Outcome Monitors: Recovery Affordances for Silent Tool Failures
arXiv:2608.19303v1 Announce Type: new Abstract: When a tool call times out, the agent sees the failure and can route around it. A cached error page or negative price can instead arrive in the expected format and be consumed as fact. We introduce Outcome Monitors, which detect violations of outcome contracts mined from task-disjoint traces or derived from public schemas. On a violation, the monitor preserves the result and issues a nonbinding receipt naming the violated property and public recovery tools. In frozen, prespecified evaluations with injected failures, Outcome Monitors raise ToolMaze completion from 10.9% to 28.1% across four models in two provider families and replicate in a third. In tau-bench retail, completion improves by 14.0 and 12.0 points on two tiers. In separate ToolMaze controls, removing the recovery-tool list eliminates the measured gain and restoring it recovers the effect; diagnostic detail and timing produce no detectable differences. Gains concentrate where the fault blocks completion. On a suite transcribed from a published incident taxonomy, detection outside the mined vocabulary falls to 46%, though delivery continues and completion is unchanged. Recovery tools are the active receipt content in these controls; extending detection beyond the contract vocabulary remains open.
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[Submitted on 19 Aug 2026]
Title:Outcome Monitors: Recovery Affordances for Silent Tool Failures
View a PDF of the paper titled Outcome Monitors: Recovery Affordances for Silent Tool Failures, by Sugam Panthi and 1 other authors
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Abstract:When a tool call times out, the agent sees the failure and can route around it. A cached error page or negative price can instead arrive in the expected format and be consumed as fact. We introduce Outcome Monitors, which detect violations of outcome contracts mined from task-disjoint traces or derived from public schemas. On a violation, the monitor preserves the result and issues a nonbinding receipt naming the violated property and public recovery tools. In frozen, prespecified evaluations with injected failures, Outcome Monitors raise ToolMaze completion from 10.9% to 28.1% across four models in two provider families and replicate in a third. In tau-bench retail, completion improves by 14.0 and 12.0 points on two tiers. In separate ToolMaze controls, removing the recovery-tool list eliminates the measured gain and restoring it recovers the effect; diagnostic detail and timing produce no detectable differences. Gains concentrate where the fault blocks completion. On a suite transcribed from a published incident taxonomy, detection outside the mined vocabulary falls to 46%, though delivery continues and completion is unchanged. Recovery tools are the active receipt content in these controls; extending detection beyond the contract vocabulary remains open.
Comments: 16 pages (9 main + 7 pages supplementary material), 3 figures
Subjects:
Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Software Engineering (cs.SE)
Cite as: arXiv:2608.19303 [cs.AI]
(or arXiv:2608.19303v1 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2608.19303
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Sugam Panthi [view email] [v1] Wed, 19 Aug 2026 17:35:30 UTC (58 KB)
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