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get_walmart_product_details

Scrape Walmart product details using ScrapingBee.

Scope: one query per call. To run many queries in one pass, or to write results to disk instead of into the conversation, use the ScrapingBee CLI — scrapingbee <command> --input-file queries.txt --output-dir results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagNoResponse-header label only.
deviceNoThe device to use for the request (desktop, mobile, tablet).desktop
domainNoThe domain to use for the search (Example: com, ca, com.mx, etc.) for localization.
add_htmlNoWhether to return the HTML along with the product details.
store_idNoSpecific Walmart store ID for localization.
product_idYesThe unique identifier for the Walmart product.
screenshotNoForce a browser screenshot (returns base64 image).
delivery_zipNoThe zip code to use for delivery localization.
light_requestNoWhether to use a light request or not.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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 discloses the third-party scraping backend and the one-query-per-call scope, which is useful, but says nothing about credential/auth requirements, credit or rate-limit costs, or failure/timeout behavior for a paid scraping call. Adequate but materially incomplete.

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?

Two short sentences, front-loaded with the core action and followed by the scope constraint and the CLI alternative. The inline CLI example is slightly verbose but earns its place by being immediately actionable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be explained, and the parameter surface is fully documented. However, for a 9-parameter paid scraping tool with zero annotations, the description omits cost/credit implications, auth prerequisites, and error behavior, leaving gaps an agent should know before invoking.

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% with 9 well-documented parameters, including defaults for device, domain, store_id, delivery_zip, add_html, screenshot, and light_request. The description adds no parameter meaning beyond the schema, so the baseline of 3 applies.

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 and resource ('Scrape Walmart product details') and names the backing service (ScrapingBee), which is enough to distinguish it from sibling listing tools like get_walmart_search_results. It stops short of explicitly contrasting with those siblings, so it lands at 4 rather than 5.

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 an explicit usage constraint ('Scope: one query per call') and names a concrete alternative with its condition (use the ScrapingBee CLI for many queries or disk output). It does not address when to prefer this over get_walmart_search_results or get_amazon_product_details, so guidance is clear but not complete.

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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