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GleanMark Trademark Search

Resolve an Ambiguous Name

resolve_trademark_subject
Read-onlyIdempotent

Matches a name to one trademark entity (an owner, law firm, correspondent, mark, TTAB proceeding, client or portfolio) and returns the match with its identifiers, or the top candidates when the name is ambiguous. Resolving clients and portfolios requires a signed-in account.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of candidate matches to return.
entityYesWhat kind of trademark subject to resolve.
subject_nameYesRaw owner, firm, correspondent, mark text/serial number, TTAB proceeding query, client name, or portfolio name to resolve.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, non-destructive behavior. The description adds valuable context beyond annotations: the return behavior (exact match vs. candidates) and the authentication requirement for clients/portfolios. It does not mention rate limits or detailed output format, but the added context is meaningful.

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, no filler, and the core function is stated up front. The additional auth note is placed at the end, keeping the structure clean.

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?

For a read-only tool with moderate complexity, the description covers the purpose, ambiguity handling, and a key auth constraint. It lacks an explicit statement about return format or ordering of candidates, but the absence of an output schema and the presence of annotations make this acceptable. Overall, it is sufficiently complete for an agent to use it 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%, so the baseline is 3. The description does not add significant per-parameter meaning beyond the schema; it lists entity types (already in the enum) and mentions ambiguity/candidates, but this is behavioral rather than parameter-specific. It doesn't explain 'limit' or add format details for subject_name.

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 states a specific verb ('Matches') and a specific resource ('trademark entity'), enumerating all entity types, and distinguishes its behavior (exact match vs. top candidates) from broader search/lookup siblings. It is not a tautology and clearly tells an agent what this tool does.

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 usage context: it resolves an ambiguous name and returns a match or candidates. It also gives a prerequisite (signed-in account for clients/portfolios). However, it does not explicitly name alternative sibling tools or state when NOT to use this tool, so it falls short of a 5.

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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