fusion-engine

A risk-aware decision engine computes weighted scores from memory relevance, command history, user signals, and system health to evaluate risk before auto-running a bash command. It outputs a final score, a recommended decision, and a structured reasoning log.

A fusion engine for tool invocation combines memory relevance, command history, user signals, and system health into a single decision context. It ingests historical logs, computes weighted scores, and outputs a final score with a recommended decision and explainable reasoning.

Yes, you can use a weighted scoring system to guide tool dispatch in Claude or Codex workflows. It integrates directly into these environments to evaluate system health and user signals, providing risk-aware decisions for tool invocation scenarios.

To get an explainable reasoning log for automated tool decisions, implement a fusion engine that ingests historical logs and computes weighted scores. It outputs a structured reasoning log alongside a final score and recommended decision for transparency.

Yes, you need psutil to monitor systems health for runtime decision engines. The fusion engine depends on psutil to gather system status metrics, which are combined with user signals and command history to compute risk-aware tool invocation scores.

The best way to combine memory relevance and command history for AI automation is using a fusion engine that applies weighted multi-source scoring. It ingests these signals alongside system health and user inputs to output a reliable decision context and a final score.