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Suriya-Ravichandran

Amazon India Product Research MCP

search_web

Search the web for product, competitor, price, and supplier research. Returns live web results from DuckDuckGo or configured search engines to support Amazon India product opportunity analysis.

Instructions

Search the web for product, competitor, price and supplier research. Uses DuckDuckGo by default (free, no API key); Brave, Serper, Tavily and Google Programmable Search are supported when a key is configured. Returns live web results, not Amazon data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
regionNoin-en
max_resultsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses the default provider (DuckDuckGo), free usage without API key, and that it returns live web results as opposed to Amazon data. This gives the agent critical behavioral knowledge about data source and limitations that are not apparent from the schema.

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 three sentences long, all informative. It front-loads the core purpose, then provides provider details and ends with a key distinction. No wasted words or filler.

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?

A search tool with a simple schema and an output schema present. The description covers the main context: purpose, providers, and what it returns. Given the simplicity, it is reasonably complete, though it could add more on how to select providers or handle errors, but these are minor gaps.

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 coverage is 0%, so the description must add meaning to the parameters. The description mentions the query scope (product, competitor, price, supplier) and providers, which gives context to the 'query' parameter. However, it does not explain the 'region' parameter (e.g., format 'in-en' or how it affects results) or 'max_results' beyond the default. The description adds some value but does not fully compensate for the lack of schema descriptions.

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?

The description clearly states the tool's purpose: 'Search the web for product, competitor, price and supplier research.' It lists the specific domains it covers. It does not explicitly differentiate from siblings like 'search_suppliers' or 'research_product', but it clarifies it returns 'live web results, not Amazon data', which helps distinguish it from Amazon-scraping tools.

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 gives context on when to use it: for web research on products, competitors, prices, and suppliers. It notes it uses DuckDuckGo by default and supports other providers, which implies usage when a provider key is configured, but it doesn't explicitly state when to use an alternative tool or what specific conditions would make another tool more appropriate.

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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