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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds genuinely new behavioral context: the data is live/right-now, and the count semantics caveat (a 1-GPU price can come from a node with one free GPU) warns about aggregation interpretation. It does not discuss rate limits or freshness latency, but the lower bar set by annotations makes this a solid 4.

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?

Three tight sentences with the return shape front-loaded, followed by usage and the parameter caveat. No filler, and the most decision-relevant information leads.

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?

There is no output schema, and the description compensates by naming the exact returned fields (min/median/max price, free GPU count). With optional params and annotations covering the safety profile, an agent has everything needed to call and interpret it correctly.

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 100%, so the baseline is 3. The description goes beyond the schema by explaining why count matters and the subtlety that a single-GPU quote may reflect a node with only one free GPU, which affects interpretation of results. The country param gets no added semantics, keeping this from a 5.

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?

States a specific verb+resource (live GPU prices) and enumerates exactly what is returned: min/median/max USD per GPU-hour plus free GPU count per model. It also explicitly contrasts itself with search_gpus, so an agent can distinguish it from the sibling without reading either schema.

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?

Gives concrete use cases ("what does an H100 cost", comparing models) and names the alternative tool with its selecting condition: use search_gpus to pick a node to rent. Both when-to-use and when-to-use-something-else are covered.

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