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mlagents-mcp

by limam-B
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    TDQS

    A3.9/5.0

    Scored across 18 tools

    Disambiguation4/5

    Most tools target distinct resources/actions: launching, stopping, resuming, config, waiting, checking, logging, comparing. A coupple of overlaps exist, especially check_completion vs. wait_for_completion and the various check_* tools vs. get_run_status, but descriptions clearly separate blocking/non-blocking and specific conditions.

    Naming Consistency5/5

    All tool names follow a consistent snake_case verb_noun pattern: force_training, stop_training, update_config, check_step, get_metrics, list_runs, export_model. There are no style mixes or vague one-word names.

    Tool Count3/5

    18 tools is in the heavier range and the count is inflated by several near-duplicate monitoring utilities: check_step, check_reward, check_completion, check_checkpoint, wait_for_completion, and wait_for_first_metrics could potentially be consolidated. Still, the coverage is understandable for a training lifecycle server.

    Completeness4/5

    The server covers most of the training lifecycle: launch, resume, stop, configure, monitor, wait, list, compare, and export models. Minor gaps exist, such as no explicit delete/cleanup for run artifacts besides process cleanup, but core workflows are not dead-end.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

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