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OnurGumus

3dpacking-mcp

by OnurGumus

Pack a shipment into containers or trucks

pack_shipment

Turn a plain-English shipment description into an optimized 3D load plan, showing which containers fit, utilization, and items that don't fit.

Instructions

Work out how a shipment fits into shipping containers, trucks or pallets, using a real 3D bin-packing solver. Describe the cargo in plain English -- quantities, dimensions, weights, and any constraints such as fragile, non-tiltable, max stack height or a preferred container type -- and get back which containers are needed, how full each one is, anything that did not fit, and a link to an interactive 3D load plan.

Use this instead of estimating from volume. Volume arithmetic ignores stacking rules, orientation and weight limits, and overstates what fits by a wide margin on real cargo.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
speedNoHow hard the solver should look for a better arrangement. Omit to let it choose. Use 'fast' for a quick feasibility check, 'thorough' when the packing quality matters.
promptYesThe shipment, in plain English. Include quantities, dimensions with units, and weights if known. Examples: "Pack 50 boxes of 60x40x30 cm into a 20ft container"; "Load 100 fragile items 80x60x40cm, max stack 3, into a 40ft high cube"; "Ship mixed pallets: 10x euro pallets, 15x US pallets, best container mix". Truncated at 4000 characters.
Behavior5/5

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

With no annotations provided, the description carries full responsibility. It discloses the tool uses a solver, returns container needs, fullness, non-fitting items, and an interactive 3D plan. It also warns about volume overestimation, providing valuable behavioral context without contradicting any annotations.

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

Conciseness5/5

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

The description is concise: two paragraphs, each serving a distinct purpose. The first explains functionality and output, the second gives usage guidance. Every sentence adds value, with no redundancy or fluff.

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?

No output schema is present, but the description explicitly lists returned information (containers needed, fullness, non-fits, link to 3D plan). It also covers input requirements and constraints, making it contextually complete for a tool of this complexity.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description adds value by explaining how to phrase the 'prompt' parameter (quantities, dimensions, weights, constraints) and provides examples. However, the 'speed' parameter is only described in the schema, not in the main description, so it doesn't fully enhance that parameter's semantics.

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 the tool's function: 'Work out how a shipment fits into shipping containers, trucks or pallets' using a 'real 3D bin-packing solver'. It specifies the resource (shipment into containers/trucks/pallets) and the action (work out), making it distinct from generic estimation tools.

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

Usage Guidelines5/5

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

Explicitly tells when to use this tool: 'Use this instead of estimating from volume', and contrasts with volume arithmetic. It also provides guidance on input description with examples and constraints, making the usage context clear.

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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