Hardened Google Workspace MCP

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 mentions the tool can 'modify text' and 'apply formatting', implying mutation, but lacks details on permissions required, error conditions (e.g., invalid indices), rate limits, or whether changes are reversible. The description adds minimal behavioral context beyond the basic operation.

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 a clear purpose statement followed by organized parameter explanations. It avoids redundancy, though the parameter list is lengthy due to the tool's complexity. Every sentence adds value, but the bulk of text is necessary for parameter clarity given the low schema coverage.

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?

For a mutation tool with 12 parameters, no annotations, and 0% schema coverage, the description does well on parameters but lacks behavioral context (e.g., error handling, auth needs). The output schema exists (returns a confirmation string), so return values need not be explained, but overall completeness is moderate due to missing usage and transparency details.

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 fully. It provides detailed explanations for all 12 parameters, including optionality (e.g., 'optional - can format existing text without changing it'), default behaviors (e.g., 'if not provided with text, text is inserted'), and examples (e.g., font family names). This adds significant meaning beyond the bare schema.

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 with specific verbs ('modifies', 'insert/replace text', 'apply formatting') and resource ('Google Doc'), distinguishing it from siblings like 'find_and_replace_doc' (which likely does only replacement) or 'batch_update_doc' (which handles multiple operations). It explicitly mentions the single-operation capability, which is a key differentiator.

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 like 'find_and_replace_doc' or 'batch_update_doc', nor does it mention prerequisites (e.g., document access permissions) or contextual constraints. Usage is implied through parameter descriptions but not explicitly stated.

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