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x402-cone-frustum-volume

Cone Frustum Volume: Volume of cone frustum.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
heightNoHeight to process
radius1NoRadius1 to process
radius2NoRadius2 to process

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedInput schema / properties / height
      Added value: +{
      +  "description": "Height to process",
      +  "type": "string"
      +}
    • addedInput schema / properties / radius1
      Added value: +{
      +  "description": "Radius1 to process",
      +  "type": "string"
      +}
    • addedInput schema / properties / radius2
      Added value: +{
      +  "description": "Radius2 to process",
      +  "type": "string"
      +}
  2. First observed

TDQS

C2.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full disclosure burden, and it delivers essentially nothing: no units (metric? any?), no return format or precision, no statement of which measurement system or ordering is expected. For a pure computation this is low-stakes, but the behavioral surface is undocumented.

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

Conciseness3/5

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

Very short and front-loaded, but the second clause simply repeats the first ('Cone Frustum Volume' / 'Volume of cone frustum'), so half the text is redundant rather than informative. Brevity here comes from under-specification, not efficiency.

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

Completeness2/5

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

For a 3-parameter math tool with no output schema and no annotations, the description omits units, the ordering/semantics of radius1 vs radius2, and any hint of the result. An agent is left guessing at inputs that materially change the computed volume.

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

Parameters2/5

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

Schema description coverage is nominally 100%, but the schema text is tautological filler ('Height to process', 'Radius1 to process'), so the schema does not actually explain the parameters. The description adds nothing to resolve the critical ambiguity of which radius is the top versus bottom base. This falls short of the baseline-3 case where the schema genuinely documents the parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Cone Frustum Volume: Volume of cone frustum' restates the tool name with no added verb, scope, or distinguishing detail. There is no differentiation from close siblings such as x402-cone-volume, x402-frustum-volume, or x402-tube-volume, leaving an agent to infer the difference from names alone.

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?

No when-to-use guidance, no statement of when this is preferable to the plain cone-volume or frustum-volume tools, and no mention of prerequisites. The agent receives no routing signal beyond the name.

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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