General skillAI and agent development

token-diet

Reduce LLM token use by pruning context, caching prompts, and routing models.

Stars
3
Forks
0
License
MIT
Updated
Updated May 19, 2026

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Project overview

Token-Diet lays out an ordered optimization workflow for LLM applications: prune retrieved context first, reuse cached material, route work by complexity, keep structured state, and compress prose only at the final step. It also defines metrics and guardrails for token use, latency, cost, and quality, while excluding code, schemas, legal text, URLs, and identifiers from linguistic compression.

Repository facts

Primary language
Not detected
License
MIT
Repository updated
May 19, 2026
Default branch
main

Resource types

General skill

Use cases

AI and agent development

Platforms

Claude Code, Codex, and more

Capabilities

MemorySecurity guardrailSummarization

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