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geekbi-temu-research-mcp

by geekbi

temu_review_search

Search and filter genuine reviews for a specific Temu product by rating, SKU, helpfulness, and date to analyze buying motives, usage scenarios, and improvement directions.

Instructions

查询一个明确 Temu 商品 ID 的真实评论,可限定站点、SKU规格、1至5星评分、有用数、评论时间并按评论时间、有用数、评分或采集时间排序,用于分析购买动机、使用场景、正向卖点、差评原因、规格风险、时间变化和产品改良方向;不能用于全站找商品。用户没有明确商品 ID时先用商品搜索定位,不猜测。默认按评论时间降序看最新评论;高参考价值评论按 helpful 降序;差评痛点筛选1至3星后按 helpful 降序,严重问题可看1至2星;正向卖点筛选4至5星后按 helpful 降序;规格差异使用 skuId或规格分组。全量研究逐页读取,单页最多200,最多前10000条,超出时按评分、规格或时间分批;部分分页的评分结构只能称为样本。total为0只表示极鲸云当前条件下暂未收录,不能解释为商品没有评论或质量好坏。分析时把主题出现次数与低评分、高有用数代表的严重度分开;有用数表示参考价值,不代表观点频率;问题集中于特定规格时不能归因整个商品;未实际查看图片或视频时不能描述媒体内容;评论时间是发表时间,采集时间不是。只依据实际评论,避免单条评论外推;优先使用多条独立、跨规格重复、近期持续且有较高有用数的证据。用户要求明细时用中文列名完整保留所有返回字段和空值。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations provided, the description carries full burden and excels: it discloses pagination limits (200 per page, 10000 max), default sorting, the meaning of total=0, helpfulness as reference value not frequency, comment time vs collection time, and analytic caveats about not overgeneralizing.

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?

The description is very long and dense, but every clause carries practical value, covering operational limits and analytical warnings. It is somewhat unstructured as a single block, but not wasteful; a slight structure improvement would make it perfect.

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?

Given the tool's complexity and the presence of an output schema, the description covers usage limits, pagination, data interpretation caveats, and output handling (Chinese column names, preserving nulls). It is complete enough for correct invocation and result interpretation.

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

Parameters5/5

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

Schema coverage is reported as 0%, so the description compensates by explaining how to use filters (e.g., score ranges for different purposes, helpful sorting, SKU grouping) and pagination strategy. It adds strategic meaning beyond the schema's structural definitions.

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 queries real reviews for a specific Temu product ID, listing filtering and sorting capabilities. It explicitly distinguishes itself from whole-site product search, which differentiates it from sibling search tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives explicit when-to-use guidance (analyzing purchase motives, use cases, positive/negative aspects, etc.) and when-not-to-use (not for whole-site product search), directing users to product search first if no ID is available. It also provides tactical advice on sorting and filtering.

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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