Generate a comprehensive email marketing best practices report based on your actual campaign performance data. Shows your performance vs industry benchmarks, identifies top-performing patterns (subject lines, send times, audience size), highlights improvement areas with specific numbers, and provides prioritized actionable recommendations tailored to your data.
| Name | Required | Description | Default |
|---|---|---|---|
| api_key | No | MailerCloud API key |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, providing a clear safety profile. The description adds detail about the report contents but does not disclose any additional behavioral traits such as data access requirements or output formatting. It does not contradict annotations, so a 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, tightly packed sentence that front-loads the core purpose and then concisely enumerates the report's components. Every phrase adds meaningful information and there is no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the single parameter, full schema coverage, and no output schema, the description successfully conveys what the report covers and how it is derived. It lacks an explicit statement about the return data format, but the detailed content list largely compensates, making it nearly complete for invocation purposes.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema fully documents the single parameter (api_key) with 100% coverage, so the description does not need to repeat it. The description provides no additional parameter-level insight beyond what the schema already states, matching the baseline for complete schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Generate') and names a concrete resource ('email marketing best practices report'), clearly distinguishing it from sibling analysis tools like analyze_campaign or compare_campaigns. It enumerates what the report contains, leaving no ambiguity about the tool's function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool should be used when a user wants best-practice recommendations based on campaign data, but it does not explicitly contrast with sibling tools or state when not to use it. Usage context is implicit rather than explicit, earning a mid-level score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Tool purposes are largely distinct, with clear separation between CRUD operations, analytics, and deliverability tools. Some overlap exists between get_campaign, analyze_campaign, and campaign_health_dashboard, but descriptions clarify scope sufficiently.
Most tools follow a consistent verb_noun pattern (list_, get_, create_, update_, delete_, send_). Minor exceptions like campaign_health_dashboard and engagement_funnel are descriptive but break the pattern.
With 47 tools, this is a very large surface area. While the variety reflects the breadth of email marketing operations, the count exceeds what is typically manageable and suggests potential redundancy or over-scoping.
The tool set covers most core workflows: contact/list management, campaign lifecycle, templates, webhooks, analytics, and transactional email. Minor gaps like no delete for templates or tags are acceptable but not fatal.
