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myntra_product

Scrape Myntra product pages by URL to extract product name, brand, pricing, sizes, images, ratings, seller details, and offers. Returns structured JSON data.

Instructions

Scrape any Myntra product page by URL to retrieve product name, brand, MRP, pricing, available sizes, color options, ratings, images, seller details, and available offers. [Credits: 5 API credits per successful request] Notes: Product identity is embedded in the url (the numeric ID path segment before /buy, e.g. 31076617). Returns: { product_results: { productId, name, brand, mrp, country_of_origin, material, fit, overall_rating, ratings_count, images: [], sizes: [ { label, mrp, discounted_price, discount_percent, available, seller, stock } ], offers: [ { type, description } ], product_details: [ { section, content } ], reviews: [ { rating, title, comment, reviewer, helpful_count } ] } }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesURL of the Myntra product page to scrape (e.g., https://www.myntra.com/jeans/powerlook/powerlook-men-baggy-fit-mildly-distressed-jeans/31076617/buy).
htmlNoReturn the full HTML of the Myntra page instead of parsed JSON. (default: false)
Behavior5/5

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

Despite no annotations, the description fully discloses behavior: credits per request, required URL structure (numeric ID before /buy), and detailed return format including optional HTML output and nested fields.

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 front-loaded with the main purpose and includes a detailed return schema. While the return schema is lengthy, it is valuable for an agent. Minor verbosity could be trimmed but overall efficient.

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?

Without an output schema, the description enumerates the full return structure including nested objects (sizes, offers, reviews). It also covers the URL format requirement, making it complete for proper tool use.

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 100%, but the description adds significant meaning beyond the schema: it clarifies the url must be a product page with a numeric ID, and explains the html parameter returns full HTML instead of parsed JSON.

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 it scrapes a Myntra product page by URL to retrieve product details, distinguishing it from sibling tools like myntra_search which handles search queries.

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 specifies to use this tool for product page URLs, includes credit cost, and explains URL format. While not explicitly excluding alternatives, the context of siblings (e.g., myntra_search) makes the usage clear.

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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