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Nexscope Ecommerce Data MCP

Walmart Intelligence ST: walmart/product Analysis API

nexscope_data_st_walmart_product_analysis

Walmart Intelligence ST: walmart/product Analysis API.

Input Schema

NameRequiredDescriptionDefault
nameNo`searchByName` required; non-empty natural language product name
operationNoRequired; only `searchByName`, `detail`, `trend`, `salesVolume`
pageIndexNo`searchByName`, `salesVolume` starts from 1, defaults to 1; maximum 100 items per page
productIdNo`detail`, `trend`, `salesVolume` required; not empty Walmart ProductId
queryDateNoStart date in the format `yyyy-MM-dd`
queryEndDateNoEnd date, in the format of `yyyy-MM-dd`; when only the start date is given, the default is the current day

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

D1.7/5.0
Behavior1/5

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

Annotations declare readOnlyHint=false and openWorldHint=true, but the description adds nothing about behavior — no statement of what the operations return, whether calls count against quotas, or what the open-world implication means in practice. The single sentence conveys zero behavioral information beyond the name.

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?

It is a single short sentence, so there is no verbosity, but it is under-specified rather than concise — the one sentence duplicates the title and wastes the only opportunity to front-load useful information about the multi-operation interface.

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?

The tool has six parameters, an empty required list despite operation being effectively mandatory, and four distinct operations with different required fields — none of which the description addresses. With no output schema and no clarifying text, an agent cannot reliably determine how to invoke this tool from the description alone.

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%, and the schema descriptions already explain the operation-dependent requirements (name for searchByName, productId for detail/trend/salesVolume, queryDate format). The description contributes no additional parameter meaning, so the baseline 3 applies when the schema carries the full burden.

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 is essentially a verbatim restatement of the title/name ('Walmart Intelligence ST: walmart/product Analysis API'), offering no verb-plus-resource detail beyond the name. An agent learns only that this relates to Walmart product analysis, with no mention of the four supported operations (searchByName, detail, trend, salesVolume) that actually define what the tool does.

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 indication of when to use this tool versus the many siblings such as nexscope_walmart_product_detail, nexscope_walmart_search, nexscope_walmart_keyword_research, or nexscope_walmart_category_market. No prerequisites, no exclusions, no routing guidance of any kind.

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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