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Nexscope Ecommerce Data MCP

Amazon Product History

nexscope_amazon_product_history

Retrieve Amazon product details by ASIN, including price, title, Item Highlights when available, main image, listing date, material, weight, variant monthly sales, and up to 12 months of monthly sales history. Triggered when users query Amazon product details, ASIN lookup, product pricing, sales rank history, monthly sales trends, product dimensions, FBA fees, product specifications, batch ASIN query, Nexscope product details, ASIN detail lookup, monthly sales data, pricing info, product specifications, FBA fees, batch ASIN query. Even if users do not explicitly mention "Nexscope", this skill should be triggered whenever the task involves obtaining structured product data for one or more Amazon ASINs.

Input Schema

NameRequiredDescriptionDefault
asinYesAmazon Standard Identification Number (ASIN), multiple ASINs separated by English commas, up to 5, max length 300 characters. Example: B0088PUEPK or B0088PUEPK,B00U26V4VQ,B07M68S376
domainYesAmazon domain ID. Options: 1 (United States), 2 (United Kingdom), 3 (Germany), 4 (France), 5 (Japan), 6 (Canada), 8 (Italy), 9 (Spain), 10 (India), 11 (Mexico), 12 (Brazil)
historyNoWhether to include historical data and historical sales in the response. 1 = include price history, sales rank, historical sales and other time-series data (sales for previous months), 0 = return only basic product information. Default: 0

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations declare readOnlyHint=false and openWorldHint=true, so the safety profile is partly covered. The description adds useful caveats such as 'Item Highlights when available' and the 12-month history cap, but says nothing about authentication, rate limits, or batch handling behavior beyond what the schema already states.

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

Conciseness2/5

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

The opening sentence is well formed, but the trigger list is badly bloated, repeating 'product specifications, FBA fees, batch ASIN query' twice within a single sentence and then restating the whole trigger idea in a trailing sentence. Significant trimming is needed to make this front-loaded and scannable.

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?

There is no output schema, and the description does list the returned fields, which is appropriate for a read tool. What it omits is the disambiguation an agent needs: with many similarly named Amazon product detail tools, the description should explain what makes this one different, and it does not.

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 100%, with asin, domain, and history fully documented including the 5-ASIN comma-separated limit and domain ID map. The description adds only the implication that history depth relates to the returned monthly sales data; the schema already does the heavy lifting, so 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 and resource (retrieve Amazon product details by ASIN) and enumerates the returned fields, including 12 months of monthly sales history, which gives it some identity. However, it never distinguishes itself from the near-identical siblings nexscope_amazon_product_detail, nexscope_amazon_market_product_detail, or nexscope_data_amazon_product_detail, so an agent cannot tell from the text which one to pick.

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 'Triggered when users query...' sentence gives usage context for triggering, which is helpful. But it is a list of keywords rather than conditions, and it names no alternative tool or when-not-to-use case, which is critical given dozens of overlapping Amazon product-detail siblings.

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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