delete_contact
Delete a contact by ID.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| api_key | No | MailerCloud API key | |
| contact_id | Yes | Contact ID,required |
Delete a contact by ID.
| Name | Required | Description | Default |
|---|---|---|---|
| api_key | No | MailerCloud API key | |
| contact_id | Yes | Contact ID,required |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare destructiveHint=true and idempotentHint=true, so the description doesn't need to repeat that. The description adds the core behavioral fact that deletion is by ID. However, it doesn't disclose side effects like whether associated data is removed or whether the deletion is permanent. With annotations covering the safety profile, this is adequate but not rich.
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?
Single sentence, no filler, front-loaded verb. Perfectly concise and clear.
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 deletion tool with annotations (destructiveHint=true, idempotentHint=true) and a fully documented schema, the description is nearly complete. It lacks explicit note on irreversibility or cascading effects, but given the tool's simplicity and annotation coverage, this is a minor 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% (both api_key and contact_id are described). The description adds a bit by specifying that the contact is deleted by ID, which matches the contact_id parameter. Since the schema fully documents parameters, the description's contribution is minimal but not incomplete. Baseline 3 for full coverage, +1 for reinforcing the required parameter's role.
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?
Description states a clear verb ('Delete') and resource ('a contact'), and identifies the required identifier ('by ID'). It is distinguishable from sibling tools like get_contact and update_contact, though it doesn't explicitly name an alternative, so it misses the strongest differentiation.
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 usage: you need a contact_id to delete a contact. It doesn't provide explicit when-to-use guidance or mention alternatives (e.g., delete_list, batch operations). The context is straightforward enough that an agent can infer intent, but there is no explicit routing.
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.