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damientilman

Mailchimp MCP

get_campaign_advice

Retrieve Mailchimp's post-send feedback and algorithmic suggestions to improve campaign performance, including subject line, content, and engagement tips.

Instructions

Retrieve Mailchimp's automated post-send feedback on a campaign (subject line, content, engagement tips).

Use to surface algorithmic suggestions Mailchimp makes after looking at how a campaign performed (e.g. 'your open rate is below industry average, try shorter subject lines'). Use get_campaign_report for raw metrics. Only works for sent campaigns.

Authenticated via API key. Max 10 concurrent requests. Read-only, safe to retry. Returns 404 error if campaign_id is invalid. Returns an empty advice array if Mailchimp has no suggestions for the campaign.

Args: campaign_id: The Mailchimp campaign ID (e.g. 'abc123def4'). Must be a sent campaign.

Returns: JSON with total_items and advice array. Each entry: type ('positive' | 'negative' | 'neutral'), message (string, the advice text).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
campaign_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations, description fully covers behavior: read-only, safe to retry, error responses (404 for invalid ID, empty array if no advice), and max concurrent requests.

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?

Well-structured with purpose first, then usage, behavior, args, returns. Slightly verbose but clear. Could combine some lines for brevity.

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?

Covers all aspects: purpose, usage, behavior, parameters, output structure, error cases. Thorough for a one-parameter tool with output schema.

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%, but description explains campaign_id meaning and constraint (must be a sent campaign). Provides example format. Could add more detail but sufficient.

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?

Clearly states it retrieves Mailchimp's automated post-send feedback on a campaign, distinguishing it from sibling tools like get_campaign_report which returns raw metrics.

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 says to use for algorithmic suggestions, points to get_campaign_report as alternative for raw metrics, and limits to sent campaigns. Also mentions authentication and concurrency limits.

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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