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. It correctly identifies the operation as a [mutation] and lists which fields are mutable (content, category, status), but fails to disclose error handling (e.g., what happens if the ID doesn't exist), authorization requirements, or whether the operation is idempotent.

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 appropriately concise and front-loaded, though slightly redundant with 'Update AI Correction — Update an existing AI correction.' The bracketed [mutation] tag efficiently communicates the operation type without verbose explanation. Each sentence serves a distinct purpose: identifying the operation, scoping the updatable fields, and tagging the mutation type.

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 this is a 4-parameter mutation tool with 100% schema coverage and no output schema, the description meets minimum requirements by identifying the resource and mutable fields. However, it lacks completeness regarding the optional nature of non-ID parameters (only implied by 'Can change'), error scenarios, or what constitutes a successful update.

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 the schema has 100% description coverage (establishing a baseline of 3), the description adds valuable semantic mapping by clarifying that 'fact_content' represents the 'content' and explicitly listing the valid status values (active/rejected) and category options, helping the agent understand the domain concepts beyond the raw parameter names.

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 specific action (Update) and resource (AI correction/existing AI correction), distinguishing it from sibling tools like delete_ai_error or set_ai_error by emphasizing 'existing' and 'update' versus create/delete operations. However, it doesn't explicitly clarify when to use this versus the similar 'set_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?

The description provides no guidance on when to use this tool versus alternatives like set_ai_error or delete_ai_error, nor does it mention prerequisites such as needing a valid correction ID. The [mutation] tag hints at side effects but doesn't constitute usage guidance.

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