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Prompt checklist (copy-paste) to get better outputs

A practical checklist you can paste into any prompt to reduce ambiguity and improve structure.

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What to include

  • Goal: what success looks like (1 sentence).
  • Context: what the model must know (data, constraints, definitions).
  • Output format: bullets / JSON / table / steps.
  • Edge cases + what to do when info is missing.
  • Quality bar: what to avoid + acceptance criteria.

Common mistakes

  • Asking for 'the best' without criteria (the model guesses).
  • No examples of the output format (inconsistent structure).
  • Mixing goals (e.g., 'be concise' + 'be exhaustive').

Before → after: the same request, rewritten

  • Before: "Write something about our new feature."
  • After: "Write a 120-word announcement of [feature] for existing customers. Goal: get them to try it this week. Include one concrete benefit and a link placeholder. Tone: plain, no hype. Output: a subject line and the body."
  • What changed: the goal, the audience, the length, the tone and the output are now stated, so the model has nothing important left to guess.

How to use it in three steps

  • Write the goal first, in one sentence. If you cannot, the prompt is not ready to send.
  • Fill in only the context lines that would change the answer, and delete the rest of the skeleton.
  • Run it and compare the answer with your quality bar. Fix the line that caused each miss (vague answer: goal or context; wrong shape: output format; too generic: constraints) and run again.
  • Promptea can score the prompt from 0 to 100 on six criteria and list what to fix, so you do not have to find the weak line by trial and error.

Templates

Universal prompt skeleton

Task: [what you want]

Goal (success looks like):
- [1 sentence]

Context:
- Audience: [who]
- Constraints: [time/budget/stack/forbidden things]
- Inputs: [paste data or describe]
- Definitions: [terms]

Output format:
- [exact format: bullets / JSON schema / table columns]

Quality bar:
- Must include: [items]
- Must avoid: [items]
If missing info, ask up to 3 questions before answering.
Opens the analyzer with the prompt prefilled.
Open in Promptea

FAQ

Do I need long prompts?
No. The goal is clarity, not length. Add only the context that changes the answer.
How do I get consistent formatting?
Specify the exact format and include a tiny example if needed.
Which line should I fix when the answer is off?
Match the symptom to the line: vague or off-topic means the goal or context is weak; the wrong shape means the output format is missing; generic or too long means the constraints are loose; invented details mean you should add 'use only the data I provide'.
Is the same checklist right for every model?
The structure is model-independent: goal, context, format, edge cases, quality bar. What changes between models is how strict to be about format and how to handle examples or search; see the per-model pages.