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NeuralVerge Business Intelligence

Flipkart Product Search

run_flipkart_product_search

Search Flipkart products by keyword: id, title, brand, price, MRP, discount, image, key specs, rating and review counts. 1 point per returned record.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordYesSearch term. e.g. wireless earbuds
max_itemsNoMax items (up to 500) Default: 25.
start_pageNoStarting page Default: 1.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.2/5.0
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 return payload fields and the pricing model ('1 point per returned record'), which is genuine behavioral context. However it says nothing about pagination behavior across start_page, truncation at 500 items, or the response envelope.

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 search action and result fields, then the cost note. Nearly every clause earns its place, though the output-field enumeration is dense and could be trimmed.

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?

No output schema and no annotations, so the description's field list reasonably compensates for the missing return-value documentation. It remains incomplete on pagination semantics, per-record truncation, and what happens when a keyword yields no results.

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%, so keyword, max_items and start_page are already documented with examples and defaults. The description's field list refers to output fields, not inputs, so it adds no parameter meaning beyond the schema. Baseline 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 ('Search') and resource ('Flipkart products') with the keyword input identified. The 'flipkart' qualifier plus the field list clearly separates it from the Amazon/eBay/Walmart search siblings, though it does not explicitly distinguish itself from run_flipkart_product or 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 Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No statement of when to use this search over the sibling detail tools (run_flipkart_product, run_flipkart_product_reviews), nor any prerequisites or exclusions. The agent must infer usage purely from the name and field list.

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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