alternative-scoring
$
npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/alternative-scoringScores alternatives against criteria to generate a detailed scoring matrix
- Evaluates candidate alternatives using defined criteria and weights
- Relies on input from the user for candidates, criteria, and weights
- Analyzes each alternative independently to ensure consistent scoring
- Produces a matrix with scores and rationales for each alternative-criterion pair
SKILL.md
.github/skills/alternative-scoringView on GitHub ↗
--- name: alternative-scoring description: Score each candidate alternative against all criteria to produce a score matrix. execution: subagent prompt: ./prompt.md input: candidates (string[]), criteria (string[]), weights (number[]) used-by: multi-criteria-scoring --- # Alternative Scoring Score candidate alternatives against each criterion to produce a complete scoring matrix (alternatives x criteria). ## Execution Subagent receives candidate list, criteria definitions, and weight vector, scores each alternative on each criterion, and outputs the scoring matrix. ## Why Subagent Scoring requires analyzing each alternative individually, involves significant workload and needs consistent scoring standards; independent execution prevents score drift. ## HARD-GATE Scoring matrix must have no empty values, each score must include a brief rationale (1 sentence), and quantitative criteria must use actual data.
More from yogsoth-ai/de-anthropocentric-research-engine
- abductive-hypothesis-generationStrategy: 面对异常的最佳解释推理
- ablation-brainstormRemove components one by one, observe system changes to reveal hidden dependencies and generate ideas from structural gaps.
- ablation-component-mappingMap system architecture to ablatable units for ablation studies
- ablation-designDesign ablation studies to isolate component contributions in ML systems
- ablation-executionRemove components one by one from a system, record the response/impact of each removal.
- abp-vulnerability-classificationClassify assumptions on 2 axes — load-bearing (how much conclusion depends on it) × vulnerable (how likely to be false). Focuses attention on High-Load × High-Vulnerable quadrant.
- abstraction-extractionExtract abstract principles from concrete domain cases. Strips domain-specific details to reveal transferable mechanisms.
- abstraction-ladderPerform bisociation at multiple abstraction levels
- abstraction-ladderingMove between concrete and abstract framings — 3 levels up (Why?) and 3 levels down (How?) to find the most productive research level.
- abstraction-to-designAbstract biological principle to design principle. Bridge from biology to engineering.