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 discloses the mutation nature via '[mutation]' tag and clarifies the scope affects all AI systems (Piloto Automatico, WhatsApp Auto, manual responses). However, it lacks details on reversibility, when changes take effect, or side effects on existing conversations.

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 follows an efficient structure: summary prefix, detailed explanation of functionality, scope clarification, and mutation tag. Every sentence earns its place—the first defines the action, the second details the media types and channel, the third specifies system-wide impact. Minor redundancy exists between the prefix and first sentence.

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 single-parameter boolean toggle with no output schema and 100% parameter coverage, the description is appropriately complete. It explains what the toggle controls, the specific media types affected, the channel (WhatsApp), and the affected AI systems. No critical gaps exist for this complexity level.

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% coverage describing the boolean values, the description adds critical semantic context: it clarifies that 'auto_describe_images' actually covers PDFs and audio too, not just images, and specifies the WhatsApp channel context. This compensates for the parameter name being narrower than the actual functionality.

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 toggles automatic media analysis (images, PDFs, audio) for WhatsApp and distinguishes itself from sibling toggle_* tools by specifying the exact resource (media) and channel (WhatsApp). The prefix 'Activar/desactivar lectura automatica de medios' combined with the detailed explanation provides specific verb+resource 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?

The description provides clear context for when the tool applies (WhatsApp media) and explicitly states its blast radius ('Afecta a todos los sistemas de IA'), helping agents understand the scope. However, it lacks explicit 'when not to use' guidance or named alternatives from the extensive sibling list.

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