API Tool Calls

Board Foot Calculator

board_feet

Read-onlyIdempotent

Sum board-foot lumber volumes from entered dimensions and whole piece counts, with per-row optional prices and a priced subtotal.

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "rows": [
        {
          "width": 6,
          "length": 8,
          "quantity": 3,
          "thickness": 1,
          "pricePerBoardFoot": 4
        }
      ]
    },
    "name": "board_feet"
  }
}

Input Schema

Name	Required	Description	Default
`rows`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 4, 2026

TDQS

A3.9/5.0

Behavior3/5

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

The annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds that per-row prices are optional and that a priced subtotal is produced, which is useful context, but it does not disclose edge cases, unit handling, or other behavioral details beyond the purpose.

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?

It is a single, front-loaded sentence that communicates the computation, inputs, and optional pricing without any filler. Every phrase contributes to understanding the tool.

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 rich annotations, detailed input schema, and presence of an output schema, the description is complete enough for an agent to understand the tool. Return values need not be explained because an output schema exists, and the description correctly focuses on the calculation and optional pricing behavior.

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 reported as 0%, so the description must compensate for the single top-level 'rows' parameter. It names the relevant concepts (dimensions, whole piece counts, per-row optional prices), but omits unit defaults and quantity defaults that are present in the nested schema properties.

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: 'Sum board-foot lumber volumes' and specifies the inputs (entered dimensions and whole piece counts) plus optional pricing. This clearly distinguishes it from sibling calculators such as square_footage_calculator or volume_calculator.

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

Usage Guidelines3/5

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

Usage is implied by the purpose: it is for computing board-foot lumber volumes from dimensions and piece counts. However, the description does not explicitly say when to use this tool versus alternative calculators or when it is not appropriate, leaving the agent to infer.

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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