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GleanMark Trademark Search

Owner Landscape for a Mark

get_mark_owner_landscape
Read-only

Show which owners hold marks matching a shared trademark term and summarize what else those owners have in their broader portfolios. Use this for crowded owner-landscape questions like "Which companies own a trademark for COMET?" or "Who owns trademarks for GLEAN?" Returns the matching owners ranked by footprint, with each owner's wider portfolio context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of owners to return.
mark_textYesTrademark term to analyze across owners, such as COMET or GLOW.
match_modeNoHow to match the mark text: contains, exact, or starts_with.contains
nice_classesNoOptional Nice classes to narrow the landscape.
status_filterNoOptional status filter. Default is live.live

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYes
ownersNo
summaryYes
headlineYes
returnedYes
mark_textYes
match_modeYes
leader_nameNo
nice_classesYes
status_filterYes
leader_detail_urlNo
total_matching_marksYes
total_matching_ownersYes
total_matching_live_marksYes
leader_matching_mark_countYes
leader_total_portfolio_mark_countYes

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare this a safe read-only operation (readOnlyHint=true, destructiveHint=false). The description adds useful context about the output (owners ranked by footprint, wider portfolio context), but does not disclose potential heavy queries, pagination, or any caveats about the 'landscape' aggregation.

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 core action, the second provides usage context and return summary. It is front-loaded, concise, and every sentence earns its place without redundancy.

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?

Despite having 5 parameters and an output schema, the description covers the essential context: it explains the output type (owners ranked by footprint with portfolio context), gives concrete examples, and the schema covers parameters and returns. The lack of extra behavior notes is acceptable given the annotations and minimal complexity.

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?

Input schema covers 100% of parameters with descriptions, so baseline is 3. The tool description adds no parameter-specific details beyond what the schema already provides; examples like 'COMET' subtly imply contains-match, but the schema explicitly documents match_mode.

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 ('Show') and resource ('owners holding marks matching a shared trademark term'), and clearly distinguishes itself from siblings by focusing on owner landscape with portfolio context. Examples like 'Which companies own a trademark for COMET?' ground the purpose.

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 includes explicit guidance on when to use the tool ('Use this for crowded owner-landscape questions...'), providing clear context. However, it does not mention alternatives or exclusions, stopping short of a full when/when-not 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.

Resources