cross-evolution

To reduce duplication and drift across autonomous skills, you can run an automated audit to discover and propagate best-practice genes, synchronizing patterns into a central registry to keep all skills aligned.

A gene registry for skill lifecycle management is a central repository that tracks best-practice patterns through defined stages (Proposed, Active, Deprecated, Extinct) to govern how skill behaviors evolve and prevent pattern conflicts.

You audit and sync best-practice patterns by executing the audit script, which performs automated discovery and registry synchronization to identify high-value genes and propagate them across multiple platforms.

Cross-evolution is designed for continuous development environments, acting as a living protocol that evolves skill patterns as new constraints are discovered and conflicts are resolved across the library.

The best way to handle conflict resolution during gene transfer is to use the defined detection rules and fitness scoring mechanisms, which evaluate pattern viability before propagating changes across the skill library.

You should not use an automated skill audit when your skill library is static or lacks continuous development, as the living protocol requires ongoing constraint discovery and active lifecycle management to function effectively.