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    • A
      license
      A
      quality
      B
      maintenance
      Enables AI assistants to plan container and truck loads from plain-English shipment descriptions, returning fitted containers, utilization, non-fitting items, and interactive 3D load plans.
      1
      96 npm
      MIT
    • A
      license
      A
      quality
      D
      maintenance
      Lets AI agents pack shipping containers using the Kubova calculator, with tools for container loading and API key verification.
      4
      12 npm
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Plan optimal container & truck loads: 3D layouts, right-size the container mix, and check utilization, centre of gravity, crush protection and securing across 200+ equipment types.
      8 npm
      2
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Enables optimal freight-mode selection (air, sea-LCL, full container) by solving 3D bin-packing, cost optimization, and delivery-risk analysis behind two tools: solve for deterministic planning and explain for hallucination-proof natural-language narration of results.
      2
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables AI assistants to track air waybills and ocean containers and compare freight quotes across carriers through typed, validated tools, with normalized milestone timelines, ETAs and check-digit validation.
      1
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables AI agents to track packages, rate and create shipments, manage pickups and customs documentation, and perform international shipping logistics checks through natural language.
      MIT

    TDQS

    A4.5/5.0

    Scored across 3 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: list_vehicles retrieves vehicle options, pack_cargo submits an optimization job, and check_job monitors that job. There is no overlap or ambiguity.

    Naming Consistency5/5

    All three tools follow a consistent verb_noun pattern with snake_case: check_job, list_vehicles, pack_cargo. The naming is predictable and clear.

    Tool Count5/5

    With only 3 tools, the scope is narrow but well-defined. Each tool serves an essential step in the cargo packing workflow without unnecessary extras.

    Completeness5/5

    The domain of cargo packing is fully covered: listing available vehicles, computing an optimal pack, and checking on an async job. No obvious gaps are present.