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A1-x-Tech

Yango Tech Retail MCP

Create or update products

create_products

Create or update up to 100 products in the Yango Tech Retail catalog with one request, specifying IDs, categories, status, and custom attributes.

Instructions

Creates (or upserts) products in the catalog (POST /b2b/v1/products/create), at most 100 per request. Each product uses the same shape query_products returns: {product_id, master_category, status, is_meta, custom_attributes}. custom_attributes must include longName ({lang: text}), shortNameLoc, markCount and markCountUnitList; extra keys are passed through. The response body is not documented upstream (2xx = success) and is returned verbatim.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
productsYesProducts to create/upsert (at most 100 per request).
Behavior4/5

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

Beyond annotations (readOnlyHint=false), the description discloses the batch limit, the POST endpoint, the requirement that custom_attributes include specific fields, pass-through of extra keys, and that the response body is undocumented and returned verbatim. This adds useful operational context without contradicting annotations.

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?

Three sentences, each earning its place: purpose and batch limit, input shape and required attributes, and response behavior. Front-loaded and clearly structured.

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?

The tool has no output schema, so the description appropriately explains the response (undocumented, 2xx = success, verbatim). It also covers the batch limit, required custom attribute keys, and pass-through, giving a complete picture for selection and invocation.

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 baseline is 3. The description repeats the required custom_attributes and pass-through behavior already present in the schema, adding no new parameter-level semantics.

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 description opens with 'Creates (or upserts) products in the catalog' — a specific verb, resource, and write/update semantics. It further distinguishes itself from sibling query_products by noting the input shape matches what query_products returns, clarifying the relationship between the two tools.

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?

Clear context is provided: this tool is for creating or updating products in the catalog, with a batch limit of 100 per request and specific required custom attributes. Although no explicit exclusions or alternatives are named, the purpose and batch nature make the usage scenario evident.

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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