WhatsApp MCP for macOS

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows this is a safe read operation. The description adds useful context about the real-time nature and source (live connection vs. database), which goes beyond the annotations. However, it doesn't describe behavioral aspects like rate limits, authentication requirements, or response format, leaving room for improvement.

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 efficiently structured: a clear purpose statement, context about real-time vs. database, usage guidance, and parameter details in a labeled 'Args' section. Every sentence adds value without redundancy, and it's front-loaded with the core functionality. No wasted words or unnecessary elaboration.

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 the tool's moderate complexity (one parameter, read-only operation), the description is quite complete. It covers purpose, usage, and parameter semantics effectively. Since there's an output schema (per context signals), the description doesn't need to explain return values. However, it could improve by mentioning sibling tools or potential errors, keeping it from a perfect score.

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 schema has 0% description coverage, so the description carries the full burden. It explains the 'since_minutes' parameter clearly: 'Look back N minutes (default 5, max 60).' This adds essential semantics beyond the schema's basic type and title. With only one parameter well-documented, it compensates adequately for the schema gap, though a perfect score would require more detail on constraints 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's purpose: 'Get recent incoming WhatsApp messages from the live connection.' It specifies the resource (WhatsApp messages) and verb (get), and distinguishes it from database-stored messages. However, it doesn't explicitly differentiate from sibling tools like 'whatsapp_get_messages' or 'whatsapp_search_messages', which prevents a perfect score.

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 usage context: 'These are real-time messages, not from the local database. Useful for checking new messages that just arrived.' This tells the agent when to use this tool (for real-time, recent messages) versus alternatives that might access stored data. However, it doesn't explicitly name alternative tools or specify when NOT to use it, keeping it from a score of 5.

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