Researchers propose Agent Harness Awareness to improve agent decision-making with real-time telemetry
A new paper on arXiv introduces Agent Harness Awareness, a design meant to bridge the gap between an agent’s decision-making and real-time operational data. The authors argue that while tool descriptions explain what an action can do, they often lack context on whether it’s safe or appropriate at the moment of use. Execution systems already track this via monitors and failure logs, but the model…
Key points
- Agent Harness Awareness shares verified operational state with agents before action, improving decision-making
- ToolRoute benchmark tests show 96.9% reduction in policy regret for GPT-5.6 Sol, Claude Sonnet 5, and Gemini 3.7 Flash
- Live TCP/HTTP tests confirm zero excess operational cost and 100% success rate in fault-injected scenarios
The paper tests the concept with ToolRoute, a benchmark that isolates task semantics while varying operational information. In a 216-decision ablation across GPT-5.6 Sol, Claude Sonnet 5, and Gemini 3.7 Flash, verified tool-health state cut mean policy regret by 96.9%—from 4,252 ms to 131 ms—and boosted single-dispatch completion from 69.4% to 95.8%. A separate 27-decision live test with TCP/HTTP execution and fault injection showed verified state eliminated excess regret entirely (from 8,956 ms to 0 ms) and improved live-action success from 5/9 to 9/9 cases.
Model page: GPT-5.6 Sol →
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