Taxonomie Produit
Server Details
Classifies product listings into the official Google Shopping taxonomy (5595 categories). Output ...
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
TDQS
Scored across 1 tool
With only one tool, there is no possibility of confusion between overlapping tools. The sole tool has a clearly defined purpose: classifying product listings into the Google Shopping taxonomy.
The single tool is named 'run', which is a vague, generic verb that gives no indication of its actual purpose. While consistency is trivially satisfied with one tool, the name is poorly aligned with the domain and lacks a descriptive verb_noun pattern.
A single tool makes the server feel more like a thin endpoint wrapper than a coherent MCP toolset. For a taxonomy-focused server, at least a few supporting tools would be expected, even if classification is the primary action.
The core classification workflow is covered and output validation is built in, but obvious supporting operations are missing, such as taxonomy search, category lookup, or batch classification. Agents have no way to explore or verify categories independently.
Available Tools
1 toolrunAInspect
Classifies product listings into the official Google Shopping taxonomy (5595 categories). Output is validated against the official list before being returned.
| Name | Required | Description | Default |
|---|---|---|---|
| input | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are empty, so the description carries the full burden. It adds one useful behavioral guarantee: output is validated against the official list before being returned. It does not describe failure behavior, return format, or state changes, though for a classifier these are less critical.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no filler; the core action comes first and the validation detail earns its place. This is an appropriately sized description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, no annotations, and an opaque nested input parameter, so the description must do more heavy lifting. It explains the high-level purpose but omits input formatting, return value details, and behavior on invalid or unclassifiable listings. This leaves a meaningful gap for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides only a generic 'input' object with 0% property description coverage, so the description must compensate by explaining the input shape. It vaguely indicates the input relates to product listings, but does not specify required fields, types, or structure. An agent cannot reliably construct a valid input from this.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific action—classifies product listings—and names the precise target resource: the official Google Shopping taxonomy with 5595 categories. Even though the tool name is the generic 'run', the description removes ambiguity about its purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The use case is implied: an agent should use this when it needs to classify product listings into Google Shopping taxonomy. There is no explicit when-not guidance, alternative tool comparison, or mention of prerequisites, but with no siblings listed the tool is at least clearly scoped.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
- First observed
run
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