Get pricing
get_pricingGet Photo AI Studio credit-package and subscription pricing, plus the credit cost per generated photo.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
get_pricingGet Photo AI Studio credit-package and subscription pricing, plus the credit cost per generated photo.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds what data is returned (credit-package/subscription pricing and per-photo credit cost) but does not disclose other behavioral traits such as response format or data freshness. This meets the lowered bar but adds only modest extra context.
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 sentence that is front-loaded with the action and resource, and packs in the key differentiators (credit packages, subscriptions, per-photo credit cost). No filler or repetition.
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 zero-parameter, read-only, idempotent lookup with no output schema, the description is fully sufficient. An agent knows exactly what the tool does and can invoke it without needing additional context about parameters, side effects, or return shape.
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?
There are zero parameters, so the schema already trivially covers 100% of parameters. The description adds no parameter-specific detail, but none is needed. The zero-parameter baseline of 4 applies, and the description clearly states what the tool returns, making the lack of param docs irrelevant.
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 has a specific verb ('Get') and resource ('Photo AI Studio credit-package and subscription pricing'), and explicitly enumerates what is included ('credit cost per generated photo'). This clearly distinguishes it from siblings like get_service_overview and get_api_capabilities, which could otherwise overlap.
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 implies the use case: when an agent needs pricing information. However, it does not explicitly state when to use this tool versus alternatives, nor does it mention any exclusions or conditions. For a simple zero-parameter lookup tool, the implied context is adequate but not explicit.
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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