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thinkneo_benchmark_report

Read-onlyIdempotent

View the outcome benchmark matrix — real quality scores per provider/model/task_type based on verified outcomes, not static estimates. Shows verification rates, sample counts, and rankings. Requires authentication.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
task_typeNoFilter by task type: 'summarization', 'code_generation', 'classification', 'translation', etc. Leave empty for all.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • removedInput schema / properties / period
      Removed value: -{
-  "default": "30d",
-  "description": "Period: 7d, 30d, 90d",
-  "title": "Period",
-  "type": "string"
-}
    • addedInput schema / properties / task_type
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Filter by task type: 'summarization', 'code_generation', 'classification', 'translation', etc. Leave empty for all.",
+  "title": "Task Type"
+}
  2. Changed2 schema fields changed
    • addedInput schema / properties / period
      Added value: +{
+  "default": "30d",
+  "description": "Period: 7d, 30d, 90d",
+  "title": "Period",
+  "type": "string"
+}
    • removedInput schema / properties / task_type
      Removed value: -{
-  "anyOf": [
-    {
-      "type": "string"
-    },
-    {
-      "type": "null"
-    }
-  ],
-  "default": null,
-  "description": "Filter by task type: 'summarization', 'code_generation', 'classification', 'translation', etc. Leave empty for all.",
-  "title": "Task Type"
-}
  3. Added

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already indicate a safe read-only, idempotent operation. The description adds valuable context by explaining the source of scores (verified outcomes vs. static estimates), what is shown (verification rates, sample counts, rankings), and requiring authentication. This goes beyond the structured fields without contradicting them.

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?

The description is two sentences, front-loaded with the core action ('View the outcome benchmark matrix'), and every sentence adds meaningful detail without redundancy. It is concise and well-structured.

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 tool's simplicity (one optional param, output schema present, full annotations), the description covers the key aspects: purpose, data basis, displayed metrics, and authentication. No critical information is missing for an agent to select and invoke the tool correctly.

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 the single optional task_type parameter is fully described in the schema with examples and a default. The tool description does not add additional parameter meaning beyond what the schema already provides, so the baseline score of 3 applies.

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 clearly states the tool views an outcome benchmark matrix with real quality scores per provider/model/task_type, based on verified outcomes. It distinguishes from siblings like benchmark_compare by emphasizing the matrix view and verified outcomes rather than static estimates.

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

Usage Guidelines4/5

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

The description provides clear context for when to use the tool (viewing verified benchmark scores and rankings) and notes authentication requirements. However, it does not explicitly state when to use alternatives like thinkneo_benchmark_compare or compare_models, so it lacks explicit exclusions.

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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