WAzion MCP Server

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

The '[mutation]' tag explicitly signals this is a write operation, which is valuable given the absence of annotations. However, it fails to disclose whether dismissal is permanent, reversible, or has side effects on the AI model's learning state.

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 uses an efficient 'Title — Details [tag]' structure with zero waste. Every word serves a purpose: identifying the action, specifying the resource, noting the optional parameter, and signaling the mutation behavior.

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 simple two-parameter mutation tool without output schema, the description adequately covers the basic operation. However, given the lack of annotations, it should clarify the persistence of the dismissal (e.g., whether it can be undone) and its relationship to the 'apply' counterpart.

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?

With 100% schema description coverage, the parameters are fully documented in the schema itself ('ID de la sugerencia a descartar' and 'Motivo del descarte (opcional)'). The description notes the optional reason ('con motivo opcional') but largely repeats the schema information without adding syntax details or examples.

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 discards/dismisses an AI training suggestion using the specific verb 'descartar'. However, while the verb inherently contrasts with sibling 'apply_training_suggestion', it does not explicitly clarify when to choose dismissal over application.

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 mentions the optional reason parameter but provides no guidance on when to dismiss a suggestion versus applying it (via apply_training_suggestion) or other alternatives. No prerequisites or exclusion criteria are stated.

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