Granola MCP Server

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

With no annotations provided, the description carries the full disclosure burden. It successfully documents the return value composition ('document counts, date range, and unique attendees'), which is the critical behavioral trait for a stats endpoint. It does not mention rate limits or caching, but 'Get' implies read-only safety.

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 efficiently structured with the action statement front-loaded, followed by standard Args/Returns sections. Every sentence earns its place; there is no redundant or wasted text despite the docstring format.

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 low complexity (zero input parameters) and the existence of an output schema, the description provides sufficient completeness by detailing what statistics are returned. It adequately covers the scope without needing to elaborate on pagination or filtering mechanisms.

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 input schema contains zero parameters, warranting the baseline score of 4 per the evaluation rules. The 'Args: ctx' section documents standard MCP framework injection rather than user-facing parameters, so it neither adds nor detracts from user understanding.

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 opens with a specific verb ('Get') and clearly identifies the resource ('statistics about your Granola meeting data'). It effectively distinguishes from siblings like 'get_meeting' or 'list_meetings' by emphasizing aggregate 'statistics' rather than individual records or lists.

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 through the term 'statistics' (suggesting aggregate analysis), but provides no explicit guidance on when to prefer this over 'list_meetings' or 'search_meetings', nor does it state prerequisites or exclusions for use.

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