GleanMark USPTO Trademark Search

Web Research

web_research

Read-onlyIdempotent

Research a company, trademark, or legal topic on the internet. Returns grounded results with source citations. Use for company background, recent news, common law trademark use, or case law research.

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": {
      "entity_name": "<entity_name>",
      "research_type": "<research_type>"
    },
    "name": "web_research"
  }
}

Input Schema

Name	Required	Description
`mark_text`	No	Trademark text (for common_law_use and state_registrations searches)
`entity_name`	Yes	Company name, trademark, or topic to research
`nice_classes`	No	Nice classes for context
`research_type`	Yes	Type of research to perform

Schema Changelog

Changes observed during successful MCP inspections.

AddedMar 17, 2026

TDQS

A4/5.0

Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds that results are grounded and include source citations, which is useful, but it does not disclose limitations like possible latency, source freshness, or citation formatting. This is acceptable but not exceptional.

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?

Two sentences with no filler. The main action and result are front-loaded, and the use-case list is compact yet informative. Every sentence contributes to tool selection and invocation.

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?

Given the annotations and full schema coverage, the description is nearly complete. It states what the tool does, what it returns, and when to use it. There is no output schema, so a bit more detail on the exact response structure could help, but the mention of source citations provides enough shape for an agent.

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 schema already documents all parameters, including the research_type enum. The description reinforces the overall purpose but does not add meaning beyond what the input schema provides, so the baseline of 3 is appropriate.

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 uses a specific verb ('Research') with a clear resource ('a company, trademark, or legal topic on the internet') and names concrete use cases. It also distinguishes itself from the many database-lookup siblings by emphasizing internet research and grounded results with source citations.

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 explicitly says when to use the tool: 'for company background, recent news, common law trademark use, or case law research.' It does not name specific alternative tools or state when not to use it, but the listed use cases are clear enough for an agent to route appropriately.

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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