# Selection From Frontier

> Select the final portfolio from the Pareto front by applying stakeholder preferences and decision criteria.

- Skill: `yogsoth-ai/selection-from-frontier` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add yogsoth-ai/selection-from-frontier`
- Raw SKILL.md: https://api.skillmd.com/api/skills/yogsoth-ai/selection-from-frontier/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Product & Planning
- Author: yogsoth-ai (https://skillmd.com/u/yogsoth-ai)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/yogsoth-ai/selection-from-frontier

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# 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.

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## Available SOPs

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

| SOP | When to use |
| --- | --- |
| spawn-agent | Spawn a customized CC subagent with full MCP tool access. Used by SOPs that declare execution: subagent. |

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