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hrishikesh-thakre

AI Workbench MCP

by hrishikesh-thakre
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    TDQS

    C2.9/5.0

    Scored across 7 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: analyzing runs, opening runs, quality gating, recording execution, selecting model, selecting policy pack, and validating runs. No overlap in functionality.

    Naming Consistency4/5

    All tools share the 'workbench_' prefix and mostly follow a verb_noun pattern (e.g., analyze_runs, open_run). Minor deviation with 'quality_gate' which is noun_verb, but overall consistent.

    Tool Count5/5

    With 7 tools, the set is well-scoped for an AI workbench run management domain. Not too few to lack utility, not too many to be unwieldy.

    Completeness3/5

    The tools cover core actions like opening, analyzing, recording, and validating runs, but lack lifecycle management tools such as listing, closing, or deleting runs. Some gaps exist for a complete workflow.

    Maintenance

    ActivityInactive
    ResponsivenessWithin a week

    Resources