context-pack

Packaging a codebase for LLM context involves converting project files into a compact markdown format while filtering out noise like node_modules and build artifacts. This Skill automates that process, producing a single file optimized for AI context windows.

Yes, you can include binary files when packing a folder for AI analysis. The Skill optionally encodes binary files using Base64, allowing them to be included alongside text files in the final markdown output for comprehensive project context.

The best way to prepare a ZIP archive for AI code review is to unpack and filter its contents into markdown. This Skill handles ZIP archives directly, applying smart file discovery to exclude unnecessary directories and structure the output for AI consumption.

Yes, the codebase packaging tool automatically ignores common noise directories like .git and node_modules during file discovery. This ensures the generated LLM-friendly context contains only relevant project files, reducing token waste.

You can filter files by type, size, or custom patterns when creating an LLM context pack. The Skill supports flexible inclusion rules, allowing you to interactively select specific files and directories or exclude unwanted files from the final output.