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

With no annotations, the description carries the full burden. It discloses the tool returns explanations of IRT fusion, coverage counts, update cadence, and citation info. For a read-only informational tool, this is sufficient, though it does not describe response format or potential restrictions.

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 concise sentence that front-loads the purpose ('What this data is') and lists four key areas. Every word earns its place; no unnecessary information.

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 an informational tool with no parameters and no output schema, the description covers the main content areas. It does not provide an example or specify the structure of the output, but it is sufficiently complete for the tool's simple nature.

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 tool has zero parameters, so no parameter information is needed. The baseline for no parameters is 4. The description does not mention parameters, which is appropriate.

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 provides information about the aggregate: how IRT fusion works, coverage counts, update cadence, and citation. This is specific and distinct from sibling tools like get_leaderboard or get_model, which focus on querying data rather than explaining it.

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 use when background information about the aggregate is needed, but it does not explicitly state when to use this tool vs alternatives or provide context exclusions. Given the self-evident purpose, this is adequate but not exemplary.

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