WAzion MCP Server

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

With no annotations provided, the description carries the full burden of behavioral disclosure but fails to define what constitutes an 'unsatisfactory' answer (e.g., low confidence scores, fallback triggers, or no matching intent). It also omits critical operational details such as the return format, pagination behavior, or whether results are sorted by recency or relevance.

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 compact and front-loaded with the key concept ('Preguntas sin respuesta adecuada'), but the single-sentence structure is overly terse given the lack of annotations and output schema. The bracketed '[query]' at the end is unnecessary and detracts from clarity without adding value.

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 annotations and output schema, the description should compensate by explaining the 'unanswered' detection logic, return structure, and the relationship between time-based parameters (period vs. hours). It provides none of this context, leaving significant gaps for an agent trying to invoke the tool correctly.

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 has 75% description coverage (plugin_type, period, and hours are documented; limit has only a default value). The description text adds no substantive explanation for these parameters or their interactions—for example, it does not clarify how the 'period' enum relates to the 'hours' integer, or what 'query' in the bracketed text refers to. With the schema doing most of the work, this meets the baseline.

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 'Identifica preguntas donde el bot no pudo dar una respuesta satisfactoria' (identifies questions where the bot could not give a satisfactory answer), providing a specific verb and resource. However, it loses a point because the text omits the 'plugin' context (present only in the tool name), which would help distinguish it from siblings like `get_unanswered_conversations`, and the trailing '[query]' appears to be an artifact or placeholder that adds confusion.

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 such as `get_recent_plugin_questions` (which retrieves all recent questions regardless of answer status) or `get_product_qa_questions`. While the purpose implies usage for quality assurance or gap analysis, there are no stated conditions, prerequisites, or exclusions.

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