Google Workspace MCP VE

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. While it mentions the tool can 'write, update, or clear values,' it fails to describe critical behavioral traits such as required permissions (e.g., edit access to the sheet), whether changes are reversible, rate limits, or error handling. For a mutation tool with no 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 extremely concise and front-loaded, consisting of a single sentence that directly states the tool's purpose. There is no wasted language or redundancy, making it efficient and easy to parse. This level of brevity is appropriate given the tool's straightforward function and comprehensive schema documentation.

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?

The description is minimal but adequate for a tool with a rich input schema (100% coverage) and an output schema (implied by 'Has output schema: true'). However, it lacks details on behavioral aspects like permissions, side effects, or error cases, which are important for a mutation tool. Given the structured data support, it meets a basic threshold but could be more informative to fully guide an AI agent.

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 100%, meaning all parameters are well-documented in the input schema. The description does not add any meaningful semantics beyond what the schema provides (e.g., it doesn't explain the interaction between 'values' and 'clear_values' or provide examples of valid range formats). Given the high schema coverage, a baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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: 'Modifies values in a specific range of a Google Sheet - can write, update, or clear values.' It specifies the verb ('modifies'), resource ('Google Sheet'), and scope ('specific range'), making it easy to understand. However, it does not explicitly differentiate from sibling tools like 'format_sheet_range' or 'read_sheet_values', which is why it doesn't 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 does not mention sibling tools like 'read_sheet_values' for reading data or 'format_sheet_range' for formatting, nor does it specify prerequisites or exclusions. This lack of contextual guidance makes it harder for an AI agent to select the appropriate tool in a given scenario.

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