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 states the tool 'Sends a message' and returns a confirmation, implying a write operation, but fails to mention critical details like required permissions (e.g., Google Chat access), rate limits, error conditions, or whether the action is reversible. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

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 and return details in the second. There's no unnecessary verbiage, and it efficiently conveys the basic action. However, the return statement could be integrated more seamlessly, and the overall brevity comes at the cost of completeness, slightly affecting its effectiveness.

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 (a mutation operation with 4 parameters), lack of annotations, and 0% schema description coverage, the description is insufficiently complete. It doesn't explain parameter meanings, behavioral constraints, or usage context, and while an output schema exists (implied by 'Returns: str'), the description's minimal detail doesn't adequately support an AI agent in selecting or invoking this tool correctly amidst many siblings.

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%, meaning none of the 4 parameters are documented in the schema. The description adds no parameter semantics beyond the return value, failing to explain what 'space_id', 'thread_key', or 'user_google_email' represent or how they should be used. This leaves key inputs ambiguous, such as whether 'user_google_email' is the sender or recipient, and doesn't 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: 'Sends a message to a Google Chat space.' It specifies the verb ('Sends') and resource ('message to a Google Chat space'), making the action unambiguous. However, it doesn't differentiate from sibling tools like 'send_gmail_message' or 'search_messages', which would require explicit comparison to achieve 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 'send_gmail_message' for email or 'search_messages' for retrieval, nor does it specify prerequisites or contextual cues (e.g., use for real-time chat vs. other communication methods). This lack of comparative or conditional advice limits its utility for an AI agent.

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