Qualification: Do More Agents Help? Controlled and Protocol-Aligned Evaluation of LLM Agent Workflows
Matched comparisons require more than common outcome labels. Fu and colleagues ask whether reorganizing a single-agent workflow into a multi-agent workflow changes accuracy and cost. Their BenchAgent design holds the base model, benchmark loader, tool interface, answer contract, evaluator, and accounting substrate constant. It also records agent identifiers and stage-level traces under one execution system. The measured difference can therefore be assigned more narrowly to workflow organization. This evidence qualifies Kaal's strict matched-analysis requirement. The source binds the compared workflows to the same base model and benchmark inputs. It also keeps the execution and evaluation surfaces common and preserves the identifiers needed to reconstruct agent activity. These controls prevent a comparison from treating changes in model, task delivery, tool access, or logging as if they were effects of agent organization. The qualification remains limited. BenchAgent compares a single-agent anchor with workflows that necessarily contain different numbers and roles of agents. It does not preserve the identity of one agent across every condition, reproduce Kaal's registered analysis, or test his cohort. The source supports the narrower methodological proposition: an agent-workflow comparison becomes interpretable only when task, model, execution, and attribution fields remain bound across conditions.
research-methodsscholarly-growth-coveragescholarly-literatureagent-evaluationmatched-analysisexperimental-designworkflow-attribution