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

Annotations already declare readOnly/idempotent/non-destructive, and the description adds context beyond them: it is free, requires no token (auth requirement), and 'changes nothing' (side-effect confirmation). It does not mention rate limits or freshness/latency guarantees of the 'live' data, so it falls short of a 5.

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?

A single compact sentence that front-loads the scope ('by GPU family') and the returned fields, then closes with cost/auth/side-effect facts. No filler or redundancy.

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 zero-param tool with no output schema, the description enumerates the key return fields well enough to plan a call. It omits output shape/ordering details, but that is a minor gap given the tool's simplicity.

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?

Zero parameters with full schema coverage, so there is nothing for the description to disambiguate. Baseline 4 applies; the description correctly signals a parameterless call by not implying filters.

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 market summary by GPU family') and names the returned metrics: cheapest price per GPU-hour, GPUs available, machines. An agent can tell it is an aggregate market view rather than a per-item query, though it does not explicitly contrast with siblings like search_gpus or list_instances.

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?

'Live market summary' implies when it is useful (current pricing/availability overview), but there is no explicit when-to-use vs when-not, nor any pointer to search_gpus or list_instances for per-GPU detail. Usage is inferable rather than stated.

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