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Bracket Normalizer

Organization
cas-bigdatalab
bracket_normalizer

括号类型统一工具。读取结构化数据文件,执行中文/全角括号到 ASCII 半角括号的映射,输出括号已统一的结构化数据文件。 当用户提到括号统一、全角括号转半角、中文括号转换、括号规范化等需求时使用此skill。 即使用户没有明确说出"bracket_normalizer",只要任务涉及括号类符号统一,就应该使用此skill。 不负责全角字母数字转换、Unicode正规化或其他通用全半角处理。

Overview

Publishercas-bigdatalab
Repositorypiflow
Skill namebracket_normalizer
Stars
541
Forks
172
Bundled files
3
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.

  • 3 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 Bracket Normalizer 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/bracket_normalizer
  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/bracket_normalizer .claude/skills/bracket_normalizer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Bracket Normalizer 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 Bracket Normalizer 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 Bracket Normalizer 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.

bracket_normalizer 括号类型统一Skill

功能概述

将中文/全角括号统一为 ASCII 半角括号:【】〔〕[]→[],「」『』→"",《》〈〉→<>,()⦅⦆→(),{}→{}。

触发条件

  • 括号统一 / 全角括号转半角
  • 中文括号转换
  • 括号规范化
  • 括号类符号统一

核心参数说明

必需参数

参数说明
--input_path输入 CSV/TSV/Excel 等结构化文件路径
--output_path输出清洗后文件路径

可选参数

参数说明默认值
--text_columns需要处理的文本列,逗号分隔;不填则处理全部字符串列全部字符串列

输入文件格式

输入为结构化表格,文本列可包含中文/全角括号:

csv
id,text
1,"【标题】「引用」《书名》(说明)"

支持的文件格式

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

使用方法

bash
python scripts/bracket_normalizer.py \
    --input_path <输入文件> \
    --output_path <输出文件> \
    [--text_columns col1,col2]

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
--text_columns否处理的文本列

输出示例

[OK] 括号类型统一完成 -> output.csv
   列: ['text'], 映射: 20 对

输入 【重要】「日本語」《タイトル》 → 输出 [重要]"日本語"<タイトル>

环境要求

使用仓库内 Python 环境运行,无额外第三方依赖;读取/写入复用共享 data_io。

注意事项

  1. 使用 translate 高速 1:1 映射
  2. 左右括号独立映射,保持配对逻辑
  3. 中文语境下 「」→"" 可能改变语义,请确认业务场景

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 Bracket Normalizer AI skill do?

括号类型统一工具。读取结构化数据文件,执行中文/全角括号到 ASCII 半角括号的映射,输出括号已统一的结构化数据文件。 当用户提到括号统一、全角括号转半角、中文括号转换、括号规范化等需求时使用此skill。 即使用户没有明确说出"bracket_normalizer",只要任务涉及括号类符号统一,就应该使用此skill。 不负责全角字母数字转换、Unicode正规化或其他通用全半角处理。

Why use Bracket Normalizer on TypingMind?

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

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

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 Bracket Normalizer?

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

Is the Bracket Normalizer 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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