WAzion MCP Server

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

Adds behavioral context that only 'active' corrections are returned, which is not in annotations. However, with no annotations provided, the description carries full burden and fails to disclose read-only nature, pagination behavior, or response format.

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?

Generally front-loaded with purpose first, but contains artifact '[query]' at the end that appears to be a formatting error or placeholder. Opening is slightly redundant ('List AI Corrections — List active...').

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?

Adequate for a simple list operation with well-documented parameters. However, lacks description of return values (no output schema exists) and could better contextualize relationship to mutation siblings (update_ai_error, delete_ai_error).

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?

Input schema has 100% description coverage, establishing baseline 3. Description reinforces optional nature and filtering purpose of parameters but does not add syntax details, examples, or meaning beyond what schema already provides.

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?

States specific verb (List) and resource (active AI corrections for this assistant). Distinguishes from sibling 'get_customer_ai_errors' by scoping to 'this assistant', though terminology mismatch between 'errors' in name and 'corrections' in description slightly reduces 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?

Provides explicit guidance on when to omit parameters ('To list ALL corrections, pass no parameters') and when to use them ('Only use category or query when filtering specific results'). However, lacks explicit comparison to sibling alternatives like get_customer_ai_errors or delete_ai_error.

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