capability-evolver

Self-improvement for long-running AI agents is enabled by running a protocol-bound mutation loop that analyzes runtime history and produces structured evolution assets. You can start continuous self-improvement with a single command while maintaining safety gating.

AI agent self-repair works by scanning runtime logs and memory for actionable failure signals, then proposing patches and recording evolution steps in an auditable format. This ensures all behavioral improvements are verifiable across sessions.

The Genome Evolution Protocol (GEP) is a standardized framework that ensures auditable, reusable assets across multiple agent runs. It leverages a centralized store with pluggable transports for Genes, Capsules, and EvolutionEvents.

Yes, you can reuse memory and assets across different agent sessions. The system applies to long-running workflows that require structured prompts and utilizes a centralized asset store with pluggable transports for reuse.

To start an agent evolution cycle from the command line, run node index.js from the skill's root directory. This initiates the loop to scan logs and autonomously produce protocol-bound evolution assets.

AI agent prompt mutations are safe and verifiable because the system implements safe command gating alongside memory logging. This protocol-bound approach ensures all autonomous improvements to agent behavior are auditable.