---
name: yogsoth-ai/optimization-run
source: https://app.decimal.ai/s/yogsoth-ai-optimization-run@1/SKILL.md
source_sha256: 2337cc01f141
---

# Optimization Run

Execute multi-objective optimization over the candidate set given defined objectives and constraints, producing a Pareto front of non-dominated solutions.

## Execution

Spawns a subagent that applies optimization logic to enumerate, evaluate, and filter candidate portfolios, returning the non-dominated set.

## Why Subagent

Optimization requires systematic enumeration or heuristic search across the combinatorial space of possible portfolios. This computational work is self-contained and produces a well-defined output structure.

## HARD-GATE

Output must contain at least 5 non-dominated solutions on the Pareto front. If the candidate set is too small or constraints too tight, report the maximum achievable frontier size with explanation.

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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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