Surprise! 🎉 I’m releasing a new data utility library today.
Meet @srtv/toondash — a clean, declarative, and framework-agnostic set of utilities built to query, slice, and transform data payloads directly on the wire without full object inflation overhead.
The Problem
When you pass large structural datasets (like user lists, analytics logs, or product catalogues) into an LLM context window, standard JSON introduces an incredible amount of syntactic noise. You waste up to 40% of your prompt token budget repeating dictionary keys, quotes, and braces.
Newer text formats like Token-Oriented Object Notation (TOON) fix this by stripping punctuation and declaring schemas once, slashing your token footprints by 40% to 70%.
