Assessment guide

Token compression for AI assessment

AI-generated assessments need to reference curriculum standards, learning objectives, and existing question banks. Compression keeps only the standards relevant to the assessment being generated.

By Arjun Shah - Creator of SuperCompress - Updated 2026-07-03

Assessment generation costs

Generating an exam with an LLM might send: the curriculum framework (2,000-5,000 tokens), learning objectives (500-1,000 tokens), question format guidelines (200-500 tokens), and sample questions (500-1,000 tokens). Compression reduces this by keeping only the objectives relevant to the specific exam being built.

Frequently asked questions

Does compression preserve assessment standards?

Yes. Only irrelevant standards are removed. The learning objectives being assessed are preserved.

Can I generate multiple assessments efficiently?

Yes. Compress the curriculum once against each assessment topic for batch generation.

Build with less context

Put compression in front of your next LLM call.

Use the hosted API or run SuperCompress locally. Keep the evidence, drop the token waste, and measure the savings before it reaches your model.

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