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damientilman

Mailchimp MCP

get_store_product_variant

Read-only

Retrieve a single product variant to view its price, SKU, and inventory details. Use to inspect variant attributes.

Instructions

Retrieve a single product variant with its price, SKU, and inventory details.

Use to inspect one variant's attributes. Use list_store_product_variants to browse and discover variant_ids.

Authenticated via API key. Max 10 concurrent requests. Read-only, safe to retry.

Args: store_id: E-commerce store ID. product_id: Product ID that owns the variant. variant_id: Variant ID. Obtain from list_store_product_variants. account: Optional account name (e.g. 'marketing') configured via MAILCHIMP_API_KEY_. Omit to use the default account. See list_accounts.

Returns: JSON with the variant object.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
accountNo
store_idYes
product_idYes
variant_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Description adds value beyond annotations by specifying 'Read-only, safe to retry', 'Max 10 concurrent requests', and 'Authenticated via API key'. Annotations only provide hints (readOnlyHint=true, destructiveHint=false), so description enriches behavioral context. However, 'safe to retry' contradicts idempotentHint=false annotation.

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?

Well-structured with front-loaded purpose, followed by usage, auth, args, and returns. Every sentence adds value, no redundancy. Appropriate length for a single-variant retrieval tool.

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 tool with 4 parameters and an output schema, the description covers all necessary context: what it does, how to get variant IDs, authentication, concurrency limits, parameter explanations, and return format. No gaps.

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 compensates by explaining each parameter: store_id is 'E-commerce store ID', product_id is 'Product ID that owns the variant', variant_id comes from list_store_product_variants, and account is optional with configuration details. This adds meaningful context beyond the bare schema.

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 the tool retrieves a single product variant with its price, SKU, and inventory details, using precise verb 'Retrieve' and resource 'product variant'. It distinguishes itself from the sibling list_store_product_variants by specifying this is for a single variant.

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

Usage Guidelines5/5

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

Explicitly tells when to use this tool ('inspect one variant's attributes') and when to use the alternative ('Use list_store_product_variants to browse and discover variant_ids'). Also provides authentication and concurrency context.

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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