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

No annotations, so the description carries the full burden. It discloses that it returns an estimate with assumptions exposed, which is meaningful behavioral context – the output is not a flat price but a derivation. It does not mention auth needs, rate limits, or what happens with unavailable GPU types, but for a read-only estimation tool that is a moderate gap.

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?

One sentence, front-loaded with the action and the data basis, with no filler. It is under-informative rather than over-long, so conciseness is high even though completeness suffers.

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?

An output schema exists, so return values need not be explained, but the description omits parameter intent (0% schema coverage) and any routing guidance among seven siblings. For a 2-required-param tool with no annotations, more is needed.

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 0% and the description mentions none of the three parameters (gpu, count, hours). 'GPU compute cost' and the tool name hint that gpu and hours are expected, but count (multi-GPU scaling) and the expected value format of gpu (slug? model name?) are undocumented in both description and schema.

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 clear verb (Estimate) and resource (GPU compute cost) and specifies the basis (observed prices). However, it gives no differentiation from siblings like gpufeed_get_cheapest or gpufeed_recommend, so an agent must infer when to use this vs. cheaper/recommend endpoints.

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?

No when-to-use, when-not-to-use, or named alternative. With seven sibling gpufeed_* tools, the absence of any routing guidance leaves the agent to guess. The phrase 'with assumptions exposed' hints at a use case but does not state conditions.

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