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NestingCalc Calculators

lumber_weight_calculator

Weight of lumber by species, dimensions, quantity and moisture (dry/fresh), using species density tables. Optional custom density in kg/m3.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qtyNo
speciesYesWood species key
length_mYes
moistureNofresh (green) wood uses 1.5x density (+50% weight)dry
width_mmYes
thickness_mmYes
custom_density_kg_m3NoOverrides species density

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description must carry full behavioral disclosure. It does reveal that calculations use species density tables and allow optional custom density override, which is useful. However, it omits the output unit and any underlying assumptions, such as metric inputs or how moisture affects the result beyond what the schema states.

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 entire description is one concise, front-loaded sentence with no filler. Every phrase carries meaning: 'Weight of lumber', the parameter categories, and the optional custom density.

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?

For a 7-parameter calculator with no output schema and no annotations, the description covers the core inputs but leaves gaps: the output unit is not explicitly stated, and there is no routing guidance to distinguish from board_feet_calculator or green_log_weight. It is sufficient for a straightforward calculation but not fully complete.

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 43%, leaving most parameters undocumented. The description adds a semantic umbrella covering species, dimensions, quantity, moisture, and custom density in kg/m3, which helps interpret the unnamed numeric parameters. Yet it does not specify dimension units (though property names imply mm/m) or elaborate on moisture states beyond the schema's own description.

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 states a specific verb and resource: 'Weight of lumber by species, dimensions, quantity and moisture (dry/fresh)'. This is not a tautology and the scope clearly differentiates it from related siblings like board_feet_calculator (volume) and green_log_weight (logs), even without naming them explicitly.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool over alternatives. It does not mention sibling tools such as green_log_weight or board_feet_calculator, nor does it state any exclusions or conditions. Usage must be inferred entirely from the name and terse description.

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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