Google Workspace MCP Server

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool lists labels but doesn't describe important behaviors like whether it requires authentication, how it handles errors, if there are rate limits, or what happens with large numbers of labels. For a read operation with zero annotation coverage, this leaves significant gaps.

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 appropriately sized and front-loaded, with the main purpose stated clearly in the first sentence. The Args and Returns sections add necessary structure without redundancy. It could be slightly more concise by integrating the parameter explanation into the main description, but overall it's efficient.

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 low complexity (1 parameter) and the presence of an output schema (which explains the return format), the description is somewhat complete. However, it lacks behavioral details like authentication needs or error handling, and with no annotations, it doesn't fully compensate for these gaps, making it only adequate.

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 description coverage is 0%, so the description must compensate. It adds meaning by explaining that 'user_google_email' is 'The user's Google email address' and is required, which clarifies the parameter's purpose beyond the schema's title. However, it doesn't provide details like format examples or constraints, keeping it at a baseline level.

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 with a specific verb ('Lists') and resource ('all labels in the user's Gmail account'), making it easy to understand what it does. However, it doesn't explicitly distinguish itself from sibling tools like 'manage_gmail_label' or 'search_gmail_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 no guidance on when to use this tool versus alternatives. There are multiple sibling tools related to Gmail (e.g., 'search_gmail_messages', 'manage_gmail_label'), but the description doesn't mention any context, prerequisites, or exclusions for usage.

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