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Moltline Shipping Maths

Freight Class

freight_class
Read-onlyIdempotent

Derive a US LTL freight class from density. FREE.

Density in pounds per cubic foot maps to a class on the published NMFC density scale. Typical input {"length": 48, "width": 40, "height": 36, "weight": 400} returns {"cubic_feet": 40.0, "density_pcf": 10.0, "density_class": "100", "caveat": "..."}.

Use for a first estimate before a carrier quote. Not as a final classification: NMFC also weighs stowability, handling and liability, so a carrier can and does reclassify. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": ""} (for example {"error": "dimensions produce zero volume"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
unitsNo"in_lb" for inches and pounds, or "cm_kg" for centimetres and kilograms. Default "in_lb".in_lb
widthYesSecond side. Must be greater than 0.
heightYesThird side, including the pallet. Must be greater than 0.
lengthYesLongest side of the palletised freight. Must be greater than 0.
weightYesGross weight including the pallet. Must be greater than 0.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.7/5.0
Behavior5/5

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

The annotations already declare readOnlyHint, idempotentHint, and destructiveHint, but the description adds crucial behavioral details beyond these. It explicitly states that invalid input never raises a protocol error, instead returning a structured error object, and that the tool is read-only and idempotent, making retries safe. This discloses error-handling behavior not present in annotations and enriches the agent's understanding of runtime behavior.

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 yet information-dense. It is front-loaded with the purpose and example, followed by usage constraints and error behavior. Every sentence serves a purpose: purpose, typical mapping, example, context for use, caveat about NMFC factors, and error handling. No unnecessary fluff; it effectively communicates the essentials in a compact format.

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 tool's moderate complexity and strong schema + annotations, the description covers all critical aspects: what it computes, when to use it, limitations, error handling, and idempotency. An output schema exists (though not shown) and is not required to be explained. The description is complete enough for an agent to decide when to invoke it and what to expect on both success and failure.

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

Parameters3/5

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

Schema description coverage is 100%—all parameters are described in the input schema. The description's example input/output adds concrete usage context but does not introduce meaning beyond the schema's field descriptions. Hence, the baseline of 3 applies, as the description does not compensate for any gaps nor does it deepen parameter semantics beyond the example.

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

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?

The description explicitly states when to use the tool: 'Use for a first estimate before a carrier quote.' It also clearly excludes its use as a final classification: 'Not as a final classification: NMFC also weighs stowability, handling and liability, so a carrier can and does reclassify.' This gives clear guidance on appropriate usage and when to resort to alternatives (carrier quotes).

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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TDQS

A4.8/5.0
Disambiguation5/5

Each tool serves a clearly distinct calculation: billable weight, free shipping break-even, freight class from density, landed cost, box selection, and rate card generation. The descriptions explicitly cross-reference which tool to use instead when there's potential overlap, eliminating ambiguity.

Naming Consistency4/5

Tool names follow a consistent lowercase snake_case style, but the pattern is mostly noun phrases (dim_weight, freight_class, rate_card) with one deviation (parcel_fit uses a noun+verb combo). This is minor and does not hinder readability.

Tool Count5/5

With 6 tools, the set is well-scoped for a shipping mathematics server. Each tool addresses a distinct functional need without redundancy, fitting comfortably in the ideal range.

Completeness5/5

The surface covers the core shipping calculations: dimensional weight, packaging selection, freight classification, landed cost, pricing thresholds, and rate tables. No obvious missing operations for the stated domain, especially given the read-only and idempotent nature of the tools.

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