Google Workspace MCP VE

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 the tool's read-only, diagnostic nature by detailing what it shows (e.g., table dimensions, cell content) and how to interpret output, though it doesn't mention potential errors, rate limits, or authentication needs. No contradictions exist, as it aligns with the implied debugging purpose.

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 (e.g., 'USE THIS IMMEDIATELY WHEN,' 'WHAT THIS SHOWS YOU,' 'WORKFLOW INTEGRATION'), making it easy to scan. It is appropriately sized for a debugging tool, though some redundancy exists (e.g., reiterating usage in multiple sections), which slightly reduces efficiency.

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 as a debugging utility with no annotations but an output schema (implied by context signals), the description is complete. It thoroughly explains the tool's purpose, usage guidelines, behavioral traits, and output interpretation, compensating for the lack of annotations and leveraging the output schema to avoid needing to detail return values.

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 100%, so the schema already documents all three parameters (user_google_email, document_id, table_index). The description does not add any parameter-specific details beyond what the schema provides, such as explaining how table_index interacts with table selection. Baseline 3 is appropriate when the schema handles parameter documentation adequately.

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 as an 'ESSENTIAL DEBUGGING TOOL' for when 'tables don't work as expected,' specifying it reveals table structure details like dimensions, cell positions, and content. It distinguishes itself from sibling tools like 'create_table_with_data' or 'append_table_rows' by focusing on inspection rather than creation or modification.

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 explicit usage scenarios with bullet points (e.g., 'Table population put data in wrong cells,' 'Need to understand existing table structure') and integrates into a workflow with steps like 'After creating table → Use this to verify structure.' It clearly indicates when to use it versus alternatives, such as planning for 'populate_existing_table.'

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