WAzion MCP Server

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden for behavioral disclosure. It mentions what data is returned but fails to disclose operational traits such as whether the operation is read-only, idempotent, cached, or subject to rate limits. The implied safety of a 'get' operation should be explicit given the absence of annotations.

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 appropriately brief and front-loaded, using a title prefix followed by the action and metric list in a single efficient sentence. The structure is clear, though the trailing '[query]' appears to be noise or a template artifact that doesn't earn its place.

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?

Given the absence of an output schema, the description partially compensates by listing the types of statistics returned (volumes, response times, etc.). However, it lacks detail on the return structure (e.g., whether data is aggregated, time-series format, or nested by agent) that would be necessary for complete understanding without an output schema.

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?

With 100% schema description coverage, the baseline score applies. The schema fully documents the period options and conditional date fields. The description adds no parameter-specific context (e.g., it doesn't explain that date_from/date_to are only valid when period='custom'), but the baseline of 3 is appropriate given the schema completeness.

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 states the tool obtains email statistics ('Obtiene estadisticas de correo electronico') and lists specific metrics returned (volumes, response times, agent breakdown, AI classification). This specificity distinguishes it from sibling tools like get_email_filter_counts or get_email_retention. However, it lacks explicit differentiation from other analytics tools, and the trailing '[query]' is ambiguous.

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 provides no explicit guidance on when to use this tool versus alternatives like get_conversation_analytics or get_agent_stats. While the listed metrics (volumes, response times) offer implicit context, there are no 'when to use' or 'when not to use' instructions, nor are prerequisites mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.