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Model detail

model_detail
Read-onlyIdempotent

One model in detail: prices, context, what it supports, and what a call of a given size would cost.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "model": "<model>"
    },
    "name": "model_detail"
  }
}

Input Schema

NameRequiredDescriptionDefault
modelYesModel ID with its vendor, like openai/gpt-4.1-mini.
tokens_inNoPrompt tokens of a typical call, for the cost estimate. 1000 by default.
tokens_outNoAnswer tokens of a typical call, for the cost estimate. 500 by default.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint=false, so safety is covered. The description goes beyond them by disclosing what the response actually contains, including a computed cost projection for a typical call, which is genuine behavioral value. It omits what happens for an unknown model ID, a minor gap.

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?

A single front-loaded sentence with no filler; the core purpose comes first and the payload contents follow as a compact list. Slightly elliptical phrasing like 'what it supports' and 'context' costs a little precision but nothing is wasted.

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

Completeness4/5

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

For a three-parameter read-only tool with no output schema, the description usefully stands in for the missing return-value documentation by enumerating the fields returned. What remains unstated is the discovery path for a valid model ID and error behavior on an invalid one.

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% and all three parameters are documented in the schema, including defaults and an example model ID. The description's phrase 'what a call of a given size would cost' reinforces why tokens_in/tokens_out exist, but adds no syntax or constraint detail beyond the schema, so the baseline of 3 applies.

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 verb+resource: retrieve one model's detail, enumerating what that detail contains (prices, context window, capabilities, cost for a given call size). This clearly contrasts with a bulk listing, though it never names list_models as the discovery counterpart, so the sibling differentiation is only implied by 'One model.'

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?

There is no explicit when-to-use or when-not-to-use guidance and no named alternative. An agent must infer that list_models is the way to discover a model ID before calling this, and that this tool is for deep-diving a single known model. The singular framing hints at usage but states nothing.

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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