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Fake2excel

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CoderWanFeng
fake2excel

自动创建 Excel 并模拟数据。当用户提到生成测试数据、mock 数据、造数据、Excel 模板、模拟数据时使用。

Overview

PublisherCoderWanFeng
Repositorypython-office
Skill namefake2excel
Stars
1.4K
Forks
305
Bundled files
1
LicenseApache-2.0
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.

  • 1 bundled files

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

  • Open source

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

Installation

Install the Fake2excel 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.
  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.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/CoderWanFeng/python-office.git /tmp/python-office
mkdir -p .claude/skills
cp -r /tmp/python-office/skills/excel/fake2excel .claude/skills/fake2excel
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Fake2excel 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 Fake2excel 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 Fake2excel 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.

fake2excel Skill

自动创建 Excel 文件并模拟数据

功能描述

自动生成一个 Excel 文件,并填充指定列的模拟数据。支持多种字段类型(如姓名、电话、地址等),支持中英文两种语言环境。

所属分类

office/skills/excel/fake2excel/

调用方式

python
from skills.excel import fake2excel

fake2excel(
    columns=['name', 'phone'],
    rows=100,
    path='./fake2excel.xlsx',
    language='zh_CN'
)

参数说明

参数类型必填默认值说明
columnslist['name']需要生成的列名。可模拟的字段参考:https://www.python4office.cn/python-office/fake2excel/
rowsint1生成的行数
pathstr'./fake2excel.xlsx'生成的 Excel 文件路径和名称
languagestr'zh_CN'数据语言。'zh_CN' 为中文,'english' 为英文

返回值

None

使用示例

python
# 示例 1:生成中文测试数据
from skills.excel import fake2excel
fake2excel(columns=['name', 'phone', 'address'], rows=1000, path='./test_cn.xlsx')

# 示例 2:生成英文测试数据
fake2excel(columns=['name', 'email'], rows=500, language='english', path='./test_en.xlsx')

视频教程

https://www.bilibili.com/video/BV1wr4y1b7uk/

原始函数

office.api.excel.fake2excel

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 Fake2excel AI skill do?

自动创建 Excel 并模拟数据。当用户提到生成测试数据、mock 数据、造数据、Excel 模板、模拟数据时使用。

Why use Fake2excel on TypingMind?

Because you install it once and use it with any model. Fake2excel 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 Fake2excel in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/CoderWanFeng/python-office/tree/develop/skills/excel/fake2excel. 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 Fake2excel?

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 Fake2excel?

As many as you like. As long as a model supports skills, you can use Fake2excel with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Fake2excel AI skill free?

Yes. It is published on GitHub by CoderWanFeng under the Apache-2.0 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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