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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description goes beyond them by disclosing a conditional behavior — the cost-efficiency figure only appears 'where a build cost or known GPU street price exists' — and by noting the response carries source credit and a canonical URL.

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?

Two sentences, zero waste, with the primary output (fastest measured result) front-loaded and the conditional metric following. Nothing to trim.

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?

With no output schema, the description usefully sketches the return payload (fastest result, tok/s per euro, source credit, canonical URL). A caller still doesn't know the result object's shape, but for a simple two-parameter read tool this is close to sufficient.

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 coverage is 100%, with both `model` and `limit` fully documented in the schema, so the schema does the heavy lifting. The description adds no syntax or format detail (e.g., substring matching behavior) beyond what is already structured.

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 and resource ('Return the fastest measured RigBase result for a model') and adds the derived metric scope (tok/s per euro). It is clear what the tool produces, though it never names the sibling tools it differs from.

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 implies the use case (finding the best GPU for a given model) but gives no explicit when-to-use/when-not guidance or routing to can_it_run, get_build, or search_builds. Selection between this and its siblings is left to inference.

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