xby-mm1-simulation

Queuing is an unavoidable bottleneck in customer service stacks, API gateways, and database connection pools. The usual workflow either derives steady-state formulas by hand or wires up a SimPy script from scratch, and both paths tend to trip over stability checks, random seeds, or the gap between theory and simulation. xby-mm1-simulation collapses that entire pipeline into a set of conversational tool calls, so a single chat session can take you from parameter validation to a graded accuracy report.

The plugin exposes five tightly-integrated capabilities: validate_config verifies that the arrival-to-service ratio satisfies the stability condition and reports utilization; calculate_metrics computes exact steady-state figures (queue length, waiting time, system time) via closed-form equations; run_simulation drives a reproducible discrete-event model through SimPy; compare_results lines up simulated values against their theoretical counterparts and returns per-metric error, mean absolute error, maximum error, and an accuracy grade; recommend_parameters works in reverse, suggesting arrival rate, service rate, and simulation duration that hit a target utilization level so you stop guessing.

It is aimed at system architects who need a quick sanity check before committing to a capacity plan, at SREs trying to determine whether latency stems from arrival bursts or insufficient service capacity, and at students studying queuing theory who want an instant, script-free sandbox to dial parameters and watch the curves respond without spinning up a separate Python project.