List all custom contact properties/fields defined in your account.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | Page number | |
| limit | No | Number of fields to return | |
| api_key | No | MailerCloud API key |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the operation read-only, idempotent, and non-destructive, so the description need not restate that. It adds modest context by specifying 'in your account', clarifying the scope, but it doesn't describe return shape, pagination behavior, or any other operational nuance beyond what the schema already implies.
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?
A single, clear sentence with no filler. The key action and object are front-loaded, making it immediately scannable and unambiguous.
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 simple read-only listing operation with optional pagination and auth parameters, this description is nearly sufficient. It lacks an explicit note about paginated return values or the output shape, and there is no output schema to fill that gap, but the core purpose and scope are clearly conveyed.
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 gives descriptions for all three parameters (page, limit, api_key), so schema description coverage is 100%. The tool description adds no parameter-level meaning, leaving a baseline of 3 per the calibration rule.
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?
States the specific verb 'list', the resource 'custom contact properties/fields', and the scope 'defined in your account'. It clearly distinguishes itself from sibling list tools, none of which reference custom fields.
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?
Provides no guidance on when to use this tool vs alternatives, no explicit exclusions, and no mention of conditions that would favor another tool. The only hint comes indirectly from the sibling tool names, not from the description itself.
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.
