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GleanMark Trademark Search

Search USPTO Design Codes

search_design_codes
Read-only

Find US trademarks by USPTO design code — the codes examiners assign to the visual elements of a logo (26.17.01 = straight bands, 24.11 = crowns). Accepts dotted (26.17.01) or packed (261701) form. USPTO design vocabulary is literal and narrow: it records "Bands, straight" where a person says "stripe", and has no entry for words like "swoosh", so a plain shape word resolves to a code through mode="search_codes" before marks can be counted or listed. Modes: count, top_owners, list_marks, by_serial (what codes one mark carries), describe_code, search_codes. Omitting mode infers it from the arguments supplied.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNosearch_codes = find a code from a word. describe_code = what a code means. count/top_owners/list_marks = marks carrying the codes. Omit it and the mode is inferred: query -> search_codes, serial_number/registration_number -> by_serial, codes -> count.count
codesNoDesign codes, dotted or packed, e.g. ["26.17.01"].
limitNo
matchNoall = mark carries every code. any = at least one.all
queryNoRequired for mode="search_codes". A shape word: band, bar, circle, star, triangle, chevron, crown, leaf, arrow, shield.
statusNoany
nice_classNoRestrict to one Nice class, e.g. "25".
serial_numberNoEight-digit serial number for mode="by_serial".
registration_numberNoRegistration number for mode="by_serial"; resolved to its serial number automatically.

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds useful behavioral context beyond that: it discloses that both dotted and packed code formats are accepted, that the USPTO vocabulary is literal and narrow, and that mode is inferred from arguments. This helps the agent predict behavior without contradicting annotations.

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 dense but each sentence earns its place: purpose, format examples, vocabulary quirk, mode list, and inference behavior. It is front-loaded with the core action and stays tightly organized despite covering a complex multi-mode tool.

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 tool has 9 parameters, 6 modes, and no output schema, the description covers the essential workflow (search codes first, then count/list), format variants, and mode inference. The schema's mode descriptions handle return semantics per mode. A minor gap is that no explicit return format is described in the tool description itself, but the schema compensates.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 78%, slightly below the 80% baseline, so the description helps compensate. It explains the packed/dotted form for 'codes', describes six modes with their inference rules, and provides examples. This adds meaning beyond the schema's property descriptions, especially for the mode parameter.

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 opens with 'Find US trademarks by USPTO design code', giving a specific verb, resource, and scope. It distinguishes itself from sibling search tools by focusing exclusively on design codes and their unique modes, with concrete examples like '26.17.01 = straight bands'.

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 context on when to use the tool, such as explaining that a plain shape word must go through mode='search_codes' before marks can be counted or listed. It also explains mode inference when the mode is omitted. However, it does not explicitly name alternative sibling tools or state when NOT to use this tool.

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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