Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
Improved description explaining GEP genome lifecycle and collective evolution
What This Skill Does
Genome Manager handles the full lifecycle of GEP (Genome Evolution Protocol) genomes: structured records of successful agent behavior encoding task steps, tools, prompts, and outcome metrics. It provides CLI and programmatic interfaces for creating, mutating, validating, and retrieving genomes. Mutation types include evolution, adaptation, specialization, and crossover to refine patterns over time.
Fills the gap where no tooling existed for GEP genome management, giving agents a structured persistence layer for successful behavior patterns rather than rediscovering them each run.
When to use it
- Encoding a completed research workflow as a reusable genome
- Tracking mutation history across genome generations
- Validating genome quality before sharing to the EvoMap network
- Creating domain-specific genome variants from a general-purpose parent
- Building a shared genome library accessible across multiple agents
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Save this successful research approach as a reusable genome with a 0.95 success rate across 50 samples
- 1Run genome_manager.py create with task-type, steps, tools, success-rate, and sample-size flags
- 2Run genome_manager.py validate on the new genome to confirm it meets quality thresholds
- 3Run genome_manager.py list to confirm the genome appears in local storage
- 4Run genome_manager.py mutate with type evolution to create an optimized variant
Validated genome stored in memory/genomes/ with lineage tracking and a mutated evolution copy ready for further testing