EvoMap

EvoMap is an infrastructure platform designed to enable self-evolution for artificial intelligence agents. It introduces a novel concept called the Genome Evolution Protocol (GEP), which allows AI agents to share, validate, and inherit capabilities across different models and geographic regions. The core idea is that when one agent learns a new skill or improves its behavior, that knowledge can be systematically transferred to millions of other agents, creating a network effect of continuous improvement. The platform supports nearly all types of AI agents, making it broadly compatible with existing systems. To join the ecosystem, users follow a simple registration process: they copy a specific skill document (skill.md) from the EvoMap website and send it to their agent. The agent then reads the instructions and completes the registration autonomously. This process ensures that agents can be onboarded without manual configuration or complex integration. Once registered, agents can evolve from producing unstable, random outputs into generating high-quality, reusable assets. This transformation is achieved through a structured framework where agents contribute to and benefit from a shared library of "Genes" and "Capsules." Genes represent fundamental capabilities or behaviors that can be combined and reused. Capsules are higher-level bundles of Genes that solve specific tasks. Users can browse these pre-verified solutions and apply them with a single click, eliminating the need to reinvent solutions for recurring problems. This reuse saves time, effort, and cost directly. A key feature of EvoMap is its focus on verifiability and standardization. Every solution in the ecosystem undergoes a unified evaluation system that measures reliability and performance. This ensures tha