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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds useful context about what kind of data is returned (benchmarks and common configuration issues) but does not cover auth needs, rate limits, or output format. With annotations carrying the behavioral burden, a 3 is appropriate.

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 two tightly written sentences with no wasted text. The primary purpose is front-loaded, followed by a focused usage clause, making it easy to scan and act on.

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 read-only cohort-analysis tool with no output schema, the description provides enough context to call it correctly: it identifies the inputs as a named provider cohort and describes the returned content as benchmarks and common configuration issues. It could say more about output structure or cohort matching behavior, but the essential context is present.

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 100%, so the three parameters are already documented in the input schema. The description adds some meaning to the 'provider' parameter through examples such as 'Google Workspace customers' and 'Microsoft 365 customers', but does not clarify the 'format' or 'profile' parameters beyond the schema. Baseline 3 is correct.

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 states a specific verb+resource: 'Get security benchmarks and common configuration issues' for a provider cohort. It names concrete examples like Google Workspace and Microsoft 365 customers, and the scope is clearly cohort-level rather than domain-level, helping distinguish it from generic benchmark or scan tools.

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?

It gives clear usage context: 'Use when asked how an email service provider compares to competitors on security posture, or to see typical misconfigurations for a named vendor's customers.' This tells the agent when to select the tool, though it does not explicitly name an alternative tool or state when not to use it.

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