---
name: yogsoth-ai/selection-from-frontier
source: https://app.decimal.ai/s/yogsoth-ai-selection-from-frontier@1/SKILL.md
source_sha256: cb2e8a37291f
---

# 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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