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credit_balance

Check remaining credits for AI detection and plagiarism scans to verify availability before batch content analysis operations.

Instructions

Check your Originality.ai credit balance. Returns remaining credits available for scanning. Use before batch operations to verify you have enough credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The main handler function that executes the credit_balance tool logic. It calls the client's get_credit_balance() method, extracts the balance from the result, and returns it as formatted TextContent.
    async def handle_credit_balance(
        arguments: dict[str, Any],
        client: OriginalityClient,
    ) -> list[TextContent]:
        """Check credit balance."""
        result = await client.get_credit_balance()
        balance = result.get("credits", result.get("balance", "unknown"))
        return [TextContent(type="text", text=f"**Originality.ai Credit Balance:** {balance}")]
  • Tool definition with name 'credit_balance', description explaining its purpose, and inputSchema showing it requires no input parameters (empty object with no properties).
    Tool(
        name="credit_balance",
        description=(
            "Check your Originality.ai credit balance. Returns remaining credits "
            "available for scanning. Use before batch operations to verify you have "
            "enough credits."
        ),
        inputSchema={
            "type": "object",
            "properties": {},
            "required": [],
        },
    ),
  • Registration mapping where the tool name 'credit_balance' is mapped to its handler function handle_credit_balance in the HANDLERS dictionary.
    "credit_balance": handle_credit_balance,
  • Client helper method that makes the actual HTTP GET request to the Originality.ai v1 API endpoint /account/credits/balance and returns the JSON response.
    async def get_credit_balance(self) -> dict[str, Any]:
        """Get remaining account credits (v1 endpoint)."""
        resp = await self.client_v1.get("/account/credits/balance")
        resp.raise_for_status()
        return resp.json()
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It states the tool returns credit balance information, which implies a read-only operation, but doesn't explicitly mention if it requires authentication, has rate limits, or other behavioral traits. The description adds basic context but lacks comprehensive behavioral disclosure.

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 two sentences with zero waste: the first states the purpose and return value, the second provides usage guidance. It's front-loaded with essential information and efficiently structured without redundant or verbose language.

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

Completeness4/5

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

Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is reasonably complete. It explains what the tool does, when to use it, and what it returns. However, without annotations or output schema, it could benefit from more detail on response format or error conditions, but it's adequate for this context.

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

Parameters4/5

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

The tool has 0 parameters, and schema description coverage is 100%. The description doesn't need to explain parameters, so it appropriately focuses on purpose and usage. A baseline of 4 is applied as no parameters exist, and the description doesn't attempt to add unnecessary param details.

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

Purpose5/5

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

The description clearly states the specific action ('Check your Originality.ai credit balance') and resource ('credit balance'), distinguishing it from sibling scanning tools. It explicitly mentions what the tool returns ('remaining credits available for scanning'), making the purpose unambiguous.

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

Usage Guidelines5/5

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

The description provides explicit usage guidance: 'Use before batch operations to verify you have enough credits.' This directly tells the agent when to invoke this tool versus proceeding with scanning operations, offering clear context for decision-making.

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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