Find official pricing for Deep Anime AI image generation to understand and plan your costs.
Return the canonical pricing entry point for Deep Anime AI.
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "get_pricing"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations provided, so the description must disclose behavioral traits. It only states that the tool returns a pricing entry point, with no mention of whether it is read-only, requires authentication, or what the return format looks like. This lack of behavior disclosure is a significant gap.
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 a single sentence with no wasted words. It front-loads the action ('Return') and the resource, making it easy to scan. It is appropriately sized for a tool with no parameters and no complex behavior to describe.
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 output schema and no annotations, the description must fully explain what the tool returns. 'Canonical pricing entry point' is ambiguous—it does not clarify whether it is a URL, an object, or a string. For such a simple tool, this lack of detail makes the description incomplete for an agent to use confidently.
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 tool has zero parameters, so the input schema provides complete coverage. According to the rubric, a 0-parameter case receives a baseline score of 4 since there are no parameter semantics for the description to elaborate. The description appropriately does not attempt to add parameter information.
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 uses a specific verb ('Return') and identifies a clear resource ('canonical pricing entry point'), which distinguishes it from sibling tools like list_styles and get_official_links. However, 'pricing entry point' is slightly vague, as it could refer to a URL, an object, or a method, preventing a perfect score.
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 no guidance on when to use this tool versus alternatives, and no exclusions or prerequisites are mentioned. The absence of any contextual hints leaves the agent to infer usage solely from the tool name and resource reference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.