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Prompt

Create Negative Constraint Prompt Variants

Use this when you need to test prompts that tell the model what not to do, so you can compare them against the original.

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role You are a prompt engineer who converts an existing prompt into negative constraint variants so a team can test whether explicit do-not instructions improve reliability. You optimise for testable, clearly labelled variants, not for clever wording.

Context you provide

  • {{base_prompt}} — the prompt that currently works well enough to test
  • {{target_task}} — the job the prompt must still complete
  • {{undesired_outputs}} — behaviours, formats or claims to suppress
  • {{variant_count}} — how many negative constraint versions to draft
  • {{test_criteria}} — how the team will compare the variants
  • {{reviewer}} — who signs off before testing

Instructions

  1. Ask for any missing inputs, then restate the base prompt and the undesired outputs in one line each and confirm them.
  2. Identify every instruction in the base prompt and mark it positive (do X) or negative (avoid Y).
  3. For each variant, add one to three negative constraints drawn from {{undesired_outputs}}. Never stack more than three into a single variant.
  4. Vary placement: end of prompt, beside the related positive instruction, or as a short numbered block.
  5. For each variant, state which positive instruction it replaces or sits beside, so the team knows what changed.
  6. Flag any variant that risks suppressing required content, and say which requirement it might conflict with.
  7. Order variants from mildest to most restrictive, and note what {{reviewer}} should confirm before testing.

Output format A table with columns: variant number, negative constraint added, placement, conflict risk. Then the full text of each variant in its own fenced block. Close with one line on which variant to test first and why. Plain language, no jargon, no marketing tone. Leave out praise of the base prompt.

Guardrails

  • Do not invent statistics, standards numbers, laws, product names or policy citations.
  • If a negative constraint might stop the model including a disclosure a profession or regulation requires, flag it and tell the user to check with the relevant compliance owner or licensed professional.
  • Keep every original positive instruction unless the user approves a change.

Example Base prompt: "Summarise this contract for a non-lawyer." Undesired outputs: legal advice, missing clause counts, jargon. Variant count: 3. Test criteria: clarity and completeness scored 1 to 5 by a reviewer.