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convert

Convert a model call's token counts into SIU and USD.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYes
input_tokensYes
output_tokensYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.7/5.0
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 burden of behavioral disclosure. It implies a pure conversion, but does not state whether it is a read-only calculation, whether it depends on live pricing data, or what happens with invalid/unrecognized models. This is a significant gap for a tool with no annotation safety profile.

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

Conciseness4/5

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

The description is a single front-loaded sentence with no wasted words. It is concise, though perhaps too brief to carry the explanatory load given the lack of schema descriptions and annotations.

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?

The tool requires three parameters and has no output schema or annotations. The description does not explain how the model parameter influences the result, the nature of SIU, expected return format, or error behavior. For a conversion tool of this simplicity, the description is minimally adequate but incomplete for confident invocation.

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?

With schema description coverage at 0%, the description must compensate. It relates 'token counts' to the token parameters and 'model call' to the model parameter, but does not explain how model affects the conversion, what units the token counts are in, or what SIU means. The available schema provides only types and bounds, leaving key semantics undocumented.

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

Purpose4/5

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

The description states a specific action ('Convert') and resource ('model call's token counts') and identifies the output units (SIU and USD). It is distinct from the sibling tools, though the acronym 'SIU' is unexplained, which leaves some ambiguity.

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 guidance is given on when to use this tool versus the siblings. The description gives no context about use cases, prerequisites, or alternatives, so the agent must guess based on the name alone.

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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