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qa-metrics-mcp

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    TDQS

    A3.9/5.0

    Scored across 11 tools

    Disambiguation5/5

    Each tool targets a distinct QA-metrics workflow: listing runs, summarizing a run, trending pass rates, finding flaky tests, detecting regressions, comparing runs, clustering failures, slow tests, test history, reporting, and dashboard export. Overlaps are minimal and descriptions clarify boundaries, such as flaky versus regression versus failure-cluster analysis.

    Naming Consistency5/5

    All tool names use consistent snake_case with a verb_noun pattern (list_runs, get_run_summary, find_flaky_tests, detect_regressions, compare_runs, generate_quality_report, export_dashboard). The verbs vary appropriately by action while the naming convention remains predictable throughout.

    Tool Count5/5

    Eleven tools is well-scoped for a QA metrics server, covering discovery, analysis, reporting, and export without obvious filler. Each tool has a clear role and there is no excessive surface area for the domain.

    Completeness4/5

    The surface covers the core QA metrics lifecycle: run listing, summaries, trends, flakiness, regressions, comparisons, failure clustering, slow tests, history, and report/dashboard outputs. Minor gaps may exist around direct suite-level listing or filtering controls, but agents can work around these using the existing tools.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

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