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neuratechcompany-ops

Kettu Marketplace Intelligence

WB Reviews by imt_id

wb_reviews
Read-onlyIdempotent

Retrieve and sort Wildberries reviews by imt_id, with client-side reordering to surface lowest-rated feedback for complaint analysis.

Instructions

Fetch reviews by imt_id (root_id from wb_root_info).

All product variants share one review pool, indexed by imt_id NOT nmId.

The WB feedbacks endpoint returns a fixed pool (~1000 most-recent reviews, newest-first) and IGNORES server-side order params (verified Nov 2026), so sort is applied CLIENT-SIDE over that pool. To surface complaints, "worst" reorders the returned pool by lowest rating first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNo"recent"/"newest"/"default" (as returned, newest-first), "best"/"highest" (highest rating first), "worst"/"lowest"/"complaints" (LOWEST rating first — finds downsides). Reorders the ~1000-review pool WB returns, not all feedbacks.recent
limitNoMax review texts to return (1..100). Counts always full.
imt_idYesRoot ID (imt_id) from wb_root_info. All product variants share one review pool indexed by imt_id, NOT by nmId.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
metaNoValidation metadata.
sortNoClient-side sort applied: recent, best, or worst.recent
imt_idNoRoot product id (imt_id) the reviews belong to.
feedbacksNoReview items.
host_usedNoFeedbacks CDN host used.
pool_sizeNoTotal reviews in the returned pool.
valuationNoOverall valuation data.
feedback_countNoTotal feedback count from the API.
valuation_distributionNoStar valuation distribution.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.2.2

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already mark this as read-only, idempotent, and non-destructive, so the bar is lower. The description adds important behavioral details beyond annotations: the endpoint returns a fixed ~1000-review pool, is newest-first, ignores server-side order params, and applies sort client-side. This materially affects how the agent should interpret results and is exactly the kind of disclosure that helps avoid misuse.

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

Conciseness5/5

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

The description is front-loaded with the core purpose, then provides only high-value caveats in a compact sequence. Every sentence earns its place: pool indexing, fixed 1000-review pool, server-side order being ignored, client-side sort, and the 'worst' alias for complaint discovery. There is no filler or repetition of the schema.

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

Completeness5/5

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

Given the rich input schema, output schema, and annotations, the description covers the remaining behavioral context an agent needs: why imt_id matters, the bounded review pool, sort semantics, and the recommended way to find complaints. Nothing essential to calling this tool correctly is missing.

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

Parameters4/5

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

Schema description coverage is 100%, so the baseline is 3. The description adds value by explaining the conceptual relationship between imt_id and nmId, clarifying that sort operates over the fixed returned pool rather than all feedbacks, and emphasizing that 'worst' reorders by lowest rating to surface complaints. These details go beyond the schema entries.

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?

The first sentence states a specific action and resource: 'Fetch reviews by imt_id'. It also names the source of the id ('root_id from wb_root_info') and distinguishes this review pool from nmId-based lookups, which separates it from sibling tools like wb_card and wb_root_info. The purpose is immediately clear and not tautological.

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

Usage Guidelines4/5

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

The description gives clear usage context: use imt_id, not nmId, because all variants share one review pool; and it explains how sort behaves given the endpoint's fixed pool. It does not explicitly name alternatives or say 'use wb_questions for questions instead', but the practical context is strong enough for an agent to know when this tool applies.

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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