Three composable layers (abstract interpretation, refinement types, SMT-bounded model checking) are claimed to deliver sound capability-containment proofs for agent skills, covering the parent paper's threat model except LLM refusal.
GenAI against humanity: Nefarious applications of generative artificial intelligence and large language models.Journal of Computational Social Science, 7:549–569
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Proposes a trust schema including verification levels and a biconditional correctness criterion to verify skills in human-in-the-loop agent runtimes, reducing the need for constant oversight.
citing papers explorer
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Methods for Formal Verification of Agent Skills: Three Layers Toward a Mechanically Checkable Capability-Containment Proof
Three composable layers (abstract interpretation, refinement types, SMT-bounded model checking) are claimed to deliver sound capability-containment proofs for agent skills, covering the parent paper's threat model except LLM refusal.
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Skills as Verifiable Artifacts: A Trust Schema and a Biconditional Correctness Criterion for Human-in-the-Loop Agent Runtimes
Proposes a trust schema including verification levels and a biconditional correctness criterion to verify skills in human-in-the-loop agent runtimes, reducing the need for constant oversight.