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

With no annotations, the description must carry the full burden. It states what the tool does but does not disclose behavioral traits such as whether authentication is required, how errors are handled (e.g., unknown model), or any rate limits. The description adds little beyond the name and schema.

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 a single, focused sentence that conveys the essential information without redundancy. It is front-loaded and appropriately sized for the tool's simplicity.

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?

The description adequately explains what the tool returns (input/output pricing per 1M tokens) but lacks context about how this differs from sibling tools, such as estimate_cost. Given the absence of an output schema, a bit more detail about the response structure or usage scenarios would improve completeness, though the tool is straightforward.

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 parameter 'model' has a clear description with examples. The tool description adds no additional meaning beyond the schema, making it redundant. Since the schema already documents the parameter well, the baseline of 3 is appropriate.

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 verb ('Get') and resource ('pricing per 1M tokens for a specific AI model'), specifying input/output pricing. This distinguishes it from siblings like count_tokens and estimate_cost, which focus on token counting or cost estimation rather than rate lookup.

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 guidance is provided on when to use this tool versus alternatives. For example, it does not clarify that estimate_cost is for computing cost based on usage while this tool returns the underlying rate card. The description implies usage only through its purpose statement, but no explicit context or exclusions are given.

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