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SLBench: LLM Agents Fail Skill Logical Constraints at 70% Rate
- Engineer — Learn: If you deploy LLM agents with skill files or tool orchestration, this research quantifies a real risk class: agents routinely violate preconditions and constraints, producing privacy leaks and unsafe config changes. No patch action today, but the SLGuard scaffold approach is worth evaluating if you build skill-guided agents.
- SOC/IR — Skip
- Leader — Learn: Academic evidence that LLM agents fail safety constraints at high rates is useful background for AI governance discussions, but there is no immediate vendor exposure or regulatory trigger here — file for the next AI risk policy review.
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