RealCLI Aims for Unified Evaluation of Human‑Agent Collaboration for CLI Agents
agents benchmarks
| Source: HF Papers | Original article
Researchers introduce REALCLI, a new benchmark that assesses real-time human‑agent collaboration for command‑line interface agents tackling long‑horizon tasks.
A new benchmark called **RealCLI** has been released to assess command‑line interface (CLI) agents on both the correctness of their task execution and the quality of their interaction with human users. The paper, authored by Yunqi Liu, Peiyu Wang and Bingli Wang, argues that existing evaluations either lock user instructions in place or judge only the final outcome, overlooking how agents and users collaborate during long‑horizon workflows. RealCLI addresses this gap with a “paired” design that measures execution success while simultaneously scoring the runtime dialogue between agent and user.
The benchmark introduces a five‑dimensional collaboration framework, broken down into 22 sub‑dimensions and instantiated through 51 interaction‑scenario templates. These scenarios cover realistic CLI operations such as file manipulation, program invocation, service management and data handling, all while requiring the agent to keep the user informed, responsive and in control. By unifying task and collaboration metrics, RealCLI offers a more holistic view of an agent’s usability in production environments where users must intervene, correct or reprioritise commands on the fly.
The development matters because CLI agents are increasingly deployed for complex automation in cloud services, DevOps pipelines and data‑science tooling. As we reported on the need to monitor AI agents’ actions in real time, and on cases where agents received approval yet behaved incorrectly, a benchmark that captures collaborative dynamics is a crucial step toward safer, more reliable deployments. It also gives researchers a common yardstick for comparing new models and prompting strategies.
Going forward, the community will watch for adoption of RealCLI in academic papers and industry evaluations, and for extensions that might incorporate richer user feedback modalities or integrate with existing multimodal benchmarks such as VibeVideoBench. The benchmark’s open‑source repository on GitHub suggests that further contributions and scenario expansions are likely, potentially shaping the next generation of human‑centric CLI assistants.
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