Score and Prioritize Ideas with an Evaluation Rubric

Select the best initiative by establishing weighted criteria tailored to your context.

Prompt · 3 variables

I need to determine which initiative to prioritize from the list below. Our situation is as follows: {{our situation}}.

Please evaluate and score the ideas in the list against our {{evaluation judgment criteria}}. Before scoring, assign a weight to each criterion and provide a one-line explanation for why that weight was chosen based on our situation.

Present the results in a markdown table. The first column should be the Idea, followed by a column for each criterion score (out of 5), and the last two columns should be "Weighted Score" and "One-line Justification for Score." Below the table, provide a two-sentence rationale for the #1 and #2 ranked ideas, and identify one idea under "Do Not Pursue Now" along with the reason.

Do not assign similar scores across all options; ensure that each criterion has at least one distinct highest and lowest score. Do not invent unverified data such as market size or projected revenue—mark them as "Needs Verification" instead. Do not use trends or subjective preferences as justifications.

After scoring, perform an internal self-check to ensure that the weighted calculations are mathematically correct and that each rationale aligns with our situation. Correct any discrepancies before outputting only the final refined table and analysis.

Idea list: """ {{idea list}} """

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Why it is written this way

Context
I need to determine which initiative to prioritize from the list below. Our situation is as follows: {{our situation}}.
Task
Please evaluate and score the ideas in the list against our {{evaluation judgment criteria}}. Before scoring, assign a weight to each criterion and provide a one-line explanation for why that weight was chosen based on our situation.
Format
Present the results in a markdown table. The first column should be the Idea, followed by a column for each criterion score (out of 5), and the last two columns should be "Weighted Score" and "One-line Justification for Score." Below the table, provide a two-sentence rationale for the #1 and #2 ranked ideas, and identify one idea under "Do Not Pursue Now" along with the reason.
Constraints
Do not assign similar scores across all options; ensure that each criterion has at least one distinct highest and lowest score. Do not invent unverified data such as market size or projected revenue—mark them as "Needs Verification" instead. Do not use trends or subjective preferences as justifications.
Self-check
After scoring, perform an internal self-check to ensure that the weighted calculations are mathematically correct and that each rationale aligns with our situation. Correct any discrepancies before outputting only the final refined table and analysis.
Input
Idea list: """ {{idea list}} """

When asking AI to evaluate ideas by simply posing "Which one is the best?", you get subjective preference rather than sound judgment. Even if plausible-looking justifications are attached, it fails to clarify why that option outperforms the others. This prompt defers final selection and establishes criteria and weighting first.

In the Task paragraph, mandating weights before scoring is the critical sequence. Adding criteria after scoring turns the matrix into a post-hoc justification for an already decided answer. Setting weights based on context first makes it clear what needs adjustment if the final results conflict with reality.

In the Format paragraph, a justification column sits directly next to each score. A table full of bare numbers collapses in meetings when challenged with "Why did this get a 3?" The Constraint instruction "Do not assign similar scores" prevents the model's tendency to give safe 3s and 4s across the board, which effectively turns prioritization into a random draw. Prohibiting fabricated numbers serves the same purpose; one hallucinated market size estimate can derail an entire roadmap.

Finally, the Review instruction forces a verification pass over calculations and internal consistency. Mathematical errors are common in large tables, and a single calculation error can invert priorities. Asking only for the final table avoids clutter and confusion.

Unfamiliar terms? See Aha AI: output-format, hallucination

Compared with a bad example

Common bad example

Which of these looks the best? Give me a recommendation.

(Paste idea list here)

Asking like this usually defaults to picking the first or safest option, accompanied by three generic bullet points. It fails to explain why other options were discarded, making it useless for meeting alignment. It also ignores operational constraints like budget or headcount, often recommending initiatives that are currently impossible to execute.

Variations

When defining criteria together first

When defining criteria together first

Given our situation: {{our situation}}, we need to prioritize which of the following ideas to execute first. Please start by proposing 4 distinct evaluation criteria.

For each criterion, write one sentence explaining "Why this criterion is critical to us right now," and consolidate any overlapping factors. Present only the proposed list of criteria first; once I review and confirm them, you will proceed with the scoring.

Idea list: """ {{idea list}} """

Scoring without agreed-upon criteria usually leads to redoing the entire matrix. Securing team consensus on the criteria first ensures the scoring is completed in a single effective step.

When deciding strictly between two options

When deciding strictly between two options

We must choose strictly one of the two options below. Our situation is as follows: {{our situation}}.

Create a side-by-side comparison table evaluating the two options against our {{evaluation judgment criteria}}. Below the table, list three distinct items under "Trade-offs if choosing Option A" and three under "Trade-offs if choosing Option B." Conclude with a short paragraph explaining under what conditions neither option should be chosen.

Two options: """ {{idea list}} """

When choosing between only two candidates, explicit trade-offs matter more than weighted point totals. Listing what you sacrifice clarifies decision-making immediately.

Model notes

LLMs occasionally make simple addition errors in weighted sums. After receiving the table, asking "Please show the step-by-step arithmetic for the weighted total of each row" provides a reliable verification step.

Related prompts

Last updated 2026-09-02 · Found a mistake? Let us know