PerspectiveGap: A Benchmark for Multi-Agent Orchestration Prompting

Jul 14, 2026

Researchers have introduced PerspectiveGap, a benchmark designed to evaluate large language models' (LLMs) ability to compose orchestration prompts for multi-agent systems. The benchmark features 110 scenarios across 10 topologies, testing models on role-fragment assignment and free-form prompt writing. Results show that even the best-performing model (GPT-5.5) achieves only a 62% pass rate, while the average combined pass rate across 33 models is 17.2%.

Why it matters: PerspectiveGap highlights a significant and under-explored gap in current LLM capabilities for orchestrating multi-agent systems, providing a new foundation for systematic evaluation and improvement.

Full story at: arXiv Multiagent Systems ↗