Check your current AI credit balance, usage for the period, and reset date.
Show the current AI credit balance, usage this period, and reset date.
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_ai_credits"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.2.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly states that the tool is read-only and reports specific information (balance, usage, reset date), which is sufficient for a simple tool with no side effects. It also implicitly signals that no mutation is performed, aligning with the read-only nature.
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, concise sentence that directly conveys the tool's purpose and key information. It is front-loaded and contains no redundant or irrelevant details, maximizing clarity in minimal words.
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 tool with no parameters and a straightforward read-only purpose, the description is complete enough. It does not detail return format or exact usage specifics, but given the simplicity and lack of an output schema, the description sufficiently covers what an agent needs to know to call it correctly.
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, and the schema is empty, so there is no parameter info to add. The description effectively communicates the output content (balance, usage, reset date), which is the core value. A baseline of 4 is appropriate for a parameterless tool where the description covers the tool's purpose.
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 clearly states the tool's function: showing the current AI credit balance, usage for the period, and the reset date. It uses a specific verb ('show') and clearly identifies the resource ('AI credit balance'), making it distinct from sibling tools that handle posts, accounts, or content generation.
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 a read-only information retrieval context, and with zero parameters, usage is straightforward. It provides clear context for what the tool reports but does not explicitly state when to prefer it over alternatives, which is acceptable given its unique scope among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.