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llm-codebase-context
Advanced tools
A command-line tool to prepare your codebase for submission to Large Language Models (LLMs) like ChatGPT or Claude. It creates a formatted context file that includes your source code while intelligently filtering out binary files, large files, and commonl
A command-line tool to prepare your codebase for submission to Large Language Models (LLMs) like ChatGPT or Claude. It creates a formatted context file that includes your source code while intelligently filtering out binary files, large files, and commonly ignored directories.
# Install globally
npm install -g llm-codebase-context
# Or run with npx without installing
npx llm-codebase-context <project_root>
# Process the current directory and output to structure.txt
codebase-context .
# Process a specific project and specify output file
codebase-context /path/to/project output.txt
# Process only a subdirectory of your project
codebase-context /path/to/project output.txt src
# Add custom ignore patterns
codebase-context . output.txt . "tests,fixtures,*.json"
# Process a specific subdirectory with custom ignores
codebase-context /path/to/project output.txt src "*.test.js,*.spec.js,__tests__"
The tool comes with sensible defaults that work for most projects:
The tool automatically ignores common patterns including:
node_modules, package-lock.json, etc..git, .gitignoredist, build, .next, etc..DS_Store, Thumbs.db.env files, .pem, .keylogs, *.log, temp, tmp__pycache__, *.class, etc.The tool produces an XML-formatted file with each source file enclosed in <file> tags:
<file path="src/index.js">
// File content goes here
</file>
<file path="src/utils/helpers.js">
// Another file's content
</file>
This format is optimized for use with LLMs as it clearly delineates file boundaries and preserves path information.
Contributions are welcome! Feel free to submit issues or pull requests.
ISC
FAQs
A command-line tool to prepare your codebase for submission to Large Language Models (LLMs) like ChatGPT or Claude. It creates a formatted context file that includes your source code while intelligently filtering out binary files, large files, and commonl
We found that llm-codebase-context demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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