Hardened Google Workspace MCP

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: it returns structured results with IDs and web links, supports pagination via page_token, and mentions manual verification capabilities. However, it does not cover aspects like rate limits, authentication requirements, or error handling, leaving some gaps for a tool with no annotations.

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 well-structured and appropriately sized, with a clear opening sentence followed by bullet-point-like sections for Args and Returns. Every sentence adds value, such as explaining pagination and return format. Minor improvements could include merging some details into a more fluid paragraph, but overall it is efficient and front-loaded.

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 complexity (4 parameters, no annotations, but with an output schema), the description is largely complete. It covers input semantics, behavioral traits like pagination, and output format, though the output schema likely handles return values. It could be more complete by addressing authentication or error scenarios, but it provides sufficient context for effective use.

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?

Schema description coverage is 0%, so the description must compensate. It adds meaningful semantics for all parameters: 'query' supports Gmail search operators, 'user_google_email' is required, 'page_size' defaults to 10, and 'page_token' is for pagination with usage instructions. This goes beyond the bare schema, though it could provide more detail on query syntax or email format validation.

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 specific verbs ('searches messages') and resources ('in a user's Gmail account'), distinguishing it from siblings like 'get_gmail_message_content' or 'draft_gmail_message'. It explicitly mentions what it returns (Message IDs, Thread IDs, Gmail web links) and supports (pagination), making the purpose unambiguous.

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 implies usage for searching Gmail messages with a query, but does not explicitly state when to use this tool versus alternatives like 'search_docs' or 'search_drive_files'. It mentions pagination support, which provides some context, but lacks guidance on prerequisites (e.g., authentication) or exclusions compared to other Gmail-related tools.

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