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. It fails to clarify whether this is a read-only analysis tool or if it performs write operations to the customer record. It does not disclose latency, rate limits, or what the AI analysis entails beyond 'suggesting tags'.

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 a single sentence and appropriately brief, but it contains the placeholder '[query]' at the end, which appears to be an editing error or template residue, significantly degrading the structure.

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 8 parameters with complex options (summary types, time ranges, translation), no annotations, and no output schema, the description is insufficient. It does not explain the return value (suggested tags? applied tags? summary text?) or how the parameters interact with the tagging behavior.

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?

While schema coverage is 100% (baseline 3), the description creates confusion rather than clarity. The parameters include 'summary_type', 'tone', and 'target_language' (suggesting summarization/translation functionality), but the description mentions only tagging, creating a semantic mismatch that the description does not resolve.

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 states the tool uses AI to analyze conversations and suggest tags, providing a specific verb and resource. However, it is unclear whether the tool actually applies tags (implied by 'auto-etiquetar') or merely returns suggestions ('sugiere'). The trailing '[query]' placeholder appears to be template debris, reducing clarity.

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?

No guidance is provided on when to use this tool versus siblings like 'add_customer_tag' (manual tagging) or 'get_ai_summary'. There are no stated prerequisites, exclusions, or workflow context.

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