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walmart_product

Extract product data from any Walmart product page: title, price, images, ratings, reviews, and seller details.

Instructions

Scrapes any Walmart product page by URL, retrieving title, price, images, ratings, reviews, seller info, and more. [Credits: 5 API credits per successful request.] Notes: Uses a full product page URL rather than a product ID parameter. No domain/country localization parameters documented; localization is implicit in the walmart.com URL passed. No pagination applicable. Returns: { title, description, upc, item_id, product_type, price, currency, availability, delivery_date, images: [], seller:{seller_id,seller_name,display_name}, overall_rating, review_count, ratings_distribution: [{stars,count}], categories: [{name,url}], specifications: {brand,count,active_ingredient,...} }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe full Walmart product page URL to scrape (e.g. https://www.walmart.com/ip/46480251).
Behavior5/5

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

With no annotations provided, the description fully discloses behavior: it mentions credit cost (5 per request), explains input format, notes no pagination, and provides a detailed return structure. This gives the agent clear expectations.

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 concise and front-loaded with the main purpose. It includes credits, notes, and return structure in a single paragraph. Minor improvement could be more structured formatting, but it is effective.

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 low complexity (single parameter, no output schema), the description covers all necessary aspects: purpose, input, behavior, cost, and return data. No gaps are evident.

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?

The single parameter 'url' is well-described in the schema. The description adds context that it must be a full product page URL (not an ID), which is helpful but not critical. With 100% schema coverage, the description adds moderate value.

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 scrapes Walmart product pages via URL and lists the data retrieved (title, price, images, etc.). It distinguishes from sibling tools like walmart_reviews, walmart_search, and walmart_autocomplete, which handle different functions.

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?

The description notes that a full product page URL is needed (not a product ID) and that localization is implicit, but it does not explicitly state when to use this tool versus alternatives. Usage context is implied but not directive.

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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