You’re Paying a 40% Syntax Tax on Every Single LLM Prompt. Here’s the Fix.

Description and use

Cut token usage and save compute by using TOON and @srtv/toondash to manipulate compressed data streams directly, avoiding costly decode‑encode cycles.

Problem

Engineers feeding large data arrays into LLMs suffer high API token costs and server CPU waste due to JSON syntax noise and costly decode‑encode cycles.

Outcome

Reduced token usage by 30–60% and eliminated costly server CPU cycles, improving operational margins for LLM‑driven pipelines.

Workflow

• 1. Convert data to TOON format with schema header once.
• 2. Use @srtv/toondash functions (filter, map, pick) to mutate TOON stream directly.
• 3. Send mutated TOON stream to LLM without decoding.
• 4. Optionally view or test mutations in the live ToonDash playground.

Evidence

TOON drops your input token footprint by 30% to 60%

Source

Instead of parsing string payloads back into memory-heavy structures just to run basic operations, @srtv/toondash executes mutations directly on the compressed TOON stream.

Source