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damientilman

Mailchimp MCP

list_store_orders

Fetch order details from a connected e-commerce store, including totals and fulfillment status. Use count and offset to paginate results.

Instructions

List orders from a connected e-commerce store with totals and fulfillment status.

Requires an active integration. Use list_store_customers for customer-level aggregates instead.

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

Args: store_id: E-commerce store ID (alphanumeric string). Obtain from list_ecommerce_stores. count: Orders to return (1-1000, default 20). offset: Pagination offset. Use when total_items exceeds count.

Returns: JSON with total_items and orders array. Each: id, customer (email), order_total (float), currency_code (ISO 4217), financial_status, fulfillment_status, processed_at_foreign, lines_count.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
store_idYes
countNo
offsetNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

No annotations provided, so description carries full burden. It clearly states read-only nature, retry safety, concurrency limits, and return format. Discloses requirement for active integration.

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?

Description is concise and well-structured with clear sections: main purpose, prerequisites, alternative, authentication, args, and returns. No unnecessary words.

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 tool's moderate complexity (3 parameters, 1 required, output schema exists), the description covers purpose, usage, parameters, behavior, and return format completely. No gaps.

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 coverage is 0%, but description documents each parameter with additional meaning: store_id is E-commerce store ID (alphanumeric) obtainable from list_ecommerce_stores; count specifies range 1-1000 with default 20; offset explained for pagination.

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 states 'List orders from a connected e-commerce store with totals and fulfillment status.' This provides a specific verb and resource, and explicitly distinguishes from sibling tool list_store_customers.

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?

Description includes when to use ('Requires an active integration'), provides alternative ('Use list_store_customers for customer-level aggregates'), and specifies authentication ('Authenticated via API key'), concurrency limits ('Max 10 concurrent requests'), and safety ('Read-only, safe to retry').

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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