skillfuzz-44147318·1 events·first seen Aliases: SkillFuzz
SkillFuzz is a new testing framework that treats skill composition in LLM-based agent marketplaces as a fuzzing problem, using contract-guided Monte Carlo Tree Search to discover 'implicit intents' — unintended behaviors that emerge only when multiple individually-benign skills are co-activated. The approach is execution-free at audit time, relying on structured skill contracts and a skill-free planning baseline as a differential oracle. Across benchmark workloads, it discovers over 1,000 distinct implicit intents within a fixed query budget and confirms more than 80% of highest-risk flagged compositions during execution-time validation.