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 and excels. It discloses critical behavioral traits: the mandatory pre-call to 'inspect_doc_structure', the requirement for a valid insertion point, data format constraints (2D list of strings, uniform columns, empty strings for empty cells), and post-creation verification with 'debug_table_structure'. This covers operational dependencies and constraints thoroughly.

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 sections like 'CRITICAL', 'MANDATORY WORKFLOW', and 'DATA FORMAT REQUIREMENTS', making it easy to follow. However, it is lengthy and includes repetitive emphasis (e.g., multiple 'CRITICAL' warnings), which reduces conciseness. Every sentence adds value, but it could be more streamlined.

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 (6 parameters, no annotations, but with an output schema), the description is highly complete. It covers purpose, usage workflow, behavioral constraints, parameter nuances, and includes an example. The output schema likely handles return values, so the description appropriately focuses on prerequisites and operational details, leaving no significant gaps.

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 baseline is 3. The description adds significant value by elaborating on 'index' (must come from 'inspect_doc_structure', never use arbitrary values) and 'table_data' (provides example format, requirements like same column count, and use of empty strings). However, it doesn't detail other parameters like 'user_google_email' or 'document_id' beyond the schema, keeping it from a perfect score.

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: 'Creates a table and populates it with data in one reliable operation.' It specifies both the creation and population actions, and distinguishes itself from siblings like 'append_table_rows' by emphasizing the combined operation rather than just adding rows to an existing table.

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, mandatory workflow steps, including calling 'inspect_doc_structure' first and using its 'total_length' as the index. It clearly states when to use this tool (after inspection) and includes critical requirements like index validity and data formatting, offering comprehensive guidance.

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