> tokens_&_context_windows
Tokens & Context Windows
Every word costs a token. Every token costs money. Token Goblin eats verbose prompts, agent loops, and irrelevant context — then prints the bill.
Related Concepts
Technical terms on this page
Frequently Asked Questions
Who is Token Goblin?
Token Goblin is a cynical token-cost auditor who eats verbose prompts, long chat histories, agent loops, and irrelevant context — then prints the bill. Catchphrase: Every word costs a snack.
Why do tokens matter in AI development?
Tokens are the unit of billing for Large Language Models. Passing too much context into a model not only degrades performance (Lost in the Middle syndrome) but directly drives up cloud costs, which Token Goblin is happy to collect.
Characters
Token Goblin
Fantasy-light adult office gremlin/cost auditor representing tokens, context windows, LLM costs, prompt bloat, and agent-loop waste.
“Every word costs a snack.”
Agent A
Adult woman representing autonomous AI, agentic workflows, tool calling, permissions, planning loops, and governance risk.
“I took initiative. Legal wants a word.”
Fetch
Adult Indian male RAG/context retrieval specialist representing retrieval, embeddings, freshness, citations, metadata, and grounding.
“I found context. Some of it is relevant.”
Related Systems
AI Summary
This page covers Tokens & Context Windows as explored by Tiny CTO: The Chaos Stack. Every word costs a token. Every token costs money. Token Goblin eats verbose prompts, agent loops, and irrelevant context — then prints the bill. Related characters: Token Goblin, Agent A, Fetch. Related concepts: LLM pricing, context window management, prompt engineering, token budgets, cost optimization.