# Screening Then Scoring

> First eliminate non-qualifying candidates with non-compensatory rules, then score survivors with full MCDA methods.

- Skill: `yogsoth-ai/screening-then-scoring` (Agent Skill)
- Install (CLI): `npx skillmds@latest add yogsoth-ai/screening-then-scoring`
- Raw SKILL.md: https://api.skillmd.com/api/skills/yogsoth-ai/screening-then-scoring/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: yogsoth-ai (https://skillmd.com/u/yogsoth-ai)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/yogsoth-ai/screening-then-scoring

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# Screening Then Scoring

First eliminate non-qualifying alternatives using non-compensatory rules, then perform fine-grained scoring and ranking of survivors. Suitable for scenarios with large candidate sets or hard constraints.

## Stages

1. **Threshold Setting** — Set minimum thresholds for critical criteria
2. **Conjunctive Filtering** — Eliminate non-qualifying alternatives based on thresholds
3. **Dominance Check** — Identify dominated alternatives among survivors (optional further reduction)
4. **Full Scoring** — Execute scoring-matrix-construction workflow on survivors

## Available SOPs

- threshold-setting — Set criteria thresholds
- conjunctive-filter — Conjunctive rule elimination
- dominance-check — Dominance relationship check
- criterion-definition — Fine-grained scoring criteria (Stage 4)
- weight-elicitation-sop — Weight computation (Stage 4)
- alternative-scoring — Alternative scoring (Stage 4)
- normalization — Normalization (Stage 4)
- scoring-synthesis — Comprehensive recommendation (Stage 4)

## Execution Guidance

- Stages 1-3 are the screening phase, rapidly reducing the candidate set
- Screening criteria should focus on hard constraints (safety, compliance, budget caps, etc.)
- Survivor count should ideally be 3-8 before entering fine-grained scoring
- If too few survivors after screening (<3), consider relaxing thresholds
- If too many survivors (>10), add screening criteria or tighten thresholds
- Stage 4 reuses the complete scoring-matrix-construction tactic workflow

## Minimum Yield

Elimination rationale + survivor ranking

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## Available SOPs

Optional, no fixed order; the final leaf is always a sop.

| SOP | When to use |
| --- | --- |
| alternative-scoring | Score each candidate alternative against all criteria to produce a score matrix. |
| conjunctive-filter | Apply conjunctive screening rules to eliminate candidates that fail any threshold. |
| criterion-definition | Extract evaluation criteria from research goals and candidate alternatives. |
| dominance-check | Identify dominated and non-dominated alternatives in a score matrix using Pareto dominance. |
| normalization | Normalize a score matrix using a specified method to make scores comparable across criteria. |
| scoring-synthesis | Synthesize score matrix, rankings, and sensitivity analysis into a final recommendation. |
| threshold-setting | Define minimum acceptable thresholds for each criterion based on context and constraints. |
| weight-elicitation-sop | Compute criteria weights using a specified elicitation method (AHP, Swing, BWM, MACBETH, or Simos). |

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