Send a test email for a campaign to specified recipients before the actual send.
| Name | Required | Description | Default |
|---|---|---|---|
| api_key | No | MailerCloud API key | |
| recipients | Yes | Test email recipients,required | |
| campaign_id | Yes | Campaign ID,required |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate the operation is not read-only and not idempotent, and the description matches that by stating an email will be sent. It adds the useful context that this is a test delivery before the real send, but does not elaborate on side effects such as whether recipients receive actual email, rate limits, or if any state is changed beyond the annotation booleans.
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, well-constructed sentence that states the action, target, and timing with zero wasted words. It is front-loaded with the verb and object, making it easy for an agent to scan quickly.
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?
For a straightforward tool with two required parameters, no output schema, and no nested objects, the description covers the core action well. However, it omits any note about return value or failure behavior, and there is no mention of prerequisites (e.g., campaign existing) or whether the test send affects campaign metrics, so the context is adequate but not fully complete.
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 has 100% description coverage for all three parameters, including required fields and the 'recipients' array. The description adds no additional parameter-level meaning, so a baseline score of 3 is appropriate given the schema already documents the parameters thoroughly.
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 ('Send'), a clear resource ('a test email for a campaign'), and states the purpose ('before the actual send'). It leaves no ambiguity about what the tool does and distinguishes it naturally from sending the real campaign email.
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 phrase 'before the actual send' implies the tool should be used as a pre-flight check, giving some usage context. However, it does not explicitly state when not to use it or contrast it with alternatives like 'send_transactional_email' or 'schedule_campaign', so guidance is implied rather than explicit.
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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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.
