QC6 SingleFieldMultiThresholdCheck logo

QC6 SingleFieldMultiThresholdCheck

Organization
cas-bigdatalab
QC6_SingleFieldMultiThresholdCheck

单字段多条件阈值检验工具。读取被检验表和阈值表,将指定字段的属性项值与阈值表中定义的多条件门限进行比对, 检查是否在门限范围内,不允许超出门限值(包括上限和下限)。不满足条件的数据会标记质控标识并输出异常数据。 当用户提到单字段阈值检验、多条件阈值检验、单字段多条件检查等需求时使用此skill。 即使用户没有说出"单字段多条件",只要任务涉及根据多个条件进行单字段阈值校验,就应该使用此skill。

Overview

Publishercas-bigdatalab
Repositorypiflow
Skill nameQC6_SingleFieldMultiThresholdCheck
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 QC6 SingleFieldMultiThresholdCheck 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/QC6_SingleFieldMultiThresholdCheck
  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/QC6_SingleFieldMultiThresholdCheck .claude/skills/QC6_SingleFieldMultiThresholdCheck
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable QC6 SingleFieldMultiThresholdCheck 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 QC6 SingleFieldMultiThresholdCheck 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 QC6 SingleFieldMultiThresholdCheck 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.

QC6_SingleFieldMultiThresholdCheck 单字段多条件阈值检验Skill

功能概述

本skill用于将被检验表中的指定字段的属性项值与阈值表中定义的多条件门限进行比对,检查是否在门限范围内(不允许超出门限值包括上限和下限)。不满足条件的数据会标记质控标识并输出异常数据。

触发条件

当用户请求以下任务时,应使用此skill:

  • 单字段阈值检验
  • 多条件阈值检验
  • 单字段多条件检查
  • 指定字段的范围校验
  • 字段多条件门限检查

处理逻辑

  1. 读取被检验表和阈值表数据
  2. 根据用户指定的检测字段,遍历阈值表的每一行条件
  3. 对每一行数据检查是否满足阈值条件:
    • max开头的列:检查字段值是否大于最大值
    • min开头的列:检查字段值是否小于最小值
    • 其他列:作为匹配条件进行精确匹配
  4. 如果数据不满足任何阈值条件,则标记为异常
  5. 为异常数据添加质控标识
  6. 输出两个文件:
    • 处理后的原始数据(带质控标识)
    • 异常数据(可选)

阈值表格式

阈值表可以包含以下类型的列:

  • max_xxx:最大值条件(如max_age表示age字段的最大值)
  • min_xxx:最小值条件(如min_age表示age字段的最小值)
  • 其他列:作为匹配条件进行精确匹配

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. 处理后原始数据输出路径
  4. 异常数据输出路径(可选)
  5. 检测字段名
  6. 质控标识
  7. 质控标识字段名(默认:QC0000)
  8. 唯一ID字段名(默认:ID0000)

步骤2:执行单字段多条件阈值检验脚本

在 scripts/ 目录下找到 QC6_SingleFieldMultiThresholdCheck.py,使用Python执行:

bash
python scripts/QC6_SingleFieldMultiThresholdCheck.py \
    --original_file <被检验表> \
    --threshold_file <阈值表> \
    --origin_output <处理后数据输出> \
    --error_output <异常数据输出> \
    --field_name <检测字段> \
    --qc_mark "<质控标识>" \
    --mark_field_name <质控字段名> \
    --id_field_name <ID字段名>

步骤3:返回结果

  • 如果有异常数据:显示异常数量并输出异常数据预览
  • 如果无异常:告知用户校验通过

参数说明

参数必填说明
--original_file是被检验数据文件路径
--threshold_file是阈值表文件路径
--origin_output是处理后原始数据输出路径
--error_output否异常数据输出路径(可选)
--field_name是阈值检测字段名
--qc_mark是质控标识
--mark_field_name否质控标识字段名,默认QC0000
--id_field_name否唯一ID字段名,默认ID0000

阈值表示例

min_agemax_ageregion
018north
1960south
61120east

表示:

  • region=north时,age需要在0-18之间
  • region=south时,age需要在19-60之间
  • region=east时,age需要在61-120之间

输出示例

有异常数据

[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: (3, 3)
########## Exception: Threshold check failed: out of range!!!
First 10 abnormal records:
...

无异常数据

[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: (3, 3)
Successfully written file: /path/to/output.csv

注意事项

  1. 阈值表支持多条件组合判断
  2. max开头的列表示最大值限制
  3. min开头的列表示最小值限制
  4. 其他列作为精确匹配条件
  5. 数据必须满足阈值表中任意一行条件,否则标记为异常
  6. 输出两个文件:处理后的原始数据(标记质控结果)和异常数据(可选)

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 QC6 SingleFieldMultiThresholdCheck AI skill do?

单字段多条件阈值检验工具。读取被检验表和阈值表,将指定字段的属性项值与阈值表中定义的多条件门限进行比对, 检查是否在门限范围内,不允许超出门限值(包括上限和下限)。不满足条件的数据会标记质控标识并输出异常数据。 当用户提到单字段阈值检验、多条件阈值检验、单字段多条件检查等需求时使用此skill。 即使用户没有说出"单字段多条件",只要任务涉及根据多个条件进行单字段阈值校验,就应该使用此skill。

Why use QC6 SingleFieldMultiThresholdCheck on TypingMind?

Because you install it once and use it with any model. QC6 SingleFieldMultiThresholdCheck 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 QC6 SingleFieldMultiThresholdCheck in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cas-bigdatalab/piflow/tree/master/workspace/skills/QC6_SingleFieldMultiThresholdCheck. 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 QC6 SingleFieldMultiThresholdCheck?

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 QC6 SingleFieldMultiThresholdCheck?

As many as you like. As long as a model supports skills, you can use QC6 SingleFieldMultiThresholdCheck with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the QC6 SingleFieldMultiThresholdCheck 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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