Handoff Debt: The Rediscovery Cost When Coding Agents Take Over Interrupted Tasks
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arXiv:2606.02875v1 Announce Type: new Abstract: Coding-agent benchmarks evaluate whether a single uninterrupted agent can resolve a repository issue. Real software work is messier: tasks are interrupted, reassigned, reviewed, and resumed from partial states left by another agent or engineer. We study this missing dimension through \emph{handoff debt}: the rediscovery cost imposed when a predecessor's work is opaque or incomplete. Our takeover protocol interrupts a coding agent at deterministic h
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✦ AI Summary· Claude Sonnet
Computer Science > Artificial Intelligence
[Submitted on 1 Jun 2026]
Handoff Debt: The Rediscovery Cost When Coding Agents Take Over Interrupted Tasks
Dipesh KC, Anjila Budathoki
Coding-agent benchmarks evaluate whether a single uninterrupted agent can resolve a repository issue. Real software work is messier: tasks are interrupted, reassigned, reviewed, and resumed from partial states left by another agent or engineer. We study this missing dimension through \emph{handoff debt}: the rediscovery cost imposed when a predecessor's work is opaque or incomplete. Our takeover protocol interrupts a coding agent at deterministic handoff points, freezes the repository, and evaluates successor agents under four handoff views: repository state only, raw trace, summary notes, and structured notes. Across 75 source tasks, the protocol generates 181 handoff-point tasks and 724 takeover runs per successor model. Across three successor models, context-bearing handoffs reduce median agent events by 20--59\% and cumulative prompt tokens by 42--63\% relative to repository-only takeover. Solved-rate effects are smaller and model-dependent, but efficiency gains are consistent. These findings suggest that coding-agent evaluation should report not only whether a task is solved, but also how costly that work is for another agent to resume.
Subjects: Artificial Intelligence (cs.AI)
Cite as: arXiv:2606.02875 [cs.AI]
(or arXiv:2606.02875v1 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2606.02875
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From: Dipesh Kc [view email]
[v1] Mon, 1 Jun 2026 20:40:38 UTC (247 KB)
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