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 return type ('A formatted list of messages') but lacks critical details: whether this is a read-only operation, if it requires specific permissions, rate limits, pagination behavior (despite a 'page_size' parameter), or error conditions. For a search tool with zero annotation coverage, this is insufficient.

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 brief and front-loaded, with the core purpose stated in the first sentence. The second sentence adds return value information efficiently. There's no wasted text, though it could be more comprehensive without sacrificing conciseness.

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 (4 parameters, 2 required), no annotations, 0% schema description coverage, but with an output schema present, the description is partially complete. It covers the basic purpose and return format, but misses parameter explanations, usage context, and behavioral details. The output schema helps, but gaps remain for effective tool selection and invocation.

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 schema provides no parameter documentation. The description adds no information about the four parameters (query, space_id, user_google_email, page_size), such as what the query syntax is, whether space_id is optional, or what user_google_email represents. It fails to compensate for the schema's lack of descriptions.

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: 'Searches for messages in Google Chat spaces by text content.' This specifies the verb ('searches'), resource ('messages'), and scope ('Google Chat spaces'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'search_gmail_messages' or 'search_docs', which would be needed for 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. It doesn't mention sibling tools like 'search_gmail_messages' for email or 'search_docs' for documents, nor does it specify prerequisites or appropriate contexts. The agent must infer usage from the tool name alone.

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