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get_click_report

Analyze campaign click performance by retrieving which URLs were clicked and total click counts for each link.

Instructions

Get click details for a campaign — which URLs were clicked and how many times.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
campaign_idYes
countNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The `get_click_report` tool handler retrieves click details for a specified Mailchimp campaign, including URL-specific click stats, and formats the result.
    @mcp.tool()
    async def get_click_report(campaign_id: str, count: int = 20) -> str:
        """Get click details for a campaign — which URLs were clicked and how many times."""
        mc = get_client()
        data = await mc.get(
            f"/reports/{campaign_id}/click-details",
            params={"count": min(count, 100)},
        )
        urls = []
        for u in data.get("urls_clicked", []):
            urls.append({
                "url": u.get("url", ""),
                "total_clicks": u.get("total_clicks", 0),
                "unique_clicks": u.get("unique_clicks", 0),
                "click_percentage": u.get("click_percentage", 0),
                "last_click": u.get("last_click", ""),
            })
        return _fmt({"campaign_id": campaign_id, "total_urls": len(urls), "urls": urls})
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves click details, implying a read-only operation, but doesn't specify whether it requires authentication, has rate limits, returns paginated results, or handles errors. For a reporting tool with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves in practice.

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 extremely concise and front-loaded, consisting of a single sentence that directly states the tool's purpose. There's no wasted language or redundancy, making it easy to parse quickly. Every word earns its place by conveying essential information without unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (reporting with two parameters) and the presence of an output schema (which likely handles return values), the description is minimally adequate. However, with no annotations and low parameter coverage, it lacks details on behavior, usage context, and parameter semantics. It meets a basic threshold but has clear gaps that could hinder effective tool selection and invocation.

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?

The description doesn't mention any parameters, while the input schema has two parameters (campaign_id and count) with 0% schema description coverage. This means parameters are undocumented in both the schema and description. The description implies a campaign context but doesn't add details about parameter usage, such as format for campaign_id or that count defaults to 20. With low coverage, the description fails to compensate, resulting in minimal added value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get click details for a campaign — which URLs were clicked and how many times.' It specifies the verb ('Get'), resource ('click details for a campaign'), and scope ('which URLs were clicked and how many times'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'get_campaign_report' or 'get_member_activity', which might also involve reporting or analytics.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, such as needing an existing campaign, or compare it to similar tools like 'get_campaign_report' for broader metrics or 'get_member_activity' for user-level data. Without this context, users might struggle to choose the right tool among the many reporting-related siblings.

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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