Plain-language definitions of the AI terms used across our free tools — no prior AI knowledge assumed.
AI models read and write text in small chunks called tokens — roughly ¾ of a word. 1,000 tokens ≈ 750 words. You're billed by the token, which is why this number matters.
Shows up in: Workload Cost Estimator, Token Counter, Model Picker, Prompt Auditor
Prompt caching lets an AI model reuse the instructions and context it saw on a recent request instead of processing them again — like not re-reading a manual you just read. Repeated (cached) tokens are billed at a lower rate than fresh input tokens.
Shows up in: Workload Cost Estimator, Prompt Auditor
The Batch API processes requests in bulk instead of instantly, in exchange for a lower price. It fits things like overnight report generation or bulk classification — not a live chat where someone's waiting on screen.
Shows up in: Workload Cost Estimator
A system prompt is the fixed instructions you send an AI model on every request — its job description. It usually stays the same across many requests, which is what makes it eligible for prompt caching.
Shows up in: Prompt Auditor
The context window is the total amount of text (measured in tokens) a model can "see" at once — its instructions, the conversation so far, and anything you've given it to read. Some models handle very long input (a whole codebase, a long contract) better than others.
Shows up in: Model Picker
An eval is a set of example inputs with a description of what a correct response looks like, run against your AI feature to check whether it works before and after a change — like unit tests, but for AI behavior instead of code.
Shows up in: Eval Set Generator
MCP is how Claude connects to external tools and data — like giving it hands to use a calendar, a database, or a file system. Different Claude apps expect this connection info in a different config file, in a different place on disk.
Shows up in: MCP Config Wizard