Prompt Ranking Tool Calculator

Weighted Prompt Quality Score

Each prompt is scored on five criteria: Clarity, Specificity, Structure, Guardrails, and Efficiency. Scores are on a 0–10 scale.

• Clarity: goal, context, and unambiguous instructions.
• Specificity: constraints, acceptance criteria, and concrete details.
• Structure: steps, delimiters, and explicit output formatting.
• Guardrails: do/don’t rules, safe boundaries, and missing-info handling.
• Efficiency: concise prompts that still cover requirements.

Step-by-step workflow

1. Paste two or more prompts you want to compare.
2. Select Auto, Manual, or Hybrid scoring mode.
3. Adjust weights to match your evaluation priorities.
4. Click Rank Prompts to compute scores and grades.
5. Review tips, then refine and re-score for iteration.
6. Download a CSV or PDF snapshot for documentation.

Scoring dimensions aligned with prompt engineering

The calculator evaluates prompts across five criteria that map to practical prompt quality. Clarity measures whether the goal and instructions are fully unambiguous. Specificity captures constraints, assumptions, and acceptance criteria. Structure rewards steps, delimiters, and explicit output formats. Guardrails check do/don’t rules and safe handling for unknowns. Efficiency favors concise prompts that still preserve requirements.

Weighted ranking for different model tasks

Weights let you tune ranking to your use case. For retrieval and tool-use prompts, increase specificity and structure, and add delimiters for inputs. This often improves determinism, reduces format drift, and simplifies downstream parsing in production pipelines. For customer-facing answers, increase guardrails and clarity to reduce risky ambiguity. For extraction or classification, raise structure and specificity to stabilize formats and reduce variance. For brainstorming, keep efficiency higher and reduce guardrails slightly, while still maintaining clarity. The overall score uses a normalized weighted average, so changing one weight never breaks comparability.

Hybrid review for teams and iterations

Auto scoring provides consistent, explainable checks, while manual ratings capture expert judgement that heuristics may miss. Hybrid mode averages both, making it useful for collaborative review where stakeholders disagree on “good.” Teams can store agreed weights, run multiple alternatives, then refine only the lowest criteria shown in the improvement tips. This workflow supports rapid iterations without losing traceability.

Interpreting grades, confidence, and length

Grades translate the overall 0–10 score into quick tiers for decision-making. The confidence value is a heuristic signal based on detectable structure, constraints, and context; it is not model accuracy. Word count is included because prompts that are too short often under-specify, while prompts that are too long can repeat rules and reduce efficiency. Use the ranked table to pick a winner, then inspect the prompt text to confirm intent.

Export-ready audit trail for experiments

CSV export preserves the ranked table for spreadsheets, experiment logs, and dataset versioning. PDF export creates a shareable snapshot for reviews and governance. Together, exports help you compare prompt revisions over time, track what changed, and document why one prompt was selected. This is especially useful when running A/B tests, maintaining production prompts, or aligning teams on quality standards.

FAQs

1) What does the overall score represent?

It is a weighted average of the five criteria scores on a 0–10 scale. Higher scores indicate clearer, more structured, safer, and more efficient prompts for consistent outputs.

2) When should I use Auto, Manual, or Hybrid mode?

Use Auto for quick screening, Manual for expert-only reviews, and Hybrid when you want both repeatable heuristics and human judgement. Hybrid is best for team consensus and iterative refinement.

3) How do weights change the ranking?

Increasing a weight makes that criterion contribute more to the overall score. If structure matters most, raise its weight. If concise prompts matter, raise efficiency. The calculator normalizes by total weight.

4) Why are prompts with more words not always better?

Long prompts can repeat rules, conflict with themselves, and reduce efficiency. Short prompts can under-specify. The tool highlights this tension so you can keep only requirements that change the output.

5) What is the confidence value?

Confidence is a heuristic estimate based on detectable features like constraints, formatting instructions, context, and examples. It helps interpret how reliable the auto signals may be, not how correct a model’s answer will be.

6) How do I share results with my team?

Run the ranking, then download CSV for analysis or PDF for a meeting-ready snapshot. Include your chosen weights and mode so teammates can reproduce the same ranking on their side.