QC8 DataTypeCheck logo

QC8 DataTypeCheck

Organization
cas-bigdatalab
QC8_DataTypeCheck

数据类型检查工具。读取被检验表,检查指定数值型字段的数据类型是否正确(是否能转换为数值型), 并标记不合格的数据点,最后输出为相同格式的文件。 当用户提到数据类型检查、数值类型校验、字段类型检查、数据格式校验等需求时使用此skill。 即使用户没有说出"数据类型检查",只要任务涉及检查数据字段类型是否正确,就应该使用此skill。

Overview

Publishercas-bigdatalab
Repositorypiflow
Skill nameQC8_DataTypeCheck
Stars
541
Forks
172
Bundled files
4
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.

  • 4 bundled files

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

  • Open source

    Published by cas-bigdatalab on GitHub. Read the source before you install it.

Installation

Install the QC8 DataTypeCheck 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/cas-bigdatalab/piflow/tree/master/workspace/skills/QC8_DataTypeCheck
  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/cas-bigdatalab/piflow.git /tmp/piflow
mkdir -p .claude/skills
cp -r /tmp/piflow/workspace/skills/QC8_DataTypeCheck .claude/skills/QC8_DataTypeCheck
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable QC8 DataTypeCheck 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 QC8 DataTypeCheck 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 QC8 DataTypeCheck 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.

QC8_DataTypeCheck 数据类型检查Skill

功能概述

本skill用于检查指定数值型字段的数据类型是否正确(是否能转换为数值型),将无法转换为数值型的数据标记为不合格,并输出处理后的数据文件。

触发条件

当用户请求以下任务时,应使用此skill:

  • 数据类型检查
  • 数值类型校验
  • 字段类型检查
  • 数据格式校验
  • 检查字段是否为数值型
  • 验证数据类型

处理逻辑

  1. 读取输入的被检验数据
  2. 解析需要检查的字段列表(逗号分隔)
  3. 对每个指定字段进行检查:
    • 如果字段值可以转换为数值型,则为正常
    • 如果字段值无法转换为数值型(如包含字母、特殊字符等),则标记为异常
    • 空值(NA/NaN)不判定为错误
  4. 为异常数据添加质控标识(格式:QC8(字段1,字段2,...))
  5. 输出处理后的数据文件

支持的文件格式

  • CSV (.csv)
  • TSV (.tsv)
  • Excel (.xls, .xlsx)
  • SPSS (.sav)

使用方法

步骤1:获取用户输入输出路径及参数

向用户确认:

  1. 输入文件路径
  2. 输出文件路径
  3. 检查字段名(逗号分隔)
  4. 质控标识(如:QC8)
  5. 质控标识字段名(默认:QC0000)

步骤2:执行数据类型检查脚本

在 scripts/ 目录下找到 QC8_DataTypeCheck.py,使用Python执行:

bash
python scripts/QC8_DataTypeCheck.py \
    --input_path <输入文件> \
    --output_path <输出文件> \
    --check_fields_name "<检查字段>" \
    --qc_mark "<质控标识>" \
    --mark_field_name <质控字段名>

步骤3:返回结果

告知用户处理完成,异常数据已标记质控标识。

参数说明

参数必填说明
--input_path是输入文件路径
--output_path是输出文件路径
--check_fields_name是检查字段名,逗号分隔(如:field1,field2)
--qc_mark是质控标识
--mark_field_name否质控标识字段名,默认QC0000

输出示例

[OK] Using encoding GB2312 successfully read CSV file
Reading input data: /path/to/input.csv
Starting data type check, check fields: fa0116,fa0118
Writing output data: /path/to/output.csv
Processing completed!

质控标识格式示例:QC8(fa0116) 表示fa0116字段存在非数值型数据

注意事项

  1. 检查字段名用逗号分隔,可以同时检查多个字段
  2. 空值(NA/NaN)不会被标记为错误
  3. 质控标识格式:质控标识(异常字段1,异常字段2,...)
  4. 多个异常字段用逗号分隔
  5. 与原有质控标识用分号拼接

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 QC8 DataTypeCheck AI skill do?

数据类型检查工具。读取被检验表,检查指定数值型字段的数据类型是否正确(是否能转换为数值型), 并标记不合格的数据点,最后输出为相同格式的文件。 当用户提到数据类型检查、数值类型校验、字段类型检查、数据格式校验等需求时使用此skill。 即使用户没有说出"数据类型检查",只要任务涉及检查数据字段类型是否正确,就应该使用此skill。

Why use QC8 DataTypeCheck on TypingMind?

Because you install it once and use it with any model. QC8 DataTypeCheck 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 QC8 DataTypeCheck in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cas-bigdatalab/piflow/tree/master/workspace/skills/QC8_DataTypeCheck. 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 QC8 DataTypeCheck?

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 QC8 DataTypeCheck?

As many as you like. As long as a model supports skills, you can use QC8 DataTypeCheck with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the QC8 DataTypeCheck AI skill free?

It is published on GitHub by cas-bigdatalab. Check the repository for licensing terms. 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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