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runapi-ai
by runapi-ai

check_pricing

Retrieve pricing details for gpt-image model line to determine costs for image editing or text-to-image generation tasks.

Instructions

Look up RunAPI pricing for the gpt-image model line.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoModel slug. Defaults to the line's primary model.
actionNoEndpoint name. Defaults to the endpoint that offers the model.
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure, but it only states the basic purpose. It does not indicate whether the tool is read-only, what data is returned, if authentication is required, or any side effects. The agent lacks critical behavioral information.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that conveys the core function with no extraneous words. It is front-loaded and efficient, earning its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple lookup tool with optional parameters and no output schema, the description is adequate but not complete. It omits details about what the returned pricing information includes (e.g., per-token costs, endpoint-specific rates). The description could be improved by mentioning the output format or the scope of pricing data provided.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents both parameters with enums and descriptions. The description adds minimal value beyond confirming the model line scope. The default behavior (primary model, default endpoint) is implied but not explicitly stated, and there is no elaboration on how parameters affect the result.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool looks up pricing for the gpt-image model line. It identifies the resource (pricing) and action (look up), and the sibling tools (edit_image, text_to_image) are clearly different in purpose, so no confusion. However, 'Look up' is somewhat generic and could be more specific like 'Retrieve pricing information'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool vs alternatives. It does not mention prerequisites, when to omit parameters, or when to use sibling tools for specific actions. The agent is left to infer usage without explicit context.

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

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