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damientilman

Mailchimp MCP

get_campaign_click_details

Read-only

Retrieve per-link click data for a sent campaign, showing which URLs were clicked and how many times. Analyze engagement by URL with total and unique click counts.

Instructions

Retrieve per-link click data for a campaign showing which URLs were clicked and how many times.

Use to analyze which links drove engagement. Use get_campaign_report instead for aggregate totals (opens, clicks, bounces). Use get_email_activity for per-recipient click timelines. Only works for sent campaigns.

Args: campaign_id: The Mailchimp campaign ID (e.g. 'abc123def4'). Must be a sent campaign. count: Number of URL results to return (1-1000, default 20).

Returns: JSON with total_items and links array. Each link: url (string), total_clicks (int, includes repeat clicks), unique_clicks (int, one per subscriber), click_percentage (decimal 0-1).

Example: get_campaign_click_details(campaign_id="abc123") -> {"total_items": 5, "links": [{"url": "https://example.com", "total_clicks": 120, "unique_clicks": 95, "click_percentage": 0.019}]}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNo
accountNo
campaign_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the tool is clearly non-destructive. The description adds behavioral context such as including repeat and unique clicks, click percentage, and constraints like requiring a sent campaign. This adds value beyond annotations.

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 with clear sections (purpose, usage, args, returns, example). Every sentence adds value, and it is front-loaded with the purpose.

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 that an output schema exists, the description does not need to detail return values, but it still provides an example and explains each field. It also covers prerequisites and usage context, making it complete for a read-only retrieval tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must explain parameters. It adequately explains campaign_id (with example and requirement) and count (range and default). However, the optional 'account' parameter is not mentioned, leaving it undocumented.

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 retrieves per-link click data for a campaign, specifying the verb 'Retrieve' and resource 'per-link click data'. It distinguishes from siblings like get_campaign_report and get_email_activity by mentioning their different scopes.

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 'Use to analyze which links drove engagement' and provides alternatives for aggregate totals and per-recipient timelines. Also notes prerequisite: 'Only works for sent campaigns.'

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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