Google Sheets Kanban MCP Server

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 behavior: it returns statistics (read-only operation), explains the optional filtering parameter, and details the return structure including nested data like 'tasks_by_status'. It doesn't mention potential limitations like rate limits, authentication needs, or data freshness, but provides solid operational context for a read-only statistical 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 and appropriately sized. It begins with a clear purpose statement, then provides parameter documentation, return value details, and examples. Every section adds value, though the example section could be slightly more concise. The Portuguese documentation is clear and avoids redundancy.

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 has an output schema (implied by the detailed Returns section), no annotations, and good parameter documentation, the description is quite complete. It covers purpose, parameter usage, and return structure. For a read-only statistical tool with one optional parameter, this provides sufficient context, though it could benefit from mentioning any limitations or performance considerations.

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?

The schema description coverage is 0%, so the description must fully compensate. It does this excellently: it explains the single parameter 'project' as optional, specifies it filters sprints by project name, and clarifies the default behavior when omitted. The description adds complete semantic meaning beyond the bare schema, including examples of usage with and without the parameter.

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: 'Retorna estatísticas de sprints com porcentagem de conclusão das tarefas' (Returns sprint statistics with task completion percentage). It specifies the verb ('retorna' - returns) and resource ('estatísticas de sprints' - sprint statistics) with the key metric being completion percentage. However, it doesn't explicitly differentiate from sibling tools like 'get_one_or_more_tasks' or 'list_tasks' beyond the statistical focus.

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 implied usage guidance through the optional 'project' parameter explanation: 'Se não fornecido, retorna stats de todas as sprints' (If not provided, returns stats for all sprints). This suggests when to use the parameter, but there's no explicit guidance on when to choose this tool versus alternatives like 'get_one_or_more_tasks' or 'list_tasks', nor any mention of prerequisites or exclusions.

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