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 includes a '[mutation]' tag indicating a write operation, but fails to disclose consequences (permanent deletion, irreversibility), side effects, or authorization requirements.

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?

Extremely efficient structure with the purpose front-loaded ('Delete AI Correction'). The em-dash separation and '[mutation]' tag are appropriately placed. No redundant or filler text.

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 single-parameter deletion tool with complete schema coverage, but lacks ecosystem context (relationship to get/update AI error tools) and output behavior description.

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 100% description coverage for the 'id' parameter. The description adds no additional parameter semantics, but the baseline score of 3 is appropriate given the complete schema documentation.

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 action (Delete/Remove) and resource (AI correction). It clarifies the specific scope (corrections that are 'no longer valid'), though it doesn't explicitly differentiate from the sibling `delete_customer_ai_error` tool.

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Provides only an implied condition ('no longer valid') for usage. Lacks explicit guidance on when to choose this over `update_ai_error` or `set_ai_error`, and doesn't state prerequisites like needing the correction ID from `get_ai_errors`.

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