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Pattern: Composite Scoring
Break a judgment into atomic Score questions, normalize each by its top level, and combine them with weights you control in code, as in the resume example's four scored dimensions.
- Category
- Practices & Patterns
- Published by
- TypeSafe AI
- Author
- —
- Added
- 2026-09-20
Tagsofficialpatternsscoreevaluationarchitecture
Highlights
- Resume screening asks four Score questions in one parallel request, each with five levels.
- Normalize each score by dividing by len(criteria) - 1 before weighting.
- Senior IC weights: 40% Python, 10% leadership, 40% design, 10% generalist.
- Engineering manager weights: 15% Python, 40% leadership, 20% design, 25% generalist.
Quickstart
python
py = response.answers["python_depth"].score / 4
lead = response.answers["team_leadership"].score / 4
arch = response.answers["system_design"].score / 4
general = response.answers["generalist"].score / 4
# Senior IC
ic_score = (0.40 * py) + (0.10 * lead) + (0.40 * arch) + (0.10 * general)
# Engineering Manager
em_score = (0.15 * py) + (0.40 * lead) + (0.20 * arch) + (0.25 * general)Watch out
The weights are policy, not model output, so revisit them whenever the role or the cost of a bad hire changes.
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