IvedaAI: MakeModel

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful response semantics ('status', 'truncated', 'timedOut') that go beyond annotations, but does not disclose pagination, data format, or auth requirements.

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?

The description is compact, with three sentences covering context, response semantics, and the operation. The initial sentence is somewhat generic but not redundant, and the structure is reasonably front-loaded.

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 simple one-operation GET tool, the description covers the operation and response flags, but lacks details on the returned data structure or any query parameter usage. Since there is no output schema, additional return-value detail would improve completeness.

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?

All five parameters have descriptions in the schema, including the operation enum listing the only valid operation. The description adds the endpoint path but no further parameter-level detail, so it relies on the schema's high coverage.

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 states a specific operation: 'GET /api/make-models — Find make model list', clearly identifying the action and resource. It does not explicitly distinguish this tool from sibling tools, but the operation is unique and self-explanatory.

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 usage for retrieving the make model list via a GET request, but provides no explicit when-to-use guidance, alternatives, or exclusions. It is clear enough for an agent to infer the primary use case.

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