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NeuralVerge Business Intelligence

Flipkart Product Reviews

run_flipkart_product_reviews

Get customer reviews for a Flipkart product: rating, title, text, author, date, location, certified-buyer flag, helpful/downvote counts and photos. 1 point per returned record.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
productYesItem ID or product URL. e.g. itm235cd318bde73
max_itemsNoMax items (up to 500) Default: 10.
start_pageNoStarting page Default: 1.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It usefully discloses the billing model ('1 point per returned record') and the exact return shape, which is real behavioral information. But it omits pagination behavior, whether reviews are sorted or deduplicated, and any failure mode for an invalid product id.

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

Conciseness5/5

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

Two compact sentences: the field list first, then the cost note. Nothing is repeated and nothing is padded. It is appropriately sized for a simple 3-param read tool.

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 simple reviews-fetch with no output schema and no annotations, the description covers purpose, fields, and the non-obvious point cost. It is nearly complete; only pagination/ordering behavior and where to get a product ID are unstated.

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% – product, max_items (max 500, default 10), and start_page are all documented in the schema. The description adds the return-field list rather than param detail, so the schema does the heavy lifting, but the description's field enumeration still helps the agent judge whether a call is worth its cost.

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 (Get) and resource (customer reviews for a Flipkart product), and enumerates the returned fields. It maps directly onto the sibling pattern, so an agent can place it immediately: it is the reviews-fetcher paired with run_flipkart_product and run_flipkart_product_search.

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 naming convention across siblings makes the when-to-use path obvious (fetch reviews for a product ID/URL), but the description never says so, nor does it name run_flipkart_product as the way to obtain the item ID it needs. Usage is implied by the tool name rather than stated.

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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