Genome Manager

Manages the Genome Evolution Protocol (GEP) genomes - structured success patterns that enable AI agents to self-evolve.

What are Genomes?

Genomes are encoded patterns of successful agent behavior:

• - Task Type: Classification (research, debug, security, etc.)
• Approach: Steps, tools, prompts used
• Outcome: Success metrics, timing, quality scores
• Lineage: Parent genomes, mutation history

When to Use This Skill

Use when:

• - Extracting successful patterns from completed tasks
• Creating reusable genome libraries
• Mutating genomes for optimization
• Tracking genome performance over time
• Preparing genomes for EvoMap sharing

Genome Lifecycle

CODEBLOCK0

Quick Start

CLI Usage

This skill provides a command-line tool for genome management:

CODEBLOCK1

Programmatic Usage

CODEBLOCK2

Genome Schema

CODEBLOCK3

Storage Locations

Default genome storage:

• - memory/genomes/*.json - Local genome library
• INLINECODE1 - Shared across agents
• EvoMap network - Distributed sharing (future)

Mutation Types

Validation Rules

Before saving a genome:

• - [ ] Success rate >= 0.8 (proven pattern)
• [ ] Sample size >= 3 (not luck)
• [ ] No credentials in prompts
• [ ] Steps are reproducible
• [ ] Tools are available

Security

• - Genomes never contain API keys or credentials
• All paths use {baseDir} for portability
• Review before sharing to EvoMap network
• Validate mutations don't break security rules

Integration with EvoAgentX

CODEBLOCK4

Version History

• - 1.0.0: Core genome CRUD operations
• 1.0.1: Added mutation tracking