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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds useful context about the data itself (currency, per-token unit, the three price dimensions, included future price changes), but says nothing about freshness, completeness of coverage, or result size/ordering.

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 short sentences with no filler: the data scope and units come first, the intended uses second. Every clause carries information an agent would otherwise have to infer.

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 carries the burden of describing results, and it does so by naming the three price dimensions and the presence of announced price changes. The remaining gap is minor: it does not describe how records are ordered or how many are returned.

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 both parameters are fully documented in the schema, including an example value for search and the enum for provider. The description only implies the provider scope and adds no filtering semantics beyond what the schema already states, so the baseline 3 applies.

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 the exact resource and its contents: current list prices in USD per 1M tokens for input, cached input and output, limited to OpenAI, Anthropic and Google models, plus announced price changes. That is far more specific than the title alone. It stops short of explicitly distinguishing itself from sibling pricing tools such as get_llm_price or compare_llm_costs.

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?

It offers two concrete use cases, "find a model id" and "compare prices", which gives the agent positive selection signals. It does not state when not to use it or name an alternative such as compare_llm_costs or estimate_llm_cost, so the routing decision is still partly inferred.

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