Look up RunAPI pricing for Nano Banana image editing and text-to-image models to estimate costs before generating images.
Look up RunAPI pricing for the nano-banana model line.
| Name | Required | Description | Default |
|---|---|---|---|
| model | No | Model slug. Defaults to the line's primary model. | |
| action | No | Endpoint name. Defaults to the endpoint that offers the model. |
Changes observed during successful MCP inspections.
v0.2.0Input schema / additionalPropertiesRemoved value: -falseInput schema / properties / model / enumRemoved value: -[
- "nano-banana-2-lite",
- "nano-banana-edit",
- "nano-banana",
- "nano-banana-2",
- "nano-banana-pro"
-]v0.1.12Input schema / properties / model / enumPrevious value: -[
- "nano-banana-edit",
- "nano-banana",
- "nano-banana-2",
- "nano-banana-pro"
-]New value: +[
+ "nano-banana-2-lite",
+ "nano-banana-edit",
+ "nano-banana",
+ "nano-banana-2",
+ "nano-banana-pro"
+]v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. 'Look up' implies a non-mutating read, which is helpful, but the description does not confirm read-only behavior, describe the shape of the pricing result, or mention any caching/rate-limit behavior. For a simple lookup this is acceptable but thin.
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?
A single front-loaded sentence with no filler. The resource and scope are stated immediately with zero redundancy.
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 two-optional-parameter read tool this is close, but with no output schema the description should say what pricing information is returned (per-endpoint cost, units, currency). That gap leaves the agent unsure what to expect from the call.
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 documented in the schema, including the defaults and the endpoint enum. The description adds no syntax, format, or defaulting detail beyond what the schema already provides, so the baseline of 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?
States a specific verb ('look up'), resource ('pricing'), and scope ('nano-banana model line'), which is enough for an agent to distinguish it from the sibling tools (login, edit_image, text_to_image, get_task), none of which concern pricing. It is clear but does not explicitly contrast itself with an alternative.
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?
There is no statement of when to call this versus alternatives, no preconditions, and no exclusions. Usage is only implied by the tool's name and the resource it targets.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.