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Nexscope Ecommerce Data MCP

Amazon Search Intelligence SF: asin Summary API

nexscope_data_sf_asin_summary

Amazon Search Intelligence SF: asin Summary API.

Input Schema

NameRequiredDescriptionDefault
descNoIs descending order
last7dNoWhether to take the last 7 days; when it is `false`, use the date range
sortByNo`totalKeywordNum`、`naturalKeywordNum`、`brandKeywordNum`、`vedioKeywordNum`、`acKeywordNum`、`erKeywordNum`、`trKeywordNum`、`sumScore`、`totalNfScore`、`totalSpSocre`、`totalBrandScore`、`totalVedioScore`、`totalAcScore`、`totalTrScore`、`totalErScore`
countryNoSite: `US`, `UK`, `DE`, `CA`, `JP`, `FR`, `ES`, `IT`, `MX`, `AU`, `AE`, `BR`, `SA`US
endDateNo`yyyy-MM-dd`; works with `startDate`
pageNumNoPage number
pageSizeNoNumber per page, range 10–10000
startDateNo`yyyy-MM-dd`; takes effect when `last7d=false`
conditionsNoComma separated: `nf`, `sp`, `sb`, `sbv`, `ad`, `acAd`, `totalPeriod.in`
searchValueYesASIN codes, multiple separated by commas, up to 10, maximum length 1000 characters

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

D1.5/5.0
Behavior1/5

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

The description adds nothing beyond the annotations. Notably the annotations declare readOnlyHint=false and openWorldHint=true for what is evidently a data-retrieval endpoint, and the description offers no clarification of cost, latency, rate limits, or side effects. No contradiction is provable, but the description carries none of the behavioral burden a 10-param API needs.

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?

One short sentence with no waste, but it is empty of content rather than concise — it is a title echo rather than a front-loaded explanation of purpose and usage.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 10 parameters, no output schema, and only minimal annotations, the description should explain scope (ASIN-level keyword/traffic summary), output shape, and pagination. None of that is present, so the definition is inadequate for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema fully documents all 10 parameters (searchValue limit of 10 ASINs, country enum list, date handling, page size range). The description adds zero parameter meaning, leaving it below the baseline-3 case where the description at least complements a rich schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description restates the title verbatim ('Amazon Search Intelligence SF: asin Summary API') without adding a verb, scope, or output meaning. An agent learns only that this concerns ASIN summaries in a 'SF' dataset, not what a 'summary' contains or how it differs from siblings like nexscope_data_sf_asin_keywords or nexscope_amazon_asin_traffic_summary.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

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

There is no when-to-use guidance, no exclusions, and no named alternative. Given dozens of near-neighbor ASIN/keyword summary tools in the sibling list, the agent is left entirely to guess which to call.

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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