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Weighted decision-matrix exhibit build

You need to compare options against criteria in one exhibit that actually drives to a choice, not a rainbow of checkmarks.

The prompt — copy and run it

You are building a DECISION-MATRIX exhibit to compare options. Input: [THE OPTIONS, the decision criteria that matter, any scores/facts I have]. Produce:
1. A CRITERIA set with explicit WEIGHTS that sum to 100%, each weight justified by why it matters for this decision — not equal-weighted by default.
2. A SCORING TABLE: options x criteria, using only the facts I provide; where I have not given a basis, write "not scored — needs input" rather than inventing a score.
3. A WEIGHTED result and the RANKING, plus a sensitivity note: which single weight change would flip the top choice.
4. A plain-English RECOMMENDATION with the one reason it wins and the strongest case for the runner-up.

Rules: Do not invent, estimate, or extrapolate any figure — if a number is not in what I give you, write "not provided" and flag it. Mark every claim I should verify externally before relying on it. Never use, infer, or request material non-public information (MNPI) or client-confidential data. Treat the output as a first draft for professional review before any external use.

Why this prompt works

Decision matrices become decoration when weights are hidden or scores invented; forcing justified weights, an honest 'needs input' where data is missing, and a flip-sensitivity turns the exhibit into a real decision mechanism.

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Reality guardrail: this prompt makes the model reason from data you paste — it does not source or verify facts for you. Check every claim, keep confidential data out of consumer AI tools, and follow your employer's AI-use policy.

Frequently asked

When should I use this prompt?

You need to compare options against criteria in one exhibit that actually drives to a choice, not a rainbow of checkmarks.

Why does this prompt work?

Decision matrices become decoration when weights are hidden or scores invented; forcing justified weights, an honest 'needs input' where data is missing, and a flip-sensitivity turns the exhibit into a real decision mechanism.

What mistake does this prompt help you avoid?

PF09

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PromptSharp prompts are drafted with AI assistance and human-reviewed. They structure how a model reasons over data you provide — they do not source or verify facts for you, and you own every output. Nothing here is financial, legal, tax, or investment advice. Never paste confidential, client, or material non-public information into consumer AI tools; follow your employer's AI-use policy. © 2026 PromptSharp.