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damientilman

Mailchimp MCP

update_store_product_variant

Update a product variant's price, SKU, inventory, or other attributes in your Mailchimp e-commerce store using a single API call.

Instructions

Update an existing product variant's price, SKU, inventory, or other attributes.

Only fields supplied in additional_fields are changed. Many stores sync variants automatically via Shopify or WooCommerce integrations; these manual writes suit custom or headless storefronts.

Args: store_id: E-commerce store ID. product_id: Product ID that owns the variant. variant_id: Existing variant ID. additional_fields: Dict of documented fields to update (e.g. title, url, sku, price, inventory_quantity, image_url) merged into the request body.

Returns: JSON with the updated variant object.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
accountNo
store_idYes
product_idYes
variant_idYes
additional_fieldsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations indicate a mutation (readOnlyHint=false, destructiveHint=false). The description adds that only fields in additional_fields are changed (partial update), which is important behavioral context beyond annotations. No contradictions.

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?

The description is structured with paragraphs and includes an args/returns section. It is front-loaded with purpose but could be slightly more concise. Every sentence adds value.

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?

Given the tool has 5 parameters and an output schema, the description explains the update behavior, partial update, and return format. It covers most aspects but omits the 'account' parameter.

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?

With 0% schema description coverage, the description lists the required parameters (store_id, product_id, variant_id) and explains additional_fields with examples. However, the 'account' parameter in the schema is not mentioned in the description.

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 clearly states it updates an existing product variant's attributes like price, SKU, inventory, with a specific verb and resource. It distinguishes from siblings like create/delete/get variant.

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?

It explains that only supplied fields are changed and warns about automatic syncing from Shopify/WooCommerce, providing context for when manual updates are appropriate. However, it does not explicitly list alternatives or when not to use.

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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