Get inbox placement tracking data for a date range, optionally filtered by campaign or domain. Helps monitor deliverability across email providers.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | No | Filter by domain | |
| api_key | No | MailerCloud API key | |
| date_to | Yes | End date (YYYY-MM-DD),required | |
| date_from | Yes | Start date (YYYY-MM-DD),required | |
| campaign_id | No | Filter by campaign ID |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds context about date range filtering and monitoring purpose, but does not disclose return format or pagination behavior. Since annotations carry the behavioral burden, a score of 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?
Two sentences convey the core action, scoping, and purpose with no redundant words. The key filtering constraints are front-loaded, making it easy 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 read-only, non-destructive list-type tool with fully documented parameters and safe annotations, the description is mostly sufficient. It lacks details on what specific tracking metrics are returned, but the absence of an output schema and the simple nature of the tool keep this from being a major gap.
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?
Schema description coverage is 100% and each parameter has a clear description. The tool description mentions date range and optional filters, which aligns with the parameters, but does not add meaning beyond the schema itself. Baseline 3 is appropriate.
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 clearly identifies a specific verb ('Get') and resource ('inbox placement tracking data'), and specifies the scope ('for a date range, optionally filtered by campaign or domain'). This distinguishes the tool from sibling tools like get_campaign_domain_report which targets a different data focus.
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 is for monitoring deliverability across email providers, which gives a clear use case. However, it does not explicitly state when to prefer this over sibling tools or mention exclusions, though the purpose is sufficiently distinct.
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.
