When feeding full repositories to AI coding agents, a significant portion of your token budget is wasted on boilerplate: long lists of external imports, standard license headers, and repetitive utility declarations.

Simply stripping whitespace is dangerous: Python, YAML, and formatted strings break immediately.

In TokenCap, we built src/pack/fold.js to perform format-aware context folding.

How Folding Operates

  1. Import Clustering: The tokenizer detects consecutive import statements and condenses them into a single-line structural fold: 
 // [Folded 18 imports: React, Lucide-React, Lodash]
  1. Boilerplate Detection: Repetitive comments and generated boilerplate are collapsed while preserving function names and parameter lists.
  2. Syntax Boundary Snapping: Folds snap cleanly between statement blocks so incomplete syntax trees are never generated. 
# Preview how folding compresses your repository snapshot tokencap make --profile balanced

CLI breakdown:

Raw source volume: 38,400 tokens After format-aware folding: 16,200 tokens (58% reduction) Syntax integrity checks: 100% passed

The model receives the exact functional signatures it needs without paying for dozens of lines of repetitive import paths.

Read more at tokencap.vansharora.app