Convert local code repositories into formatted text transcripts for LLM analysis.
npx skills add https://github.com/aresbit/MateBot --skill repo2txt
Please help me install this Agent Skill. Skill: repo2txt Source: https://github.com/aresbit/MateBot/tree/main/skills/repo2txt Command: npx skills add https://github.com/aresbit/MateBot --skill repo2txt
This Skill converts local code repositories into a formatted text transcript suitable for analysis by large language models.
Run the repo2txt tool on a local repository to generate a textual report. Example: python3 scripts/repo2txt.py /path/to/repo -o output.txt
High-intent search queries and answers about installing and using this skill.
To convert a code repository for LLM analysis, run the Python CLI script to generate a text transcript containing the repository summary, directory structure, and file contents. You can specify the target path and output file directly from the command line.
Extracting file contents for an AI code review is done by filtering the repository by specific file extensions and ignore patterns. This generates a focused, formatted text report of the code, making it easier for large language models to process the relevant data.
No external dependencies are required to format repository code into a text transcript. The tool runs on Python 3 using only the standard library, meaning you can execute the script immediately without installing additional packages via pip or other managers.
Yes, you can exclude specific file types and directories when exporting a repository structure for debugging. The CLI provides options to include or exclude file extensions, apply ignore patterns, and use flags to omit the directory tree or summary from the final text output.
The generated repository text transcript for large language models contains a three-part report. This includes a repository summary, the directory structure, and the extracted file contents, providing a comprehensive overview of the codebase for AI processing.
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