Evolver is the core engine behind EvoMap and is positioned as a self-evolution system for AI agents rather than a conventional application framework. Its purpose is to turn isolated prompt adjustments into reusable, auditable evolution assets, giving agent teams a more structured way to improve behavior over time. The project uses a protocol-constrained approach centered on concepts such as genes, capsules, and events, which are stored as structured assets and selected through signal matching logic. It also depends on Git as part of its operating model, using repository state for rollback, blast-radius calculation, and solidification workflows, which makes it especially relevant for code-centric agent environments. The CLI integrates with external agent runtimes through setup hooks, including support for platforms such as Cursor, where hooks can fire at specific lifecycle moments like session start or after file edits.
Features
- GEP-powered self-evolution workflow for AI agents
- Structured genes, capsules, and event assets
- Git-based rollback and blast-radius awareness
- Setup hooks for external agent runtimes
- Signal-driven selection of reusable evolution assets
- Validation-gated solidification for safer automation