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google_serp_shopping: GET /

hasdata_google_serp_shopping_getSearchResults

Scrape Google Shopping search results to retrieve product listings with titles, prices, ratings, merchants, thumbnails, and filter chips for e-commerce price tracking, catalog building, and product data collection.

Instructions

Get Shopping Search Results

Scrapes Google Shopping listings for a query with location/uule, country/language/domain, time/date filters, device type, shoprs filter-helper IDs, and offset pagination. Returns product title, price, merchant/source, rating, reviews count, thumbnail, product link, productId, immersiveProductPageToken, and filter chips with hasdata_link for refining by brand/price/condition/promotions. Use for e-commerce price tracking, catalog building, promotion discovery, and feeding productIds into the Product API or tokens into the Immersive Product API for deeper data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesSpecify the search term for which you want to scrape the SERP.
locationNoGoogle canonical location for the search.
uuleNoThe encoded location parameter.
domainNoGoogle domain to use. Default is google.com.
glNoThe two-letter country code for the country you want to limit the search to.
hlNoThe two-letter language code for the language you want to use for the search.
tbsNoThis parameter supports various filters that can be combined by separating them with a comma. Here are examples of these filters: - Specific Time Range: `cdr:1,cd_min:10/17/2018,cd_max:3/8/2021` - Filter results to show only those within the defined date range. - Sort by Date: `sbd:1` - Results are sorted by date, from the most recent to the oldest. - Sort by Relevance: `sbd:0` - Results are sorted by relevance to the search query. - Sites with Images: `img:1` - Only show results from webpages that contain images. Quick Date Range (qdr): - `qdr:h` - Show results from the past hour. - `qdr:d` - Limit results to the past day. - `qdr:w` - Filter results from the week. - `qdr:m` - Display results from the past month. - `qdr:y` - Show results from the past year. - `qdr:h10`, `qdr:d10`, `qdr:w10`, `qdr:m10`, `qdr:y10` - Specify a number to show results from the last 10 hours, days, weeks, months, or years respectively. These filters enhance the control over search results, allowing for precise retrieval of information based on specific criteria.
shoprsNoSpecifies the helper ID for applying search filters. Must be used with the updated `q` parameter, which includes the selected filter (e.g., Coffee sale). To apply filters, use the `hasdata_link` from `filters[index].options[index]` in the JSON. Apply multiple filters by following each `hasdata_link` one by one. To remove a filter, follow its specific `hasdata_link`.
deviceTypeNoSpecify the device type for the search.
startNoThis parameter specifies the number of search results to skip and is used for implementing pagination. For example, a value of 0 (default) indicates the first page of results, 40 refers to the second page, and 80 to the third page.
Behavior4/5

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

With no annotations, the description carries full burden. It discloses the scraping behavior, parameter usage (location, filters, pagination), and return fields (product title, price, etc.). It does not mention rate limits or errors but sufficiently explains the tool's operation.

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 well-structured with a clear title, a paragraph on functionality, a list of return fields, and use cases. Each sentence adds value, though it could be slightly more concise without losing information.

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 complexity (10 parameters, no output schema), the description adequately explains the tool's capabilities, return values, and how results can be used in downstream APIs. It omits details about response structure (e.g., JSON format, pagination metadata) but remains sufficient for an agent to decide invocation.

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 100%, so baseline is 3. The description adds value by explaining how parameters like 'shoprs' and 'tbs' work, and by grouping related parameters (e.g., 'time/date filters'). It does not repeat all parameter descriptions but enhances understanding beyond the schema.

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 explicitly names the tool's purpose ('Get Shopping Search Results') and details the resource ('Google Shopping listings') with specific verbs ('Scrapes'). It distinguishes from siblings by specifying 'Shopping' as opposed to other Google SERP tools like general search or news.

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 use cases (e.g., 'e-commerce price tracking, catalog building, promotion discovery') and suggests how to chain with other tools ('feeding productIds into the Product API'). However, it does not explicitly state when not to use this tool or compare it to alternatives like the general search 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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