Schema Mutation: Measuring Tool Calls After Interface Changes

Tool interfaces change while familiar call patterns remain. Schema Mutation measures whether a call follows the current interface after a migration. The benchmark crosses 12 tool families with 5 mutation types, yielding 60 public tasks. A prompt-only scripted solver achieves 100.0% accuracy (95% Wilson interval 94.0-100.0%). Empty, constant, refusal, echo, and first-tool controls score 0.0% (0.0-6.0%). Exact stale calls fail and receive a separate diagnostic. A simulated population sweep compares pass-through with schema validation. At adherence q=0.5, simulated accuracy is 52.0% (agent-bootstrap interval 50.8-53.2%) under both layers. Validation blocks stale proposals without improving completion. These are scripted and simulated results, not learned-model evaluations. The study supports measurement checks on a synthetic public task set; it does not establish deployment reliability or identify memorization as a cause.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-29
DOI
https://doi.org/10.5281/zenodo.23752422
Primary Topic
Software Engineering Research
Type
preprint
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preprint

Schema Mutation: Measuring Tool Calls After Interface Changes

Pooria Arab
Zenodo (CERN European Organization for Nuclear Research)
Software Engineering Research
preprint

Schema Mutation: Measuring Tool Calls After Interface Changes

Pooria Arab
preprint en

Abstract

Tool interfaces change while familiar call patterns remain. Schema Mutation measures whether a call follows the current interface after a migration. The benchmark crosses 12 tool families with 5 mutation types, yielding 60 public tasks. A prompt-only scripted solver achieves 100.0% accuracy (95% Wilson interval 94.0-100.0%). Empty, constant, refusal, echo, and first-tool controls score 0.0% (0.0-6.0%). Exact stale calls fail and receive a separate diagnostic. A simulated population sweep compares pass-through with schema validation. At adherence q=0.5, simulated accuracy is 52.0% (agent-bootstrap interval 50.8-53.2%) under both layers. Validation blocks stale proposals without improving completion. These are scripted and simulated results, not learned-model evaluations. The study supports measurement checks on a synthetic public task set; it does not establish deployment reliability or identify memorization as a cause.

Zenodo (CERN European Organization for Nuclear Research)
Software Engineering Research
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