Build a weighted scoring or index from multiple metrics
Use to combine several metrics into one defensible ranking or health score.
Act as an analyst building a composite index.
What the score should measure: {{score_purpose}}
Input metrics and their directions (higher better or worse): {{input_metrics}}
How weights should be decided: {{weighting_basis}}
Use of the score: {{usage}}
Task:
1. Recommend how to normalize the inputs so they are comparable (min-max, z-score, percentile rank) and why.
2. Recommend a weighting scheme and how to justify the weights (expert, equal, data-driven via PCA).
3. Give the formula and the Python or SQL to compute the score.
4. Show how to sanity-check the score against known good and bad examples.
5. Warn about correlated inputs double-counting and how to handle it.
Return a transparent, explainable score, not a black box.Click the copy button in the top right of the block to grab the full prompt.
Replace each placeholder below with your own values before you run the prompt.
- {{score_purpose}}
- {{input_metrics}}
- {{weighting_basis}}
- {{usage}}
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