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SoapyRED

FreightUtils MCP Server

by SoapyRED

ldm_calculator

Calculate loading metres (LDM) for European road freight shipments to determine trailer space usage and check pallet fit within vehicle limits.

Instructions

Calculate loading metres (LDM) for road freight shipments.

LDM measures how much of a trailer's length a pallet load occupies. European trailers are 13.6m long and 2.4m wide. LDM = (pallet_length x pallet_width x quantity) / (trailer_width x stack_factor).

Use this tool when you need to:

  • Quote European road freight (FTL/LTL)

  • Calculate trailer utilisation percentage

  • Check if pallets fit within vehicle weight/space limits

Supports pallet presets (euro, uk, half, quarter) or custom dimensions. Supports vehicles: artic (13.6m), rigid10, rigid75, luton, or custom length.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
palletNoPallet preset. Euro=1200x800mm, UK=1200x1000mm, Half=800x600mm, Quarter=600x400mm
length_mmNoCustom pallet length in mm (use instead of preset)
width_mmNoCustom pallet width in mm (use instead of preset)
quantityNoNumber of pallets (default: 1)
stackableNoCan pallets be stacked? (default: false)
stack_heightNoStack height: 2 or 3 (default: 2)
weight_kgNoWeight per pallet in kg
vehicleNoVehicle type (default: artic 13.6m)
vehicle_length_mNoCustom vehicle length in metres (required if vehicle=custom)
Behavior3/5

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

Discloses calculation formula and European trailer standards, but fails to explain stack_factor derivation from stack_height parameter or what the tool returns (LDM value vs utilisation percentage).

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?

Perfectly structured with definition first, then formula, usage scenarios, and capability summary; no redundant sentences.

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

Completeness3/5

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

Adequate for basic invocation but lacks output specification (critical given no output_schema) and clarification on how stackable/stack_height affect the LDM calculation via stack_factor.

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?

Adds value beyond 100% schema coverage by grouping parameters (presets vs custom) and clarifying vehicle dimensions (artic=13.6m), though schema already covers most enum descriptions.

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?

Specific verb (Calculate) + resource (loading metres/LDM) with clear mathematical definition and explicit differentiation from volume/weight-based siblings like cbm_calculator and chargeable_weight_calculator.

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?

Provides explicit 'when to use' scenarios (European road freight, trailer utilisation) but lacks explicit 'when not to use' or direct comparison to alternatives like pallet_fitting_calculator.

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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