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

With no annotations, the description carries the full behavioral burden. It usefully discloses methodology (fixed 8-task suite, OpenRouter default settings, charged cost, monthly cadence), but it does not explicitly state read-only behavior, freshness beyond 'monthly', or how medians are computed.

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 that front-loads the core purpose ('Monthly measurement: dollars and tokens per completed task'). The parenthetical adds necessary methodology without becoming bloated.

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 zero parameters, no annotations, and no output schema, the description does a reasonable job listing the returned metrics: dollars/tokens per task, reasoning share, accuracy, and medians. Some ambiguity remains around 'medians' and exact response fields, but it is sufficient for an agent to understand what the tool returns.

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 the baseline is 4. No parameter semantics are needed, and the description appropriately focuses on what the tool measures rather than inputs.

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 a specific measurement resource: monthly dollars and tokens per completed task, with supporting metrics like reasoning share and accuracy. It distinguishes itself from siblings such as model_price and speed by focusing on end-to-end cost-per-task under a fixed suite, though it does not explicitly name alternative 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 gives no explicit guidance on when to use this tool versus alternatives such as model_price, speed, or open_vs_closed. Usage is only implied by the nature of the metrics, and there are no exclusions or routing instructions.

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