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UVR maestro

UVR maestro

by romanstark
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Python
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    TDQS

    B3.2/5.0

    Scored across 34 tools

    Disambiguation3/5

    Most tools target distinct operations, but the separation family (separate_ensemble, start_separation, separate_audio, separate_chain, separate_vocal_splitter, separate_batch) has overlapping boundaries that require close reading to choose correctly. Model-management tools also overlap somewhat (download_model, download_missing_models, register_model, refresh_catalog), though descriptions provide enough context to disambiguate.

    Naming Consistency4/5

    The tool set is predominantly snake_case verb_noun (list_models, download_model, cancel_job, probe_audio), which is readable and predictable. Minor deviations include noun-style names such as uvr_status, change_journal, and matchering_inputs, plus uvr_skills.

    Tool Count2/5

    34 tools is heavy for an audio separation server, spanning model catalog management, job control, core separation, and several niche audio utilities. Many specialized tools could be consolidated or moved into documented workflows, making the surface feel overextended rather than tightly scoped.

    Completeness4/5

    The surface covers model lifecycle, job execution and cancellation, settings, catalog verification, separation workflows, and audio analysis/processing utilities. Minor gaps may exist around detailed per-model inspection or richer job-output retrieval, but most agent workflows are supported end to end.

    Maintenance

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    ResponsivenessNo issues

    Resources