Google Workspace MCP Server

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions pagination ('pagination info') and implies read-only behavior through 'List', but lacks critical details: authentication requirements (Google email suggests OAuth), rate limits, error conditions, or what 'basic details' includes. For a tool with 4 parameters and no 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 well-structured with clear sections (Args, Returns) and front-loads the core purpose. Each sentence adds value, but the 'Returns' section could be more specific about output format given the output schema exists, making it slightly redundant.

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 4 parameters, 0% schema coverage, no annotations, and an output schema, the description is moderately complete. It covers parameter meanings and hints at pagination, but lacks behavioral context (e.g., auth, errors) and doesn't leverage the output schema to avoid repeating return details. For a list operation with pagination, more guidance on usage and limits would improve completeness.

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 context for all parameters: 'user_google_email' is explained as 'The user's Google email address. Required.', 'form_id' as 'The ID of the form.', and pagination parameters with defaults and purposes. This goes beyond the bare schema, though it could elaborate on format constraints (e.g., email 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 verb 'List' and resource 'a form's responses', making the purpose immediately understandable. It distinguishes from sibling tools like 'get_form' or 'get_form_response' by focusing on listing multiple responses rather than retrieving a single form or response. However, it doesn't explicitly differentiate from other list tools like 'list_docs_in_folder' or 'list_tasks', which keeps it from 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 prerequisites (like needing form access), compare to similar tools (e.g., 'get_form_response' for single responses), or specify use cases. This leaves the agent without context for tool selection.

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