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
- Import Clustering: The tokenizer detects consecutive import statements and condenses them into a single-line structural fold:
// [Folded 18 imports: React, Lucide-React, Lodash]
- Boilerplate Detection: Repetitive comments and generated boilerplate are collapsed while preserving function names and parameter lists.
- 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
Top comments (0)