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[ARTICLE · art-126526] src=arxiv.org ↗ pub= topic=ai-agents verified=true sentiment=· neutral

ContractEval: Query-Conditioned Execution Matching for Procedural Instruction Conformance

Researchers introduced CONTRACTEVAL, a diagnostic framework that represents procedural instructions as query-active obligations and matches them against response or trace evidence to detect conformance failures. On a controlled suite of audited procedural contracts, output-only and trace-aware LLM judges missed many injected structural failures, while ContractEval detected and localized all of them under gold expected and observed graphs. The authors state ContractEval is not a compliance guarantee but makes procedural conformance auditable rather than implicit in final-answer quality.

by read1 min views2 publishedSep 11, 2026

arXiv:2609.09458v1 Announce Type: new Abstract: As LLM agents move from answering questions to carrying out procedures, failures can be unwarranted rather than visibly wrong: the final response looks acceptable even though the system skipped the check, branch, dependency, or invariant that made the answer justified. Output-only evaluation sees the answer, and trace-aware judging sees activity, but neither identifies which obligations were active for the query. We introduce CONTRACTEVAL, a diagnostic framework for making those active obligations explicit. It represents procedural instructions as query-active obligations and matches them against response or trace evidence, turning omissions, wrong branches, ordering errors, extra actions, invariant breaches, and output-contract violations into distinct conformance failures. On a controlled suite of audited procedural contracts, output-only and trace-aware LLM judges miss many injected structural failures; under gold expected and observed graphs, ContractEval detects and localizes all of them. LLM-backed extraction preserves much of this signal but remains calibration-sensitive. ContractEval is therefore not a compliance guarantee; it makes procedural conformance auditable rather than implicit in final-answer quality.

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