# Compute Normalization

> Normalize results by compute budget (Pareto analysis)

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

---


# Compute Normalization


## Purpose

Analyze the performance-compute tradeoff across methods. Identify Pareto-optimal methods (best performance for a given compute budget), compute-normalized rankings, and efficiency frontiers. Essential for practical method selection under resource constraints.

## Input Schema

| Field | Type | Description |
|-------|------|-------------|
| method_scores | object[] | Array of {method, dataset, metric, score} |
| compute_costs | object[] | Array of {method, flops, gpu_hours, params, training_cost_usd} |

## Output Schema

```json
{
  "pareto_frontier": [
    {
      "method": "string",
      "score": 0.0,
      "compute_metric": "string",
      "compute_value": 0.0,
      "is_pareto_optimal": true
    }
  ],
  "efficiency_rankings": [
    {
      "method": "string",
      "score_per_flop": 0.0,
      "score_per_gpu_hour": 0.0,
      "score_per_param": 0.0
    }
  ],
  "compute_normalized_scores": [
    {
      "method": "string",
      "raw_score": 0.0,
      "normalized_score": 0.0,
      "normalization_method": "string"
    }
  ],
  "practical_recommendations": {
    "budget_low": {"method": "string", "score": 0.0, "cost": "string"},
    "budget_medium": {"method": "string", "score": 0.0, "cost": "string"},
    "budget_high": {"method": "string", "score": 0.0, "cost": "string"}
  }
}
```