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shop_search

搜索TikTok Shop店铺。支持按关键词或ID搜索,可按评分、销量、商品数等条件筛选。

Args:
    keyword (string): 店铺关键词或名称
    search_type (string): 搜索方式 N:ID,K:关键词
    region (string): 国家/区域,默认US
    category (string[]): 店铺类目列表
    shop_type (string): 卖家类型
    service_type (string): 运营模式
    price_from (number): 价格下限
    price_to (number): 价格上限
    rating_from (number): 评分下限
    rating_to (number): 评分上限
    products_from (integer): 在售商品数下限
    products_to (integer): 在售商品数上限
    sales_volume_from (integer): 总销量下限
    sales_volume_to (integer): 总销量上限
    sales_volume_lst30d_from (integer): 近30天销量下限
    sales_volume_lst30d_to (integer): 近30天销量上限
    sales_volume_gr30d_from (number): 近30天销量增长率下限
    sales_volume_gr30d_to (number): 近30天销量增长率上限
    influencer_from (integer): 带货达人数下限
    influencer_to (integer): 带货达人数上限
    videos_from (integer): 带货视频数下限
    videos_to (integer): 带货视频数上限
    order_field (string): 排序字段
    order_type (integer): 排序方向:0降序,1升序,默认0
    page_num (integer): 页码,默认1
    page_size (integer): 每页数量,默认20,最大100

Returns:
    object: 分页结果。
        外层: {code(string): 状态码, message(string): 提示信息, success(boolean): 是否成功, data(object): 分页数据}
        data: {total(integer): 数据总数, pageNum(integer): 当前页码, pageSize(integer): 页容, list(object[]): 结果集}
        list元素(店铺):
            id (string): 店铺ID
            shopId (string): 店铺ID
            shopName (string): 店铺名称
            imageUrl (string): 店铺图片
            link (string): 链接
            region (string): 地区
            shopType (string): 卖家类型
            serviceType (string): 运营模式
            fulfillmentType (string): 履行模式(自营/全托管)
            crossBorder (integer): 是否跨境(0:本地, 1:跨境)
            categories (string): 英文类目信息
            cnCategories (string): 中文类目信息
            rating (number): 评分
            ratingRate (number): 4+评分占比
            respondRate (number): 24小时回复率
            shipRate (number): 2天内发货概率
            shopRate (number): 超过的店铺占比
            products (integer): 在售商品数
            avgPrice (number): 在售商品平均价格
            currency (string): 货币单位
            totalSalesVolume (integer): 总销量
            totalSales (number): 总销售额
            salesVolumeLst30d (integer): 近30天销量
            salesVolumeGr30d (number): 近30天销量增长率
            salesLst30d (number): 近30天销售额
            influencers (integer): 带货达人数
            videos (integer): 带货视频数
            kolspriteUrl (string): kolsprite详情链接

Input Schema

NameRequiredDescriptionDefault
regionNo国家/区域,默认US
keywordNo店铺关键词或名称
categoryNo店铺类目列表,只支持传递一个,可选值通过product_category_list工具查询
page_numNo页码,默认1
price_toNo价格上限
page_sizeNo每页数量,默认20,最大100
rating_toNo评分上限
shop_typeNo卖家类型
videos_toNo带货视频数上限
order_typeNo排序方向:0降序,1升序,默认0
price_fromNo价格下限
order_fieldNo排序字段
products_toNo在售商品数上限
rating_fromNo评分下限
search_typeNo搜索方式 N:ID,K:关键词
videos_fromNo带货视频数下限
service_typeNo运营模式
influencer_toNo带货达人数上限
products_fromNo在售商品数下限
influencer_fromNo带货达人数下限
sales_volume_toNo总销量上限
sales_volume_fromNo总销量下限
sales_volume_gr30d_toNo近30天销量增长率上限
sales_volume_lst30d_toNo近30天销量上限
sales_volume_gr30d_fromNo近30天销量增长率下限
sales_volume_lst30d_fromNo近30天销量下限

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

No annotations exist, so the description carries the full burden. It does disclose defaults (region US, page_size 20/max 100, order_type 0) and a detailed response shape, which is useful. However it says nothing about authorization requirements, rate limits, whether results are capped, or how multiple filters combine – behavior an agent would want before calling.

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

Conciseness2/5

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

The opening two sentences are well front-loaded, but the Args section duplicates all 26 schema parameters verbatim, which is pure token waste at 100% coverage. The Returns section is warranted given no output schema, but overall the definition is bloated by redundancy.

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?

For a 26-parameter search tool with no output schema and no annotations, the definition supplies defaults, pagination limits, and a thorough return-field breakdown. Gaps remain around filter combination logic and valid enumerations for string fields, but an agent has enough to invoke it correctly.

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%, so every parameter is already documented in the schema and the Args block is a near-verbatim restatement. The description adds no extra semantics beyond the schema (e.g. it never explains valid values for shop_type, service_type, or order_field), so the baseline 3 applies.

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?

States a specific verb+resource (搜索TikTok Shop店铺) and clarifies the two search modes (keyword or ID) plus the filterable dimensions. An agent can distinguish it from product_search, creator_search, and video_search siblings without opening any schema.

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

Usage Guidelines3/5

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

Usage is implied by the tool's nature (searching shops with optional filters), but there is no explicit when-to-use/when-not guidance and no routing to alternatives such as creator_search for people or product_search for items. It also does not say when keyword vs ID search_type should be chosen, only what the codes mean.

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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