QC5 BatchThresholdCheck logo

QC5 BatchThresholdCheck

Organization
cas-bigdatalab
QC5_BatchThresholdCheck

批量阈值检验工具。读取被检验表和阈值表,将数据列的值与阈值表中定义的上下限进行比对, 识别并标记超出允许范围(包括上限和下限)或为空值的数据点,最后输出为相同格式的文件。 当用户提到批量阈值检验、阈值表校验、多字段阈值检查、范围校验等需求时使用此skill。 即使用户没有明确说出"批量阈值",只要任务涉及根据阈值表进行多字段范围校验,就应该使用此skill。

Overview

Publishercas-bigdatalab
Repositorypiflow
Skill nameQC5_BatchThresholdCheck
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 QC5 BatchThresholdCheck 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/QC5_BatchThresholdCheck
  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/QC5_BatchThresholdCheck .claude/skills/QC5_BatchThresholdCheck
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable QC5 BatchThresholdCheck 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 QC5 BatchThresholdCheck 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 QC5 BatchThresholdCheck 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.

QC5_BatchThresholdCheck 批量阈值检验Skill

功能概述

本skill用于将数据表中的字段值与阈值表中定义的上下限进行批量比对,识别并标记超出允许范围(包括上限和下限)或为空值的数据点。

触发条件

当用户请求以下任务时,应使用此skill:

  • 批量阈值检验
  • 阈值表校验
  • 多字段阈值检查
  • 范围校验
  • 检查数值是否在阈值范围内
  • 批量范围检查

处理逻辑

  1. 读取被检验表和阈值表数据
  2. 从阈值表构建阈值映射表(字段名 -> 最大值, 最小值)
  3. 遍历数据表的每一行,检查每个阈值字段:
    • 如果字段值为空,标记为异常
    • 如果字段值超出最大值或小于最小值,标记为异常
  4. 为异常数据添加质控标识(格式:QC5(异常字段1,异常字段2,...))
  5. 输出处理后的数据文件

阈值表格式

阈值表必须包含以下三列:

  • field:字段名
  • max_value:最大值
  • min_value:最小值

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. 被检验表路径
  2. 阈值表路径
  3. 输出文件路径
  4. 质控标识(如:QC5)
  5. 质控标识字段名(默认:QC0000)

步骤2:执行批量阈值检验脚本

在 scripts/ 目录下找到 QC5_BatchThresholdCheck.py,使用Python执行:

bash
python scripts/QC5_BatchThresholdCheck.py \
    --original_data_path <被检验表> \
    --threshold_data_path <阈值表> \
    --output_path <输出文件> \
    --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
--original_data_path是被检验数据文件路径
--threshold_data_path是阈值表文件路径
--output_path是处理后数据输出路径
--qc_mark是质控标识(如QC5)
--mark_field_name否质控标识字段名,默认QC0000

阈值表示例

fieldmax_valuemin_value
age1200
height3000
weight5001

输出示例

[OK] Using encoding GB2312 successfully read CSV file
Successfully read file: /path/to/original.csv, shape: (1000, 18)
Successfully read file: /path/to/threshold.csv, shape: (5, 3)
Successfully written file: /path/to/output.csv
Processing completed! Output saved to: /path/to/output.csv

质控标识格式示例:QC5(age,height) 表示age和height字段超出阈值范围

注意事项

  1. 阈值表必须包含field、max_value、min_value三列
  2. 超出阈值范围或为空的值都会被标记
  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 QC5 BatchThresholdCheck AI skill do?

批量阈值检验工具。读取被检验表和阈值表,将数据列的值与阈值表中定义的上下限进行比对, 识别并标记超出允许范围(包括上限和下限)或为空值的数据点,最后输出为相同格式的文件。 当用户提到批量阈值检验、阈值表校验、多字段阈值检查、范围校验等需求时使用此skill。 即使用户没有明确说出"批量阈值",只要任务涉及根据阈值表进行多字段范围校验,就应该使用此skill。

Why use QC5 BatchThresholdCheck on TypingMind?

Because you install it once and use it with any model. QC5 BatchThresholdCheck 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 QC5 BatchThresholdCheck in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cas-bigdatalab/piflow/tree/master/workspace/skills/QC5_BatchThresholdCheck. 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 QC5 BatchThresholdCheck?

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 QC5 BatchThresholdCheck?

As many as you like. As long as a model supports skills, you can use QC5 BatchThresholdCheck with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the QC5 BatchThresholdCheck 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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