Tokalator: A Context Engineering Toolkit for AI Coding Assistants

Vahid Faraji · arXiv:2604.08290 · April 2026

https://arxiv.org/abs/2604.08290

Summary

Tokalator is an open-source context engineering toolkit for AI coding assistants. It makes token usage explicit, measurable, and optimisable so teams can control cost and quality across coding workflows.

Contribution

• Token-aware context management — real-time token budgeting and tab relevance scoring
• Output-quality models — Cobb-Douglas style models relating context quality to output quality
• Caching break-even analysis — when caching pays off across 17 supported LLMs
• Shipped as a VS Code extension (500+ installs) and a web platform
• MIT licensed, open source

Adoption

• 500+ VS Code extension installs
• 17 LLM models supported for token economics
• 58 wiki articles on context engineering
• Secured a $40K Perplexity AI business fellowship grant

References & Links

• arXiv: https://arxiv.org/abs/2604.08290
• Website: https://tokalator.wiki
• VS Code Marketplace: vfaraji89.tokalator
• GitHub: github.com/vfaraji89/tokalator
• Author: Vahid Faraji — Applied AI Specialist