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. While it mentions that omitting certain parameters preserves existing values and describes the return value, it doesn't address important behavioral aspects like whether this requires specific permissions, whether changes are reversible, potential rate limits, or error conditions. The description provides basic operational context but lacks comprehensive behavioral transparency for a mutation tool.

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 detailed parameter explanations and return value information. While comprehensive, it's appropriately sized for a tool with 10 parameters. The information is front-loaded with the core purpose, though the parameter details are extensive but necessary given the complexity.

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 10 parameters, 0% schema description coverage, no annotations, but with an output schema, the description provides good completeness. It explains the tool's purpose, detailed parameter semantics, and mentions the return value. The main gap is lack of behavioral context around permissions, reversibility, and error handling, but the parameter coverage is excellent and the output schema handles 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?

With 0% schema description coverage and 10 parameters (7 optional), the description provides excellent parameter semantics. It clearly explains what each parameter does, including specific details like 'A1-style range', '0-based index', 'Hex background color', 'Sheets condition type', and how omitted parameters preserve existing values. This fully compensates for the lack of schema descriptions.

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 specific action ('Updates an existing conditional formatting rule by index on a sheet'), identifies the resource (conditional formatting rule on a sheet), and distinguishes it from sibling tools like 'add_conditional_formatting' and 'delete_conditional_formatting' by specifying it updates existing rules rather than creating or deleting them.

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 implies usage by specifying it updates existing rules by index, which suggests it should be used when you have an existing rule to modify rather than creating a new one. However, it doesn't explicitly state when to use this versus alternatives like 'add_conditional_formatting' or provide any exclusion criteria or prerequisites beyond the required parameters.

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