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embodied-mcp

embodied-mcp

by DDDB479
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    TDQS

    B3.4/5.0

    Scored across 19 tools

    Disambiguation4/5

    Each tool targets a reasonably distinct action (detect vs. summarize vs. validate vs. quality_report vs. quality_gate), and the descriptions draw the lines clearly (structural validation vs. statistics/anomalies vs. rule evaluation). The main soft overlaps are detect_dataset/summarize_dataset (both surface the format) and the direct-call vs. submit_job paths for validate_dataset/quality_gate, but the background job model is explained well enough to avoid misselection.

    Naming Consistency4/5

    Nearly all tools use a consistent snake_case verb_noun pattern (segment_episodes, detect_dataset, validate_dataset, convert_dataset, catalog_search), grouped with readable prefixes like catalog_ and job-related tools. Minor deviations are noun-phrase names such as job_status, quality_report, quality_gate and catalog_stats, which mix styles slightly but remain predictable and readable.

    Tool Count4/5

    At 19 tools the surface is a bit heavy, but the domain is genuinely broad: inspection, validation, quality analysis, windows/segmentation, conversion, scaffolding, cataloging and job orchestration. Almost every tool maps to a real capability rather than filler, so it lands just over the ideal band without feeling padded.

    Completeness4/5

    Coverage is strong end-to-end: discovery, schema summary, structural validation, quality analysis and gating, annotation manifests, conversion, project scaffolding, a searchable catalog with version history, and async job lifecycle (submit/status/cancel/list). Minor gaps remain — no tool to read individual frames/episodes or sample data, and no catalog entry deletion/update beyond upsert by index.

    Maintenance

    ActivityNo data
    ResponsivenessOutdated data

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