Arcangel Trademark Search

Suggest trademark classes

suggest_nice_classes

Read-onlyIdempotent

Suggest trademark (Nice) classes for a description of goods or services, e.g. "mobile app for booking yoga classes".

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": {
      "description": "<description>"
    },
    "name": "suggest_nice_classes"
  }
}

Input Schema

Name	Required	Description	Default
`description`	Yes

Output Schema

Name	Required	Description	Default
`classes`	Yes
`description`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedNov 14, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "classes": {
+      "items": {
+        "properties": {
+          "class": {
+            "maximum": 45,
+            "minimum": 1,
+            "type": "integer"
+          },
+          "name": {
+            "type": [
+              "string",
+              "null"
+            ]
+          }
+        },
+        "required": [
+          "class",
+          "name"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "description": {
+      "type": "string"
+    }
+  },
+  "required": [
+    "description",
+    "classes"
+  ],
+  "type": "object"
+}

First observedNov 14, 2026

TDQS

A3.7/5.0

Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint=false and destructiveHint=false, so safety is covered. The description adds that it operates on goods/services text and returns class suggestions, but does not say how many classes come back, that results are indicative rather than authoritative, or anything about determinism or cost. With annotations carrying the behavioral profile, a 3 fits.

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?

One sentence, front-loaded with the verb and resource, with the example placed at the end where it clarifies rather than delays. Nothing is wasted and nothing essential is repeated.

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?

A single-parameter, read-only tool with a full annotation set and a declared output schema — the description appropriately focuses on purpose and input semantics rather than return values. It could be slightly more complete by noting that suggestions are indicative and non-authoritative for filing purposes, but nothing needed to invoke it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has a 0% description-coverage field, so the description must compensate — and it does, clarifying that the single string is a description of goods or services and giving an illustrative value ('mobile app for booking yoga classes') that shows the expected level of specificity. It does not mention the 3–500 character bounds, but adds genuine semantic guidance beyond the bare schema.

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?

States a specific verb and resource ('Suggest trademark (Nice) classes') and scopes the input to 'a description of goods or services', with a concrete example that pins down the expected granularity. It is distinguishable from the sibling check/get-check tools by being a suggestion generator rather than a lookup, though the description never explicitly contrasts with them.

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?

Usage is only implied: the goods/services framing and the example convey the intended call context. There is no explicit when-to-use vs. when-not guidance (e.g., that this is for pre-filing exploration and that check_trademark should follow for availability), and no statement about limitations of the suggestions.

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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