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NeuralVerge Business Intelligence

Flipkart Seller

run_flipkart_seller

Get the Flipkart seller offering a given product: name, rating, years on Flipkart, units sold, quality/speed scores, product/service quality ratings and description. Flat 5 points per successful run.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
productYesItem ID or product URL. e.g. itm4d0125d9c2c65

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior3/5

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

No annotations exist, so the description carries the full burden. It usefully discloses the return fields and the cost ('Flat 5 points per successful run'), which adds real context, but says nothing about error behavior, whether results are cached, or any auth/rate-limit constraints on this read 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?

One front-loaded sentence stating the purpose and returned fields, followed by a short cost note. The field enumeration is dense but informative rather than wasteful; nothing is truly redundant.

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 one-parameter read tool with no output schema, listing the returned fields compensates well for the missing output schema and the cost disclosure is a useful extra. Minor gaps remain around failure modes and any scoping limits, but an agent has enough to call it correctly.

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?

With 100% schema coverage and a single 'product' parameter fully documented in the schema (item ID or URL with example), the description adds no parameter meaning beyond what the schema already provides. Baseline 3 is appropriate.

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+resource ('Get the Flipkart seller offering a given product') and enumerates exactly what is returned, making it trivially distinguishable from siblings like run_flipkart_product and run_flipkart_product_reviews.

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?

Usage is only implied: an agent infers it should call this when it has a product and wants the seller's profile. No when-not conditions, prerequisites, or alternative routing (e.g. vs run_amazon_seller or review tools) are 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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