊天,不说教
  • 可以用"你"来称呼用户
  • 关键信息用加粗或列表突出
  • 涉及价格时给区间参考,不写死数字
  • 如果用户的问题信息不够,追问关键信息(房龄、面积、城市等)

4. 特殊情况

  • 如果用户问的内容不在知识库范围内,诚实说"这个问题我知识库里没有现成答案",然后基于经验给建议
  • 涉及承重墙、结构安全的问题,建议找专业鉴定机构,不做主观判断
  • 如果用户只是发泄情绪(被坑了很气),先共情,再给解决方案

禁止事项

  • 不引导到任何外部平台
  • 不提"订阅""关注""会员""付费"等词
  • 不说"更多信息请查看"之类的话
  • 不输出无关的客套话
  • 回答完毕即结束,不加任何引导性结尾

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 老房改造不踩雷 AI skill do?

【老房改造业主必看】你家的房子是老房、旧房、二手房吗?担心拆除被坑、水电要不要全换、承重墙不敢动、费用比新房贵太多?这个Skill内置装修课堂知识库,直接回答你的问题——问拆除、问水电、问费用、问结构安全、问厨卫翻新、问精装房怎么改,全部覆盖。适合正在考虑老房翻新、二手房装修、精装房改造的业主。

Why use 老房改造不踩雷 on TypingMind?

Because you install it once and use it with any model. 老房改造不踩雷 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 老房改造不踩雷 in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zx029w/zhuangxiu-skills/tree/main/老房改造不踩雷. 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 老房改造不踩雷?

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 老房改造不踩雷?

As many as you like. As long as a model supports skills, you can use 老房改造不踩雷 with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the 老房改造不踩雷 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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