Search USPTO trademark database for conflicts with a brand name. Returns exact matches, similar marks, risk level, and Nice class information.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | The brand name to check | |
| niceClasses | No | Optional Nice classes to focus on |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It discloses that the tool searches the USPTO database and returns results including risk level. However, it omits behavioral traits such as whether the tool is read-only, authentication requirements, rate limits, or what happens on errors. The description is basic but not misleading.
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?
The description is two sentences with no redundant information. It front-loads the action and resource, then lists return values efficiently. Every word serves a purpose.
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?
Given the low complexity (2 params, no output schema, no annotations), the description covers the essential purpose, scope, and output data. It mentions the USPTO database (US-specific) and Nice classes, which are key. It could mention that it only searches US trademarks, but that is implied by 'USPTO'. Nearly complete for a straightforward search tool.
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?
Schema description coverage is 100%, with both parameters having descriptive names and types. The description adds value by linking the 'niceClasses' parameter to 'Nice class information' in the output, and mentioning 'risk level' which is not in the schema. However, the added meaning is modest, so a baseline of 3 is appropriate.
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?
The description clearly specifies the action ('Search USPTO trademark database') and the resource ('brand name conflicts'). It also lists what is returned (exact matches, similar marks, risk level, Nice class information). This effectively distinguishes it from siblings like check_domain, check_geo, check_social, which cover different domains.
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 description implies usage when checking trademark conflicts for a brand name, but it does not explicitly state when to use this tool versus alternatives (e.g., check_domain for domain names). There is no guidance on when not to use it or prerequisites like trademark registration.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct aspect of brand name evaluation: domain availability, GEO score, social handles, trademark conflicts, and overall scoring. There is no overlap in purpose.
Four of five tools follow a consistent 'check_' prefix pattern, but 'score_name' breaks this convention with a different verb. The pattern is otherwise clear.
With 5 tools, the set is well-scoped for a brand name evaluation service. It covers individual checks and a composite scoring function without redundancy.
The tools cover key evaluation dimensions (domain, trademark, social, AI findability, and composite score). Minor gaps might include language-specific checks or URL verification, but core workflows are supported.
