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Compare models

compare_models
Read-only

Side-by-side core overall and per-size accuracy, cost, latency and token results for model or family names.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelsYes2 to 20 model variant ids or family names, e.g. claude-opus-5.5 or gpt-6-astra-xhigh

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / models / description
      Added value: +"2 to 20 model variant ids or family names, e.g. claude-opus-5.5 or gpt-6-astra-xhigh"
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "$schema": "https://json-schema.org/draft/2020-12/schema",
      +  "additionalProperties": false,
      +  "properties": {
      +    "models": {
      +      "items": {
      +        "additionalProperties": {},
      +        "properties": {
      +          "accuracy": {
      +            "description": "Percentage of puzzles solved",
      +            "type": "number"
      +          },
      +          "bySize": {
      +            "items": {
      +              "additionalProperties": {},
      +              "properties": {
      +                "size": {
      +                  "type": "string"
      +                }
      +              },
      +              "required": [
      +                "size"
      +              ],
      +              "type": "object"
      +            },
      +            "type": "array"
      +          },
      +          "correct": {
      +            "type": "number"
      +          },
      +          "displayName": {
      +            "type": "string"
      +          },
      +          "effort": {
      +            "type": [
      +              "string",
      +              "null"
      +            ]
      +          },
      +          "failedRuns": {
      +            "type": "number"
      +          },
      +          "family": {
      +            "type": "string"
      +          },
      +          "model": {
      +            "description": "Model variant id, e.g. claude-opus-5.5-high",
      +            "type": "string"
      +          },
      +          "provider": {
      +            "type": [
      +              "string",
      +              "null"
      +            ]
      +          },
      +          "reasoning": {
      +            "type": "boolean"
      +          },
      +          "total": {
      +            "type": "number"
      +          }
      +        },
      +        "required": [
      +          "model",
      +          "displayName",
      +          "family",
      +          "effort",
      +          "provider",
      +          "reasoning",
      +          "accuracy",
      +          "correct",
      +          "total",
      +          "failedRuns",
      +          "bySize"
      +        ],
      +        "type": "object"
      +      },
      +      "type": "array"
      +    }
      +  },
      +  "required": [
      +    "models"
      +  ],
      +  "type": "object"
      +}
  2. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds which metric families are compared (accuracy, cost, latency, tokens; overall and per-size), which is useful, but since an output schema exists this is largely a preview of return contents rather than disclosure of behavior an agent couldn't infer.

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?

A single sentence with no filler, front-loading the comparison framing and then the dimensions compared. Nothing could be removed without losing information.

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 read-only, one-parameter comparison tool with a full output schema, the description covers what is compared closely enough for correct invocation. The remaining gap is routing guidance versus sibling tools such as get_model_results or get_leaderboard.

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%, so the single 'models' array is fully documented, including the 2–20 bound and id examples. The description's 'model or family names' merely restates the schema, adding no new format or syntax guidance; baseline 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?

Names a specific action (side-by-side comparison) plus the resource (models/families) and enumerates the compared dimensions: overall and per-size accuracy, cost, latency, and token results. An agent can distinguish it from single-model tools like get_model_results, though the description never explicitly names that sibling.

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?

The word 'side-by-side' and the plural 'names' imply the multi-model use case, and the schema's 2–20 min/max reinforces it, but there is no explicit 'use this when…' statement and no reference to get_model_results, get_leaderboard, or other alternatives for single-model or ranked lookups.

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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