Prime Agent: A Recursive Terminal Coding Agent

Recursive Language Model Architecture

Prime Agent shifts from traditional tool-calling patterns to a Recursive Language Model (RLM) architecture. Instead of dumping raw tool outputs into the context window, the agent maintains a persistent IPython kernel. The model treats its context as a variable and executes Python code to process data, which significantly reduces token consumption. This architecture allows the agent to spawn sub-agents as function calls, enabling parallel task execution where child agents return results to the parent without flooding the primary context.

Self-Improving Harness

The system features a "continual harness" that treats the agent's memory, skills, and system prompts as mutable state. Users can trigger a /refine command to review recent trajectories and bake corrections into the agent's persistent state, ensuring that lessons learned in one session are applied to future tasks. Skills are packaged as executable Python packages rather than static markdown instructions, allowing for the creation of reusable, project-specific workflows.

Operational Capabilities

Prime Agent supports long-running autonomous tasks via a /goal command and heartbeat functionality. Sessions are daemon-backed, allowing them to persist across terminal closures or SSH disconnections. The tool integrates with existing subscriptions for Claude, ChatGPT, and GitHub Copilot, while also supporting local execution via Ollama, LM Studio, or vLLM. It is currently available for macOS and Linux, with the developer noting that it is not a security sandbox and should be used with caution on untrusted repositories.