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

Annotations already confirm this is a safe read operation ('readOnlyHint: true'). The description adds critical behavioral context by specifying that the data is 'aggregate' and 'privacy-preserving,' which dictates the nature of the information the agent can expect to retrieve.

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 a single, dense sentence, making excellent use of space. It front-loads the most important constraints (aggregate, privacy-preserving) and is highly efficient.

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 lack of an output schema, the description provides a reasonable high-level overview of the *type* of data being retrieved (evidence and outcomes). It is functionally complete for a usage-level summary tool.

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%, meaning the schema provides no explanatory text. The description mentions 'selected audience' but fails to provide any semantic detail or constraints regarding the single input parameter, 'window_days,' leaving the parameter function entirely undocumented by text.

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 ('Read'), the resource ('Referee activity and outcome evidence'), and the nature of the data ('aggregate, privacy-preserving'). While clear, it doesn't explicitly differentiate this from a sibling tool like 'describe_referee' without external knowledge.

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 when summary or privacy-focused data is required ('aggregate, privacy-preserving'). However, it offers no guidance on when *not* to use this tool or how it compares to more granular sibling functions.

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