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get_open_report

Retrieve subscriber open data for Mailchimp campaigns to analyze email engagement timing and recipient activity.

Instructions

Get open details for a campaign — which subscribers opened and when.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
campaign_idYes
countNo
offsetNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The 'get_open_report' handler function, decorated with @mcp.tool(), which fetches open details for a specific Mailchimp campaign.
    async def get_open_report(campaign_id: str, count: int = 20, offset: int = 0) -> str:
        """Get open details for a campaign — which subscribers opened and when."""
        mc = get_client()
        data = await mc.get(
            f"/reports/{campaign_id}/open-details",
            params={"count": min(count, 100), "offset": offset},
        )
        members = []
        for m in data.get("members", []):
            members.append({
                "email": m.get("email_address", ""),
                "opens_count": m.get("opens_count", 0),
                "first_open": m.get("first_open", ""),
                "last_open": m.get("last_open", ""),
            })
        return _fmt({
            "campaign_id": campaign_id,
            "total_opens": data.get("total_opens", 0),
            "total_items": data.get("total_items", 0),
            "members": members,
        })
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 open details (a read operation) but doesn't cover critical aspects like pagination behavior (implied by count/offset parameters), rate limits, authentication needs, error conditions, or what 'open details' entails beyond subscribers and timestamps. This leaves significant gaps for a tool with three parameters.

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 a single, efficient sentence with zero waste. It's front-loaded with the core purpose and avoids unnecessary elaboration, making it easy to parse quickly.

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 (3 parameters, no annotations, but has an output schema), the description is incomplete. It covers the basic purpose but lacks usage guidelines, behavioral details, and parameter explanations. The output schema may help with return values, but the description doesn't reference it or provide enough context for safe and effective use.

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 schema provides no parameter descriptions. The description mentions 'campaign' (mapping to campaign_id) and implies retrieval of subscriber and time data, but doesn't explain the count and offset parameters for pagination. It adds minimal semantic value beyond what's inferable from parameter names, failing to compensate for the low coverage.

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 open details for a campaign — which subscribers opened and when.' It specifies the verb ('Get'), resource ('open details for a campaign'), and scope ('which subscribers opened and when'). However, it doesn't explicitly distinguish it from sibling tools like 'get_campaign_report' or 'get_click_report', which likely provide different types of campaign 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 (e.g., needing a campaign ID), exclusions, or comparisons to similar tools like 'get_campaign_report' or 'get_click_report'. The agent must infer usage from the name and context alone.

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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