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zenigame-analyze-genome-archive

Analyze Alpha Factory GA genome archives and generate multi-section performance reports.

Updated Apr 17, 2026
Search Tags:#performance#metrics#archive#analyze#ga#genome
One-click install
npx skills add https://github.com/kent013/zenigame-fx --skill zenigame-analyze-genome-archive
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: zenigame-analyze-genome-archive
Source: https://github.com/kent013/zenigame-fx/tree/main/.claude/skills/zenigame-analyze-genome-archive
Command: npx skills add https://github.com/kent013/zenigame-fx --skill zenigame-analyze-genome-archive

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Analyzes Alpha Factory GA genome archives to identify actionable improvements in GA runs and outputs structured insights for optimization.

Core Features & Use Cases

  • Deep analysis of GA genome archives to uncover performance gaps and optimization opportunities.
  • Generates a multi-section report detailing dashboards, statistics, evolution effects, cost structure, diversity, and parameter distributions.
  • Use Case: Evaluate recent GA runs to guide strategy tweaks and primitive selection, with options to focus on new primitives.

Quick Start

Run the genome archive analysis with uv run python scripts/trading/analyze_genome_archive.py for the latest GA run (you may specify a run_id to target a specific one).

Frequently Asked Questions about zenigame-analyze-genome-archive

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze GA genome archives to improve my trading strategy runs?▼

To analyze GA genome archives, run the analysis script via uv to evaluate historical Alpha Factory GA executions. This generates a multi-section report detailing dashboards, statistics, evolution effects, and parameter distributions to guide strategy tweaks.

What metrics are evaluated when analyzing a GA genome archive?▼

Analyzing a GA genome archive evaluates performance insights across metrics such as B-Sharpe, C-PASS, cost structure, diversity, and parameter distributions. The multi-section report provides unit-aware reporting to identify optimization opportunities.

Can I target a specific historical GA run for archive analysis?▼

Yes, you can target a specific historical GA run by specifying an optional run_id. This allows you to focus the genome archive analysis on a particular execution rather than defaulting to the latest run.

Do I need uv installed to run the genome archive analysis script?▼

Yes, you need uv installed to run the genome archive analysis script. The process requires invoking the uv runner with the Python script located at scripts/trading/analyze_genome_archive.py to execute the analysis.

What is the best way to compare multiple GA runs for performance gaps?▼

The best way to compare GA runs is using genome archive analysis to extract performance insights across metrics like B-Sharpe and C-PASS. The multi-section report uncovers performance gaps and optimization opportunities across historical executions.

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