Raven composes model–harness pairs into a multi-agent ecosystem and leads planning, four specialist domains, and skill reuse over Claude Code and other baselines
Raven is an open-source multi-agent ecosystem that treats each executable model–harness pair as a composable unit of intelligence: a Host Agent decomposes goals into a directed acyclic graph and matches subtasks to registered specialists, HarnessBank-style evolution, EverOS memory, and Skill Forge reuse experience across tasks, and the paper gives sufficient conditions under which composition expands reliable task coverage under a shared resource budget, reporting gains over Claude Code, Hermes Agent, OpenClaw and other baselines on the MAOB planning benchmark, four native specialist domains, frozen-backbone harness evolution, and fixed skill-library reuse.