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Open source · Python

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Prompt writing basics: clear asks, roles, constraints and format

A good prompt tells the model four things: what to do, who it is for, what limits apply and what the answer should look like. Most weak prompts miss one of these. They ask a vague question, leave out the audience, give no length or scope, or never say whether the answer should be a list, a table or JSON. Delimiters such as tags or headings help the model tell your instructions apart from the material it should work on.

These beginner guides explain what prompt engineering is, show how to write a clear prompt with a task, role, constraints and output format, and how to give the model the context it needs. Each comes with before and after examples you can try in any chat model.

[n.01/02]> 4 guides
  1. 01How to Brief an LLM: Context Gaps and Clarifying QuestionsHow to brief an LLM like a new colleague: why it lacks your context and won't ask, the jagged frontier, and a real example of guesses swapped for asks.Beginner · 5 minOct 18, 2026
  2. 02Grounding LLM Answers: Give the Model the Right ContextGround LLM answers in your own text: paste the source, fence it with delimiters, require citations and handle gaps. Real return-policy example.Beginner · 7 minOct 18, 2026
  3. 03How to Write Clear Prompts: Ask, Role, Constraints, FormatWrite prompts the model can't misread: state the ask, set a role, add constraints and fix the format. A real product-description prompt, before and after.Beginner · 6 minOct 18, 2026
  4. 04What Is Prompt Engineering? A Beginner's Guide with ExamplesWhat prompt engineering is, how a prompt works, and the five parts of a good one, with a real before-and-after example and a map of the beginner path.Beginner · 7 minOct 18, 2026
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Related topics

  • Context Engineering6
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  • Hallucinations11
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