AI & Agent WorkflowsSoftware EngineeringOpen accessPublished 3 Oct 2026
Score a multi-model routing policy on cost versus quality using the two
metrics that actually decide selective intelligence: cost per successful
completion (not cost per token) and a per-node quality parity threshold with
domain-specific failure weights. Wraps a NodeInvocation log, computes
cost-per-success and p95 latency per node, and evaluates a candidate model
against a per-node evaluation set drawn from production data. Use to justify
or recalibrate a routing decision AFTER you have run traffic. NOT for deciding
routing a priori (that is model-routing-selector), NOT for generic benchmarks
(MMLU/HumanEval do not capture your alert taxonomy), NOT for latency/KV
budgeti…