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 return format ('chats with unread messages and recent message previews'), but doesn't specify behavioral details like whether it includes archived chats, group vs. individual chats, or pagination. With annotations covering safety, a 3 is appropriate—the description adds some value but not rich behavioral context.

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 front-loaded with the core purpose in the first sentence, followed by return details and usage examples in two additional concise sentences. Every sentence adds value without repetition or fluff, making it efficient and well-structured.

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 simplicity (0 parameters, read-only operation), annotations covering safety, and the presence of an output schema (which handles return value documentation), the description is complete. It clearly states the purpose, usage context, and return format, leaving no gaps for an AI agent to understand and invoke the tool correctly.

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?

There are 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description doesn't mention parameters, which is appropriate. Baseline for 0 parameters is 4, as it avoids unnecessary clutter while being complete for this tool's structure.

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 specific action ('Get a summary') and resource ('all unread WhatsApp messages'), distinguishing it from siblings like 'whatsapp_get_messages' (general message retrieval) and 'whatsapp_list_chats' (listing chats regardless of read status). The phrase 'chats with unread messages and recent message previews' further clarifies the scope.

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 explicitly provides usage guidance with examples ('Great for "catch me up" or "what did I miss" requests'), indicating this tool is for catching up on missed activity rather than general message browsing or sending. This helps differentiate it from alternatives like 'whatsapp_get_messages' or 'whatsapp_send'.

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