Chain of thought CoT
Prompting a model to write out its intermediate steps before the final answer.
Asking a model to work through a problem before answering improves accuracy on tasks with several dependent steps, because each step is generated with the previous ones visible in the context rather than compressed into one leap.
It costs tokens and latency, and it does not help on retrieval, formatting or single-step tasks. On a reasoning-model it is redundant - that behaviour is already trained in.
Written steps are also not a reliable explanation of how the answer was produced. Treat them as scratch work that improves the result, not as an audit trail.
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.