UniClawBench: A Universal Benchmark for Proactive Agents on Real-World Tasks

The rapid development of large language models and multimodal large language models has accelerated the emergence of proactive agents capable of operating everyday tools and assisting users in real-world environments. However, existing benchmarks struggle to evaluate such agents effectively, as they often rely on sandboxed environments and single-turn evaluation paradigms. Moreover, their scenario-based task taxonomies mix multiple model capabilities within the same task category, making it diff

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ethics.ai (8 July 2026), “UniClawBench: A Universal Benchmark for Proactive Agents on Real-World Tasks,” evidence record 1551, https://ethics.ai/record/1551 (originally published by HuggingFace Daily Papers).

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