Unverified50% confidenceSolutionExact time
Selective tool loading refers to exposing to the model only the tools actually needed for the current task scenario, which reduces token consumption and decreases model confusion in tool selection.
1
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50%
Confidence
Long-term
Relevance
9/26/2026
First Seen
Sources
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Related Claims
UnverifiedToo many tools cause model selection confusion; the current mainstream direction is to provide a small number of tools and let the model iteratively leverage them on its own, or let the model dynamically design tools based on the task (especially by writing scripts).76% similarUnverifiedThe same model can perform very differently across different tools; the model determines the system's lower bound while the Harness determines the upper bound of agent performance.74% similarUnverifiedIf the requirement is only to reliably call a certain API or tool, a model at the tool-calling level is sufficient and there is no need to use the latest models with orchestration capabilities.74% similarUnverified工具可分为「补偿智能不足的工具」和「随智能增长的工具」，前者会强迫特定写代码顺序且无法随模型变强受益，后者随模型越强越有用73% similarUnverifiedFinding the model and Harness combination that matches one's own workflow is more important than blindly chasing the latest releases.73% similar
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