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 and includes '[mutation]' to indicate it's a write operation. It discloses the side effect (AI analysis and indicator display) but omits details about reversibility, whether changes apply to existing conversations or only new ones, and lacks any warning about potential data retention implications.

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 relatively compact and front-loaded with the core function. The Spanish phrase at the beginning slightly mirrors the tool name, creating minor redundancy, but the structure efficiently moves from definition to behavioral explanation. The '[mutation]' tag at the end is somewhat buried but present.

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 single-parameter toggle tool without an output schema, the description adequately covers the functional scope and visible effects. However, it omits mention of the return value (success/failure indicator) and fails to clarify temporal scope (existing vs. future conversations), which are relevant for a configuration mutation tool.

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% coverage with the parameter 'auto_sentiment_analysis' clearly documented as a boolean for activate/deactivate. The description aligns with this but does not add additional semantic context (e.g., default state, implications of toggling) beyond what the 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?

The description clearly identifies the tool as activating/deactivating automatic sentiment analysis specifically for WhatsApp conversations, distinguishing it from sibling getter tools like get_sentiment_analysis. It specifies the concrete output (satisfaction, urgency, and intent indicators in the Chrome extension) when enabled.

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?

While the description explains what happens when the feature is enabled, it lacks explicit guidance on when to use this versus manual sentiment analysis tools or one-off analysis functions. It does not specify prerequisites or conditions where this toggle should be avoided.

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