get_pricing

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key traits: it returns 'current published' pricing, notes that rates vary by media type (images vs. video), mentions the data source ('hardcoded from the official docs'), and warns about potential drift and the need for verification. This covers most behavioral aspects for a read-only pricing tool.

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 front-loaded with the core purpose in the first sentence, followed by supporting details. Every sentence earns its place by clarifying pricing units, data source, and reliability warnings. It is appropriately sized with no wasted words.

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 tool's simplicity (0 parameters, no annotations, but with an output schema), the description is complete. It covers purpose, usage context, behavioral details like data source and limitations, and output semantics. The presence of an output schema means the description doesn't need to explain return values, so this is sufficient.

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 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds value by explaining the semantics of the returned pricing data (e.g., 'per-image for images and per-second for video'), which goes beyond the schema. A baseline of 4 is appropriate for zero-parameter tools with high schema 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 clearly states the tool's purpose: 'Return current published Gemini API pricing for the models this server uses.' It specifies the verb ('Return'), resource ('Gemini API pricing'), and scope ('models this server uses'), distinguishing it from sibling tools like generate_image or submit_video that perform different operations.

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 for when to use this tool: to get pricing information for API operations. It implies usage before 'expensive operations' but does not explicitly state when not to use it or name alternatives among sibling tools, which would be needed for a score of 5.

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