Unverified50% confidenceSolutionExact time
The high-frequency reason a Skill fails to match a task is that the description is not written in enough detail; the name itself carries limited information, and the model cannot judge the functional boundary from the name alone.
1
Sources
50%
Confidence
Long-term
Relevance
10/21/2026
First Seen
Sources
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Related Claims
VerifiedWhen a skill description is so detailed that it contains all the information needed to complete a task, the model will skip the skill-calling step.79% similarUnverified语义层与执行层的割裂是业务Skill失效的根本原因，语义层描述模糊会导致Agent从不调用或错误场景频繁触发该Skill76% similarUnverifiedWord count errors are difficult to eliminate entirely through prompt improvements, because the problem lies in a fundamental mismatch between the nature of the task and the model's working mechanism, not in whether the wording is clear75% similarVerifiedReasoning intensity and task complexity are not linearly correlated; for tasks with clear structure, the Low or Medium level is often already sufficient to reach the upper limit of the model's capabilities.74% similarUnverifiedThe cost of "files as skills" is that skills cannot contain complex runtime logic, and execution capability is limited by the model's own reasoning and tool-calling abilities.74% similar
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