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. It mentions using AI but fails to disclose whether this is a read-only analysis or if it writes categories back to conversations, rate limits, cost implications, or what the output format looks like (especially critical given no output_schema exists).

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 brief and front-loaded with the action, but the '[query]' fragment at the end appears to be noise or a template remnant that reduces clarity. The em-dash structure is acceptable but the artifact suggests incomplete editing.

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 tool with 8 parameters and no output schema, the description is insufficient. It fails to describe the return value (categories as JSON? Tags? Summary text?), the relationship between summary_type and categorization, or how the AI processing behaves (async vs sync).

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%, so all parameters are documented in the schema. The description adds no parameter-specific context (e.g., explaining how 'tone' or 'target_language' affect the categorization output), which is baseline acceptable when the schema is comprehensive.

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 categorizes recent conversations by topic, intent, and priority using AI. However, the trailing '[query]' appears to be a placeholder or copy-paste error that creates minor confusion, and it does not explicitly differentiate from sibling tools like 'search_conversations' or 'get_conversations_summary'.

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 provided on when to use this tool versus alternatives like 'search_conversations', 'get_sentiment_analysis', or 'get_conversations_summary'. Given the numerous sibling conversation-analysis tools, explicit selection criteria would be valuable.

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