Evolver

Auditable AI agent self-improvement works by analyzing runtime history and applying a protocol-constrained framework to generate tracked evolution artifacts. This process turns scattered optimizations into reusable assets like Genes and Capsules.

The Genome Evolution Protocol works by analyzing agent runtime history to provide auto-log analysis and self-repair guidance. It uses EvolutionEvents to track changes and outcomes, ensuring safe and provenance-enforced evolution.

Yes, you can use this framework for large team agent networks because it scales across EvoMap networks and maintains auditable evolution trails. It is designed to harden agent loops and improve prompt governance across teams.

Yes, you need plug-in memory integration requirements like memory graphs to run automated agent evolution. The framework enforces safety and provenance by utilizing GEP assets and memory graphs during the evolution cycle.

The best way to start an automated agent evolution cycle is to run node index.js. This initiates the process, applying the protocol-constrained framework to inspect runtime history and generate auditable evolution artifacts.

Yes, the agent evolution framework supports optional GitHub reporting. It enforces safety and provenance while using GEP assets, memory graphs, and this optional reporting to maintain auditable self-improvement in real-world settings.