selection-from-frontier
$
npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/selection-from-frontierSelects optimal portfolio from Pareto front using stakeholder preferences
- Solves the problem of choosing between efficient portfolio options
- Depends on Pareto front data and stakeholder preference inputs
- Evaluates frontier solutions against decision criteria and practical constraints
- Returns a justified selection with alternatives and tradeoff explanations
SKILL.md
.github/skills/selection-from-frontierView on GitHub ↗
--- name: selection-from-frontier description: Select the final portfolio from the Pareto front by applying stakeholder preferences and decision criteria. execution: subagent prompt: ./prompt.md input: pareto_front, preferences used-by: portfolio-optimization --- # Selection from Frontier Apply stakeholder preferences, decision criteria, and practical considerations to select a single portfolio from the Pareto front. ## Execution Spawns a subagent that evaluates Pareto front solutions against stated preferences and produces a justified selection with alternatives noted. ## Why Subagent Selection requires integrating quantitative frontier data with qualitative preferences, practical constraints, and judgment calls. This deliberative process benefits from focused reasoning. ## HARD-GATE Output must include the selected portfolio, explicit justification referencing frontier position, and at least one noted alternative with explanation of what would be gained/lost by choosing it instead.
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.