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Glama

Zhihuo Container Loading

Server Details

How many identical cartons fit in a container or space, where they go, plus a 3D loading plan.

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Healthy
Last Tested
Transport
Streamable HTTP
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Tool DescriptionsA

Average 4.5/5 across 2 of 2 tools scored.

Server CoherenceA
Disambiguation5/5

The two tools are completely distinct: pack_boxes performs container loading calculations, while send_feedback is for contacting the tool maintainers. There is no overlap.

Naming Consistency5/5

Both tools follow a clear verb_noun pattern: pack_boxes and send_feedback. The naming is consistent and predictable.

Tool Count4/5

The server has only two tools, which is slightly minimal for a container loading server but still acceptable. The feedback tool is auxiliary, and the core functionality is captured in a single, powerful tool.

Completeness3/5

The main packing tool is comprehensive, but there is no tool to list available container presets or retrieve their dimensions. Users must rely on the tool's internal knowledge of presets, which could be considered a minor gap.

Available Tools

2 tools
pack_boxesA
Read-onlyIdempotent
Inspect

Calculate how many identical boxes fit in a rectangular space, and where.

    The space is a shipping container, a pallet area, leftover container space,
    or a larger box. Give the box's L/W/H and EITHER a `container` preset OR the
    space's L/W/H (all in millimetres - container presets are mm). Boxes mix
    orientations across regions to pack densely; the plain maximum-load answer
    uses the exact SmartPacker T solver.

    Args:
        box_length: Box length.
        box_width: Box width.
        box_height: Box height.
        container: Container preset instead of explicit space dims (fills the
            internal usable L/W/H in mm; overrides space_* when recognised).
            ISO dry: 20GP 20HQ 40GP 40HQ 45GP 45HQ; NA domestic: 53HC 48HC;
            reefers: 20RF 40RF 40RH; EU pallet-wide: 40HQ-PW 45HQ-PW. Many
            aliases (20/40/45, 20ft, 40HC, 40', 40 reefer, ...).
        space_length: Space length (front-back). Use this OR `container`.
        space_width: Space width (left-right).
        space_height: Space height (up).
        count: How many boxes to load. 0 (default) loads the maximum.
        to_front: Anchor a partial load to the front (else the back).
        to_left: Anchor a partial load to the left (else the right).
        to_bottom: Anchor a partial load to the bottom (else the top).
        box_weight: Weight of one box (optional; same unit as max_weight).
        max_weight: Max total load weight (optional; 0 = no weight limit).
        include_image: Set true ONLY when the user wants to SEE or visualize
            the loading plan / 3D layout (e.g. "show the loading plan",
            "visualize it", "what does it look like?"). Default false is
            faster and lighter and still returns `image_url`, a shareable
            link to the 3D render. When true, the image is ALSO embedded
            inline (Claude Desktop and Cherry Studio display it; the
            claude.ai web app shows only the link either way).

    Returns the maximum that fits, how many were loaded, the fill rate, the
    region/block decomposition (each block's position, orientation, and
    grid), any weight limit applied, an `image_url` link to the rendered 3D
    loading plan, and - when include_image is true - the inline image too.
    
ParametersJSON Schema
NameRequiredDescriptionDefault
countNo
to_leftNo
to_frontNo
box_widthYes
containerNo
to_bottomNo
box_heightYes
box_lengthYes
box_weightNo
max_weightNo
space_widthNo
space_heightNo
space_lengthNo
include_imageNo
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description details the tool's behavior, including that it is read-only (matching readOnlyHint=true) and idempotent (idempotentHint=true). It explains the return structure, the effect of 'include_image' on performance, and default settings. This adds significant context beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is relatively long (22 lines) but well-structured: a concise intro, then an Args section with line items, and a return description. It is front-loaded with the main purpose. Despite length, every sentence adds value and it is appropriately detailed for the tool's complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the high parameter count (14), no output schema, and absence of sibling tools for comparison, the description is complete. It covers all inputs, default behaviors, return values (including image_url and inline image), and usage context such as container presets and aliases.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description carries full burden. It thoroughly explains each parameter: box dimensions, container aliases, space dimensions, count (0 means maximal), anchor positions, weight limits, and include_image. The description provides full semantic meaning for all 14 parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Calculate how many identical boxes fit in a rectangular space, and where.' It uses specific verbs and resources, and distinguishes from the only sibling 'send_feedback' by focusing on packing calculation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains when to use the tool: provide box dimensions and either a container preset or explicit space dimensions. It also clarifies the 'include_image' parameter usage: only when visualization is needed. No explicit exclusions are given, but the context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

send_feedbackAInspect

Send a question, suggestion, or bug report about this container-loading tool to the Zhihuo maintainers.

    Use this when the user wants to ask the tool's authors a question,
    suggest an improvement (e.g. another container type or output field),
    or report a result that looks wrong. The note reaches the Zhihuo team.

    Args:
        message: The question, suggestion, or bug report, in plain text.
        contact: Optional email or handle if the user would like a reply.
        category: Optional tag - "question", "suggestion", "bug", or "other".

    Returns a short confirmation string.
    
ParametersJSON Schema
NameRequiredDescriptionDefault
contactNo
messageYes
categoryNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations indicate non-read-only (readOnlyHint: false) and non-destructive (destructiveHint: false). The description adds that feedback reaches the Zhihuo team and includes optional contact/category. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is well-structured with a brief intro, usage paragraph, and Args. It's front-loaded with purpose, but slightly verbose with the Args section. Still concise enough.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, the description succinctly notes it returns a short confirmation string. All three parameters are explained, and usage guidance is provided. No gaps for a feedback tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description's Args section explains each parameter: message as plain text, contact as optional email/handle, category as optional tag with specific values. This adds essential meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states it sends a question, suggestion, or bug report to maintainers. It uses specific verbs and resource, and clearly distinguishes from the sibling tool 'pack_boxes' which deals with packing.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description lists clear use cases: user questions, improvement suggestions, bug reports. It doesn't explicitly state when not to use, but the list is comprehensive and no alternative tools are needed.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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