Build agents via YAML with Prolog validation and 110 built-in tools

I'm one of the creators of The Edge Agent (TEA). We built this because we needed a way to deploy agents that was verifiable and robust enough for production/edge cases, moving away from loose scripts.The architecture aims to solve critical gaps in deterministic orchestration identified by *Prof. Claudionor Coelho Jr. (Stanford alum, ML/DL Faculty at Santa Clara Univ., and Senior Fellow for AI at Majestic Labs)* during our work on the Kiroku project.*Key Technical Features:** *Neurosymbolic Native:* We integrated Prolog to logically validate LLM outputs. This combines neural flexibility with symbolic reasoning to help mitigate hallucinations.* *YAML + Overlays:* Agents are defined in YAML with overlay support (similar to the Kustomize pattern in Kubernetes), making configs testable and reproducible across environments (Dev/Prod) without code duplication.* *Hybrid Scripting:** *Lua:* Embedded in all binaries (Python, Rust, Wasm) for secure, lightweight logic at the Edge.* *Python:* Full integration for data science workloads.* *Batteries Included:* We implemented 110+ tools based on Sarwar Alam’s Agentic Design Patterns. https://github.com/sarwarbeing-ai/Agentic_Design_Patterns* *Polyglot:* Core written in Rust/Python with Wasm support (runs in browser, Docker, or embedded).* *Observability:* Native hooks for Comet (Opik) to track execution/cost.The goal is to provide a solid engineering foundation for agents. I’d love to hear your feedback on the Prolog integration and the YAML-based architecture.Repo: https://github.com/fabceolin/the_edge_agentDemo (Wasm): https://fabceolin.github.io/the_edge_agent/wasm-demo