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NeuralVerge Business Intelligence

Rakuten item reviews

run_rakuten_items_reviews

Customer reviews of a Rakuten Ichiba item by shop_code/item_code or URL: rating, text, author, dates, helpful count, purpose tags, SKU, media and shop replies. 1 point per returned record.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemYesItem (shop_code/item_code) or URL. e.g. sawaicoffee-tea/ac-sale-1960
max_itemsNoMax items (up to 500) Default: 10.
start_pageNoStarting page Default: 1.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior3/5

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

No annotations, so the description carries the full burden. It usefully discloses a cost model ('1 point per returned record') and enumerates returned fields, but says nothing about authentication, rate limits, or pagination behavior, and doesn't clarify whether the call mutates anything.

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 tightly packed sentences, front-loaded with the tool's purpose. The long returned-field enumeration earns its place given the absence of an output schema, though it is a dense list rather than prose.

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?

With no output schema, the description compensates by enumerating the returned review fields and disclosing per-record cost, which is enough for an agent to call it correctly. Gaps remain around pagination semantics and any auth/limits context.

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 the schema already documents item, max_items, and start_page. The description restates the accepted identifier formats (shop_code/item_code or URL) but adds no new syntax or semantics beyond the schema, so baseline 3 applies.

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

Purpose5/5

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

States a specific verb+resource (customer reviews of a Rakuten Ichiba item) plus the accepted identifier formats, which cleanly separates it from siblings like run_rakuten_items and run_rakuten_items_search. An agent can identify this as the reviews-fetch tool without opening the schema.

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?

Usage is only implied by the resource name; there is no explicit when-to-use vs. alternatives, no note that this is the Rakuten counterpart to run_ebay_product_reviews / run_walmart_product_reviews, and no guidance on prerequisite steps (e.g., obtaining item codes).

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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