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One1 Trademark Risk Check

listing_scan

扫描一段商品 listing 标题/文案,找出其中撞美国注册商标的词/词组并按风险分组。

用于卖家发品前一键自查整条 listing 标题是否含侵权商标词。
text: listing 标题或文案(可整段)。
nice_class: 尼斯商品类别号,可选。
返回: {summary:{高,中,低}, tro_count, hits:[{mark, risk_level, applicant, tro_alert?}]}。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
countryNoUS
nice_classNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It does disclose the return structure (summary buckets, tro_count, hits with mark/risk_level/applicant/tro_alert), which is real behavioral value, but says nothing about accuracy limits, data source, latency, or authorization needs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core action, followed by use case, parameter notes and return shape in a compact, scannable block. Every line contributes; no filler.

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?

With no annotations and no output schema, the description usefully supplies the return structure and the two key parameters. It is nearly complete; the undocumented country parameter is the main gap.

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 0%, so the description must compensate. It explains text ('listing 标题或文案,可整段') and nice_class ('尼斯商品类别号,可选'), but the third parameter, country (default US), is never mentioned — an agent would not know it can target non-US registries.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource (scan a listing title/copy) and a clear scope: find US-registered trademark words and group them by risk. The '发品前一键自查' framing implicitly separates it from the per-term siblings like trademark_text_search, though no sibling is named explicitly.

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?

Gives a clear usage context — pre-publication self-check of an entire listing title for infringing marks. However, it names no alternatives (e.g. trademark_text_search for single-word lookups) and states no when-not conditions.

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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