ResiMind
Equip AI agents with verified memory, neuro-symbolic self-correction, and symbolic math verification tools.
ResiMind is an open-source neuro-symbolic agent framework that integrates independent domain verification, residual-guided self-correction, and reusable rule memory. When models or tools propose actions, deterministic domain checks ensure only sound steps become committed facts, while failed checks supply precise residual feedback to drive targeted repairs. Checked solutions can be synthesized into independently admitted rule schemas, allowing knowledge to accumulate outside model weights and execute future algebraic tasks with zero model calls. Beyond its core Model Context Protocol (MCP) tools for bounded rational algebra, ResiMind supports domain-specific verifiers for Lean 4 formal proofs, continuous bridge engineering, constrained optimization, and open-ended itinerary planning.