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damientilman

Mailchimp MCP

list_promo_codes

Read-only

Retrieve promo codes attached to a specific promo rule for your Mailchimp e-commerce store. Get codes customers type at checkout, with details like usage count and enabled status.

Instructions

List the redeemable codes attached to a promo rule (e.g. 'SUMMER20', 'VIPONLY').

Codes are what customers type at checkout. They redeem the discount defined by the rule. A single rule can have many codes (e.g. one per customer segment).

Args: store_id: E-commerce store ID. promo_rule_id: Rule ID. Obtain from list_promo_rules. count: Number of codes to return (1-1000, default 20). offset: Pagination offset.

Returns: JSON with store_id, promo_rule_id, total_items, and promo_codes array. Each code: id, code (the string customers type), redemption_url, usage_count, enabled, created_at, updated_at.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNo
offsetNo
accountNo
store_idYes
promo_rule_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Annotations already indicate readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds the purpose and return format (JSON with store_id, promo_rule_id, etc.), but doesn't discuss pagination behavior beyond parameters or any other behavioral nuances.

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 concise and well-structured: a clear first line, a brief paragraph explaining codes, followed by Args and Returns sections. Every sentence is informative and efficient.

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 schema has 5 parameters (including account), the description covers the main ones. An output schema exists, and the description outlines the return structure. Lacks coverage of the account parameter, but overall sufficient for the tool's simplicity.

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?

Schema coverage is 0%, so the description must compensate. It explains store_id, promo_rule_id, count (range and default), and offset (pagination). This adds meaning beyond the schema parameter names, though 'account' parameter in schema is not mentioned.

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 'List the redeemable codes attached to a promo rule' with specific examples like 'SUMMER20', 'VIPONLY'. It distinguishes itself from sibling tools like create_promo_code, delete_promo_code, get_promo_code by focusing on listing.

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 codes are what customers type at checkout and that a single rule can have many codes, providing context. It also mentions obtaining promo_rule_id from list_promo_rules. However, it does not explicitly state when not to use this tool or mention alternatives.

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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