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ilyautov

wildberries-mcp-ru

wb_set_price

Set the base price and discount for one Wildberries product; require confirm_write to apply live changes and return an upload ID for tracking via price history tasks.

Instructions

Set price and discount for ONE product (Discounts-Prices API). WRITE.

Requires confirm_write=true (this changes your live price). A new price 3x below the old one lands the product in WB price quarantine.

Args: nm_id: product nmID. price: new base price in rubles (integer). discount: discount percent (0-99). confirm_write: must be true to actually send the change. Returns JSON: {"ok": true, "data": {"id": uploadID}} — poll wb_prices_history_tasks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nm_idYes
priceYes
discountNo
confirm_writeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.3

TDQS

A4.8/5.0
Behavior5/5

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

Beyond annotations (readOnlyHint=false, openWorldHint=true), the description adds important behavioral detail: confirm_write gates the live update, prices 3x below the old one trigger WB quarantine, and the endpoint returns an upload ID to poll via wb_prices_history_tasks. This meaningfully enriches the agent's understanding of side effects and follow-up.

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 compact and well structured: a one-line purpose, a crucial warning, an args list, and the return contract. No sentence is wasted; the quarantine caveat and polling instruction each carry operational value.

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?

For a write operation with side effects, the description covers the required confirmation flag, a domain-specific risk (quarantine), all parameter semantics, and the asynchronous response pattern. An agent has everything needed to invoke it correctly and know what happens next.

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

Parameters5/5

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

Schema description coverage is 0%, but the description compensates fully: nm_id is defined as the product nmID, price as new base price in rubles (integer), discount as percent 0-99, and confirm_write as the flag that must be true. Units, ranges, and meaning are all supplied, exceeding the bare schema types.

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?

Description names a precise action—'Set price and discount for ONE product'—and scopes it to the Discounts-Prices API. The explicit 'WRITE' marker plus 'live price' makes the tool's mutating nature unmistakable, distinguishing it from read-only siblings like wb_get_prices.

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?

Description clearly states the mandatory precondition: 'Requires confirm_write=true' and 'must be true to actually send the change.' It gives a concrete consequence (price quarantine) but does not explicitly name an alternative sibling or state when not to use it, so it stops short of full when-vs-alternative guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.