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Life sciences · Preprint
arXiv · August 17, 2026
Early or partial results. Treat as a signal, not a conclusion.
This preprint identifies source-style collapse, a failure mode in fine-tuned tool retrievers where performance degrades on different source styles despite fixed capability corpora, and proposes ToolScout, a TF-IDF-based routing method to mitigate it. The work is empirical and addresses a systems-level problem in agent tool access but has not undergone peer review and does not report statistical significance or held-out test set validation.
Empirical evaluation study; systems benchmark analysis. Tool-backed executable skills in structured APIs; ToolRet benchmark with source-specific slices.. Intervention: ToolScout, a source-aware routing method using TF-IDF fingerprints as routing guard. Compared with: Baseline retriever (FT-1100) without source-aware routing; semantic and length-based proxies for source-style detection. n = 4,996.
Fine-tuned retriever (FT-1100) collapsed from higher lexical overlap baseline on ToolRet when tested on different source-specific slices of same benchmark TF-IDF fingerprints better identified source styles on which retriever fails than semantic or length-based proxies ToolScout routing raised coverage on 4,996-query mixed stream from 22.3% to 86.1%
Safety was not reported in the material analysed. Check the source before drawing any conclusion about harm.
The source did not state who this applies to in practice.
This is a preprint reporting a novel failure mode in tool retrieval systems and proposing a routing method; it lacks peer review, clinical outcomes, and validation on held-out test sets with statistical significance reporting.
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Large-scale agents increasingly rely on retrieval to access external capabilities. We study this retrieval gate in structured tools and APIs, a measurable class of tool-backed executable skills that must be surfaced before an agent can plan, incorporate, or act. In this setting the retrieval layer can silently fail even when the capability corpus is fixed: on ToolRet, a retriever fine-tuned on one source-specific slice collapses on another source-specific slice of the same benchmark, with FT-1100 despite its higher lexical overlap with the gold tools. We call this failure mode source-style collapse. Query-side TF-IDF fingerprints flag source styles on which the fine-tuned retriever is likely to fail better than semantic or length-based proxies, giving a cheap signal for mismatch over a fixed tool corpus. We propose ToolScout, a source-aware routing method that uses this signal as a routing guard: on the mixed 4,996-query stream, TF-IDF-based routing raises coverage from 22.3% to 86.1%, and across five collapsed sources 20 matched examples raise the coverage-weighted global top-1 proxy from 1.3% to 53.9%. The same failure and routing behaviors persist when tools are rerendered as executable skill cards, which rules out raw API-schema format as the sole cause.
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