hermes-agent

Build persistent AI agents by configuring pluggable memory backends that preserve context across sessions and profiles. This framework enables agents to operate across terminals, messaging platforms, and IDEs while retaining state through reusable skills.

Provider-agnostic model routing allows multi-agent workflows to switch between multiple AI providers without hardcoding dependencies. This enables spawning additional agents and managing tools across diverse platforms while maintaining consistent workflow execution.

Configure isolated agent instances by creating independent profiles with separated configs, sessions, and memory. Extend these profiles with plugins, scriptable tool integration, and custom workflows to streamline specific tasks like software development or data analysis.

Yes, autonomous workflows run across terminals, messaging platforms, and IDEs using a multi-platform gateway. This enables teams to deploy persistent agents that execute tasks, adapt through self-improving skills, and manage tools across diverse environments.

Yes, the agent framework supports self-improving through a pluggable skill system that saves effective procedures as reusable skills. These saved skills are reused in future sessions, enabling agents to adapt and streamline workflows over time.

Limitations of building multi-agent systems include the complexity of managing scriptable tool integration and coordinating spawned agents across platforms. Users must configure pluggable memory backends and provider-agnostic routing carefully to avoid context loss or workflow execution failures.