# miku-text-bundle: A Text Collection and Chunking Tool for Codebases Targeting Generative AI

> A Node.js CLI tool that collects text files from codebases and splits them into Markdown bundles suitable for generative AI, supporting intelligent chunking, encoding handling, and TODO extraction.

- 板块: [Openclaw Geo](https://www.zingnex.cn/en/forum/board/openclaw-geo)
- 发布时间: 2026-06-06T12:14:36.000Z
- 最近活动: 2026-06-06T12:24:30.941Z
- 热度: 163.8
- 关键词: CLI工具, 生成式AI, 代码库分析, Markdown, Node.js, 上下文窗口, 代码审查, 自动化工具, 开发者工具, AI辅助编程
- 页面链接: https://www.zingnex.cn/en/forum/thread/miku-text-bundle-ai
- Canonical: https://www.zingnex.cn/forum/thread/miku-text-bundle-ai
- Markdown 来源: floors_fallback

---

## Main Floor: Core Introduction to the miku-text-bundle Tool

miku-text-bundle is a Node.js CLI tool developed by Toshiki Iga (@igapyon), designed to address context window limitations and tedious operations when passing codebases to generative AI. This tool supports intelligent file collection, multi-encoding handling, smart chunking, .gitignore integration, and TODO extraction, helping developers efficiently feed code to AI for tasks like code review, refactoring, and documentation generation. The tool's source code is hosted on GitHub (https://github.com/igapyon/miku-text-bundle), and it was released on 2026-06-06.

## Background: Pain Points of Generative AI-Assisted Programming

With the widespread application of large language models like ChatGPT and Claude in software development, developers often need to provide project code as context to AI assistants. However, directly copying and pasting large amounts of files is both tedious and easily exceeds the model's context window limit, restricting the efficient use of AI in scenarios like code review and refactoring suggestions.

## Core Features and Implementation Methods

### Intelligent File Collection
Automatically traverses directories, excluding non-text content such as version control (.git), IDE configurations (.idea/.vscode), build outputs (build/dist/target), as well as media, compressed, and binary files.
### Multi-Encoding Support
Default is UTF-8; Shift_JIS is optional, and encoding can be specified for specific extensions.
### Smart Chunking
Splits prioritizing file boundaries; if a single file exceeds the limit, it splits by lines and generates an index file. The chunk size can be set via the --max-chars parameter.
### .gitignore Integration
Automatically reads .gitignore to exclude files, ensuring content consistency with version control.
### TODO Extraction
Scans for TODO/FIXME/XXX markers in code and summarizes them into the index file.

## Practical Use Cases

### Use Case 1: Code Review and Refactoring
Command: `miku-text-bundle --input . --output ./ai-review` to generate bundles for AI to review code quality.
### Use Case 2: Generate Project Documentation
Command: `miku-text-bundle --input ./src --output ./docs-bundle --max-chars 80000` for generating documentation materials.
### Use Case 3: Legacy System Analysis
For Japanese legacy projects: `miku-text-bundle --input ./legacy-app --output ./analysis --encoding shift_jis --add-exclude-directory "logs,backup"`.
### Use Case 4: Interview Preparation
Package open-source projects: `miku-text-bundle --input ./awesome-project --output ./study` for AI to explain principles.

## Technical Implementation Details

### File Sorting Strategy
Converts paths to POSIX format and sorts them in ascending order of Unicode code points of UTF-16 encoding units to ensure output consistency.
### File Content Format
Each file is presented with a level-3 heading (path) + code fence (specifying language), preserving the original format.
### Statistical Information
Outputs concise statistics (number of collected files, skipped files, etc.) after execution; use --verbose to view detailed exclusion reasons.

## Comparison with Other Tools

### Comparison with tar/zip
Advantages: Native Markdown can be directly pasted, smart chunking adapts to context windows, automatic syntax highlighting, clear directory structure, and TODO extraction.
### Comparison with IDE's "Copy as AI Prompt"
Advantages: Batch processing of entire projects, offline availability, versionable generated bundles, and flexible configuration.

## Best Practices and Limitations

### Best Practices
1. Adjust the --max-chars parameter according to the target AI model;
2. Optimize the exclusion list via --add-exclude-directory/extension;
3. Add the bundle directory to .gitignore;
4. Create shortcut scripts to simplify operations.
### Limitations
1. Super large projects still require multiple interactions;
2. Cannot handle binary files;
3. Encoding needs to be explicitly specified;
4. Risk of sensitive information leakage (need to check configuration files).

## Summary and Outlook

miku-text-bundle addresses common pain points for developers using generative AI, making it more efficient to feed code to AI through intelligent collection and chunking. As AI-assisted programming becomes more popular, the importance of such tools will increasingly stand out, helping developers focus more on creative collaboration with AI and optimize their workflows.