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

With no annotations, the description carries full behavioral burden and exceeds expectations. It discloses important semantic details: each entry holds until the next one, and history starts when AI Wave began recording rather than at model launch. These caveats manage user expectations and are not evident from the schema or tool name.

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, all informative with no filler. The primary purpose is front-loaded, and the behavioral nuances about entry semantics and data coverage are placed after the core statement, making it easy to parse and act on.

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?

Given the simple single-parameter tool and no output schema, the description is mostly complete: it specifies the resource, the output concept, and two important caveats. It stops short of detailing the exact response structure, but such detail is arguably unnecessary for this straightforward lookup tool.

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 description coverage is 100% and the sole parameter is documented with a clear description ('OpenRouter id or Hugging Face repo id'). The tool description adds no extra param detail, so the baseline of 3 applies because the schema handles parameter semantics.

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 the tool returns price history for one model, including when the price changed and to what. It differentiates itself by emphasizing the single-model scope and the specific question it answers ('was this cheaper last month?'), which separates it from sibling tools like compare_models and list_model_changes.

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 provides clear context: the public catalog exposes only current price, so this tool is for historical price lookups. It implies the appropriate use case without explicitly naming alternatives or stating when not to use it, so the guidance is clear but not fully explicit about exclusions.

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