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

The description adds significant behavioral context beyond the annotations: it notes the free beta charge ($0.00), explains that costs depend on token emission which varies by model, and highlights the comparability of standard_bench versus production_mixed. This is valuable context for interpreting the data and aligns with readOnlyHint and idempotentHint. No contradiction with annotations.

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 detailed and informative, covering purpose, usage context, licensing, and an example URL. While each sentence adds value, it is slightly verbose and could be tightened. The main purpose is front-loaded, but the extra details on licensing and example could be considered secondary. Overall, it is well-structured but not maximally concise.

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 data retrieval tool with an output schema, the description covers everything an agent needs: what data is returned, how to interpret it (standard_bench vs production_mixed), usage guidance, and licensing. The schema covers parameter details, and the output schema covers return values. Nothing essential is missing.

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 already provides a complete description for the 'days' parameter (measurement window in days, default 30), and schema coverage is 100%. The tool description does not add any additional parameter semantics. Per the baseline rule, when schema coverage is high, a score of 3 is appropriate since the description does not need to compensate.

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 returns measured platform cost metadata for one call on each model. It identifies the resource (cost data) and the action (measured). However, it does not explicitly differentiate from sibling tools like compare_models or list_models, so it lacks explicit sibling distinction. The purpose is unambiguous but would benefit from referencing related 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?

The description explicitly states when to use the tool: 'use that to choose a model before bulk work.' It also warns against using production_mixed data for comparisons, clarifying when not to rely on the data. This provides clear guidance without naming alternatives, but it effectively routes the agent to the appropriate use case.

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