Get one SpicyAPI model

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

Annotations already cover readOnly, idempotent, and non-destructive behavior. The description adds that the input schema is plain JSON Schema with display-only and rate-card annotations removed, and that some input values change the price. This goes beyond annotations and gives actionable context about the data returned.

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 sentences, front-loaded with the primary purpose, then usage and pricing caveats. Each sentence adds distinct value with no redundancy or fluff.

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?

Output schema exists, and the description covers purpose, input source, and pricing behavior. It also routes to task_create for exact quotes, leaving no critical information missing for correct invocation.

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?

The single 'model' parameter has no schema description (0% coverage). The description hints at how to populate it by referencing models_list ('Reuse a complete record already obtained from models_list'), but it does not explicitly state the expected format or that it is an identifier. This partially compensates but leaves room for clarity.

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 states it returns one exact model with specific details (live input schema, pricing, policy, availability). It also distinguishes itself from models_list by instructing reuse of a record from that sibling, making the scope explicit.

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?

Provides explicit guidance: reuse a record from models_list with includeSchema, and directs that task_create is for exact price quotes while this tool's pricing is for comparisons. This clearly informs when to use this tool versus alternatives.

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