create_list
Create a new contact list in MailerCloud.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | List name,required | |
| api_key | No | MailerCloud API key | |
| list_type | Yes | List type (number),required |
Mailercloud
TDQS
C2.8/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=false, destructiveHint=false, and idempotentHint=false, which establish this is a non-idempotent write operation. The description adds no behavioral context beyond what annotations already convey — it doesn't clarify API key requirements, what happens on duplicate names, or how list_type affects behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single efficient sentence with no wasted words, which earns some credit. However, it is under-specified for a tool that creates a resource — it lacks any qualifiers about list_type values or usage context, making it brief rather than genuinely informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 3 parameters (2 required), no output schema, and a description that merely states the action. With no output schema, the agent gets no information about what a successful response looks like. list_type is an integer with no enumerated values or explanation of valid options, which is a meaningful gap for correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with name and list_type documented as required parameters. The description adds no extra meaning beyond the schema; however, the schema already documents parameter presence and types, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Create') with a clear resource ('new contact list') and platform scope ('in MailerCloud'). It clearly distinguishes from sibling tools like delete_list and update_list, though it doesn't explicitly differentiate from other create_* siblings like create_contact or create_tag.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternative create tools or when existing lists should be updated instead. There are no exclusions, prerequisites, or context that would help an agent decide between create_list and update_list or list_contact_lists.
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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TDQS
B3.4/5.0
Disambiguation4/5
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.
Naming Consistency4/5
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.
Tool Count2/5
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.
Completeness4/5
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.