gworkspace-mcp

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden but offers limited behavioral insight. It mentions validation types and DROPDOWN-specific behavior (values as list), but doesn't disclose critical traits like whether this overwrites existing validation, requires edit permissions, has rate limits, or returns confirmation. For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding its effects.

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 brief and front-loaded with the core purpose. Both sentences are functional: the first establishes the tool's scope, and the second provides essential parameter guidance. There's no redundant or verbose language, though it could be more structured (e.g., bullet points for validation types).

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 moderate complexity (5 parameters, mutation operation) and lack of annotations, the description is minimally adequate but incomplete. It covers validation types and a key parameter nuance, yet omits behavioral context, prerequisites, and error handling. The presence of an output schema reduces the need to describe return values, but overall context for safe and effective use is insufficient.

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 but only partially does. It explains validation_type options (DROPDOWN, CHECKBOX, NUMBER, DATE) and clarifies that 'values' should be a list for DROPDOWN, adding meaning beyond the schema's generic types. However, it doesn't address other parameters (spreadsheet, sheet_name, range_a1) or detail format requirements (e.g., A1 notation), leaving half the parameters semantically unclear.

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 action ('Add data validation') and specifies the resource (spreadsheet cells via validation types). It distinguishes from siblings like sheets_format or sheets_conditional_format by focusing on validation rules rather than formatting or protection. However, it doesn't explicitly mention the spreadsheet context beyond the tool name, which slightly reduces specificity.

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 doesn't mention prerequisites (e.g., spreadsheet must exist), compare to similar tools (e.g., sheets_protect for cell locking), or specify use cases (e.g., data entry forms). The only implicit usage hint is for DROPDOWN validation, but overall guidance is minimal.

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