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GleanMark Trademark Search

Top Correspondents at a Firm

get_firm_top_correspondents
Read-only

Get the leading correspondents or attorneys inside one named law firm, ranked by filing volume with prosecution and TTAB activity counts. Use this when the user asks for top correspondents at a specific firm, such as "Who are the top correspondents at Fross Zelnick?"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum correspondents to return.
firm_nameYesLaw firm name or normalized firm key.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
summaryYes
headlineYes
returnedYes
firm_nameYes
leader_nameNo
presentationYes
firm_detail_urlNo
leader_detail_urlNo
leader_total_filingsYes
total_correspondentsYes

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows this is a safe read operation. The description adds valuable context about ranking criteria (filing volume, prosecution, TTAB activity counts) and the one-firm scope, going beyond simple read-only labeling.

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?

The description is two sentences: the first states the function and criteria, the second gives usage context with an example query. Every word earns its place; no redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a two-parameter tool with full schema annotations, an output schema, and explicit usage guidance, the description is complete. It covers the core purpose, ranking metrics, one-firm scope, and a practical trigger example.

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%, with both firm_name and limit having clear descriptions in the input schema. The description adds no parameter-specific details beyond what the schema already 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 clearly states the tool retrieves leading correspondents/attorneys at a named law firm, ranked by filing volume with prosecution and TTAB activity counts. It distinguishes this from sibling tools like get_correspondent_marks by focusing on firm-level ranking and specific metrics.

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 instructs using this tool when the user asks for top correspondents at a specific firm, with a concrete example query. However, it doesn't mention alternatives or when not to use it, so it falls short of full exclusion guidance.

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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TDQS

B3.4/5.0
Disambiguation3/5

Most tools have clearly defined scopes, but several search/count tools overlap (search_trademarks, phonetic_search, run_knockout_search, get_similar_marks) and owner/firm analytics tools have similar boundaries. Descriptions help differentiate them, but the large set increases the chance of misselection.

Naming Consistency5/5

All tool names follow a consistent lowercase snake_case verb_noun pattern (get_, search_, run_, analyze_, etc.). The only minor deviation is web_research, which is noun_verb, but it remains perfectly readable and consistent with the overall style.

Tool Count1/5

61 tools is extreme for any server, far exceeding the 50+ threshold. Even for a comprehensive trademark platform, this number overwhelms agents with selection complexity and makes the toolset difficult to navigate.

Completeness2/5

Several tools launch asynchronous processes and instruct users to call status tools (get_prosecution_history_status, get_ttab_proceeding_analysis_status, get_office_action_research_status) that are not present in the toolset. Additionally, search_trademarks and phonetic_search reference list_marks_containing_term, which is also missing. These critical gaps cause agent failures when following the described workflows.

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