Retrieve RunAPI pricing for any Nano Banana model to estimate costs for image editing or text-to-image tasks. Select model and endpoint for accurate rates.
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.
v0.1.12Input 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 full burden. It implies a read-only lookup but says nothing about permissions, whether pricing is live or cached, currency/units, or what the response shape is for a zero-argument-required call.
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, and the resource is named before the scope. It is efficient, though arguably under-sized for a tool with no annotations and no output schema.
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 annotations, no output schema, and no return-value description, an agent cannot know what 'pricing' means in practice (per-image cost, tiers, token rates). For a lookup tool this is a meaningful gap that the single sentence does not close.
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% with both enum parameters and their defaults documented in the schema, so the baseline is 3. The description adds only that the lookup spans a 'model line,' which slightly informs the model parameter but provides no syntax or default detail beyond the schema.
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') and resource ('RunAPI pricing') scoped to the nano-banana model line, so an agent knows exactly what it retrieves. It does not, however, explicitly differentiate itself from the sibling tools (edit_image, text_to_image) that consume that pricing.
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 guidance on when to call this versus the sibling generation tools, no mention of prerequisites, and no indication of when the information would be stale or unnecessary. An agent must infer that this is a pre-flight/cost-check step.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.