Metacog adds nervous system to AI agents

Metacog solves the "Passive Librarian Problem" by pushing operational awareness to the agent instead of waiting for a retrieval query it doesn't know it needs.

• –Five distinct "senses" detect anomalies like token velocity spikes and consecutive similar errors.
• –A unique reinforcement model rewards the absence of failure, preventing the pruning of effective rules.
• –Nociceptive interrupts force agents to state operating assumptions when stuck in loops.
• –Minimal token overhead ensures the system remains silent and cost-effective until a deviation occurs.
• –Per-project scoping allows for learning codebase-specific patterns without global behavioral contamination.