code-stitcher

To consolidate project files for LLM context loading, you can stitch multiple code and documentation files into one manageable flat text file. This aggregates your codebase while respecting .gitignore rules, simplifying comprehensive context provision to Large Language Models.

Yes, you can search across an entire codebase using grep by first aggregating project files into a single text file. This flat file serialization enables efficient project-wide search and analysis using standard command-line text processing tools.

Yes, code-stitcher respects .gitignore rules when aggregating source files. It consolidates supported code and documentation extensions into a single text file while automatically excluding ignored paths, ensuring only relevant project structures are read.

Yes, Swift is required as a dependency to stitch project files into one output file. The skill offers both script-based and direct Swift execution methods for reading project structures and writing the aggregated text output.

The best way to provide comprehensive project context to an LLM is to serialize your project structures into a readable flat format. Stitching supported code and documentation files into a single text file streamlines analysis and context loading.

When stitching project files into a single text file, aggregation is limited to supported common code and documentation extensions. Files matching .gitignore rules are excluded, meaning unsupported binary or non-text formats will not be included in the output.