Signals: finding the most informative agent traces without LLM judges [R]

Short summary

Signals is a taxonomy-based method for identifying informative agent traces without expensive LLM evaluation. Signal-based sampling achieved 82% informativeness versus 54% for random sampling, delivering 1.52x efficiency. Implementation is available in open-source plano project; paper and authors available for technical discussion.

• •Signal-based trace filtering achieves 82% informativeness vs 54% random sampling, 1.52x efficiency gain
• •Lightweight taxonomy of interaction, execution, and environment patterns; no GPU required
• •Open-source implementation (plano) and arXiv paper available; authors engaging on technical details

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