check_pricing

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

With no annotations, the description must disclose behavioral traits. It correctly characterizes it as a lookup, implying read-only, but does not mention permissions, rate limits, or whether results are cached. The minimal description is adequate but does not exceed expectations.

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 sentence that directly states the tool's function with no unnecessary words or repetitions. It is optimally concise.

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 pricing lookup with optional parameters, the description captures the core purpose. However, it does not mention that parameters are optional or that defaults apply, which could leave an agent unsure about what happens if no arguments are provided.

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 input schema has 100% coverage with parameter descriptions already defining defaults and enums. The tool description adds no new meaning about how parameters affect pricing results, so it meets the baseline but provides no extra value.

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 uses a specific verb ('look up') and resource ('pricing'), and identifies the exact model line ('gpt-image-2'). It clearly distinguishes from sibling tools like edit_image or text_to_image, which perform actions rather than lookups.

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?

While the sibling names imply this is for pricing queries rather than image editing, the description provides no explicit guidance on when to use this tool versus alternatives, nor any conditions or prerequisites.

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