Token
The unit a model reads and writes - roughly a word fragment. Pricing, context limits and speed are all measured in tokens.
Models do not see characters or words. Text is split into tokens, which are common character sequences learned from the training data. In English a token averages about four characters, so a hundred words is roughly 130 to 150 tokens. Code, rare names and non-English text tokenise less efficiently, sometimes at more than one token per character.
This matters for three reasons: your context-window is measured in tokens, you are billed per token in and out, and tasks that depend on individual characters - counting letters, reversing a string, rhyming - are hard for a model that never sees the characters.
Tagged
Where this comes up
Prompts, configs and tutorials in the library that touch this term.
- GuideUniversal
Working with long documents and code
Why long sessions drift, what a large context window actually buys you, and how to keep a model on task across a big input.
- GuideUniversal
Giving a model a role and constraints
How naming the audience, the format and the exclusions turns unpredictable answers into repeatable ones.
No-padding everyday default
The one to set if you set only one. Answer first, nothing before it, nothing after it, and no offer to help further.
Tested on Claude Sonnet · May 2026
- CheatsheetUniversal
Forcing an output format that holds
The phrasings that actually constrain output, and the ones people use that do not. Tested by asking for the same thing twenty times and counting the…
Tested on Claude Sonnet · May 2026
- PromptUniversal
Extract structured data as JSON
A strict extraction prompt that returns valid JSON only, with nulls for missing fields instead of invented values.
- PromptMidjourneyStable Diffusion
Image prompt skeleton
A fill-in structure for image models that keeps subject, environment, light, lens and style in the order the models weight them.