I Built a Token Compressor That Cuts LLM Context Size by 60%

Every token you send to an LLM costs money and eats into your context window. If you're stuffing structured data - JSON arrays, database records, API responses - into your prompts, you're probably wasting more than half your tokens on repeated keys, redundant values, and verbose formatting. I built ctx-compressor( https://www.npmjs.com/package/ctx-compressor ) to fix that. The Problem Say you have 100 user records that look like this: { "name": "Adeel Solangi", "language": "Sindhi", "id": "V59OF92YF627HFY0", "bio": "Donec lobortis eleifend condimentum...", "version": 6.1 }, { "name": "Afzal Ghaffar", "language": "Sindhi", "id": "ENTOCR13RSCLZ6KU", "bio": "...", "version": 3.2 } // ... 98 more records ] That JSON blob eats up 19,338 tokens and 63,732 characters when you feed it to a model. Every single object repeats "name", "language", "id", "bio", "version" - that's pure waste. The Solution ctx-compressor analyzes your data, extracts a schema, deduplicates repeated values, and encodes