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

With no annotations, the description carries the behavioral burden. It discloses that throughput is based on dense vendor spec sheets and that models without defensible specs are marked unrated. It does not mention output shape, pagination, or data freshness, but the read-only, board-like behavior is reasonably clear.

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 three compact sentences with no filler. The core metric is front-loaded, the parenthetical adds necessary precision, and every sentence contributes either definition or usage guidance.

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 ranking tool with no output schema and no annotations, it explains the core computation and unrated behavior but omits parameter effects and return format details. It is adequate for selecting the tool but not fully complete for invoking it with confidence.

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% and the description does not explain any of the three parameters. 'limit' and 'min_vram_gb' are fairly self-explanatory, but 'offer_class' remains ambiguous, and the description adds no meaning to the parameters beyond their names.

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 defines the tool as a per-GPU-model ranking board that computes TFLOPS per dollar-hour from live price and FP16 throughput, and distinguishes it from a 'cheapest card' query. It lacks a formal verb like 'list' or 'return', but the resource and metric are specific enough to be identifiable.

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 explains that this tool answers 'most compute for my budget' rather than 'cheapest card', which gives clear selection context. It does not explicitly name sibling tools or state when to prefer them, but the contrast is enough to guide an agent.

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