get_team_overview

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 describes what metrics are returned but doesn't address important behavioral aspects like whether this is a read-only operation (implied but not stated), potential rate limits, authentication requirements, data freshness, or error conditions. For a tool with no annotation coverage, this leaves significant gaps in understanding how it behaves.

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 perfectly concise with just two sentences that each earn their place. The first sentence clearly states the purpose and enumerates the returned metrics. The second sentence provides valuable usage guidance. There's no wasted language or redundancy, making it highly efficient and well-structured.

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 (2 parameters, no output schema, no annotations), the description does an adequate job but has clear gaps. It explains what the tool returns but doesn't address behavioral aspects or provide context about the return format. Without annotations or output schema, the agent must infer how to interpret the results. The description is complete enough for basic understanding but lacks depth for confident usage.

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 100%, so the input schema already fully documents both parameters (startDate and endDate) with their types and default values. The description doesn't add any parameter-specific information beyond what's in the schema, which is acceptable given the high schema coverage. The baseline score of 3 reflects adequate but not exceptional parameter documentation.

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 ('Get a comprehensive team overview') and lists the exact metrics returned (member count, total spend, top spenders, DAU, most-used models). It distinguishes itself from sibling tools by emphasizing it's 'the best starting point for understanding your team's Cursor usage,' positioning it as a high-level summary tool rather than detailed analytics like get_daily_usage or get_spending.

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 clear context for when to use this tool ('the best starting point for understanding your team's Cursor usage'), which implicitly suggests it should be used first before diving into more specific sibling tools. However, it doesn't explicitly state when NOT to use it or name specific alternatives for different scenarios, which prevents a perfect score.

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