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get_domain_status

Monitor a domain purchase order by polling the backend every 3 seconds for up to 120 seconds, until the order completes or fails.

Instructions

Get the status of a domain purchase order.

Polls the backend every 3 seconds (up to 120 seconds) until the order reaches a terminal state (complete or failed).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
order_idYesThe order ID returned from buy_domain (e.g. "ord_abc123").

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The get_domain_status MCP tool handler. Polls the backend /status/{order_id} endpoint every 3 seconds (up to 120s) until the order reaches a terminal state (complete, failed, or expired). Returns the status dict or a timeout message.
    @mcp.tool()
    async def get_domain_status(order_id: str) -> dict:
        """Get the status of a domain purchase order.
    
        Polls the backend every 3 seconds (up to 120 seconds) until the order
        reaches a terminal state (complete or failed).
    
        Args:
            order_id: The order ID returned from buy_domain (e.g. "ord_abc123").
        """
        terminal_statuses = {"complete", "failed", "expired"}
        deadline = asyncio.get_running_loop().time() + POLL_TIMEOUT_SECONDS
    
        async with httpx.AsyncClient(base_url=BACKEND_URL, timeout=15) as client:
            while True:
                resp = await client.get(f"/status/{order_id}")
                resp.raise_for_status()
                data = resp.json()
    
                if data.get("status") in terminal_statuses:
                    return data
    
                if asyncio.get_running_loop().time() >= deadline:
                    data["_poll_timeout"] = True
                    data["_message"] = (
                        f"Order {order_id} did not reach a terminal state "
                        f"within {POLL_TIMEOUT_SECONDS}s. Current status: {data.get('status')}"
                    )
                    return data
    
                await asyncio.sleep(POLL_INTERVAL_SECONDS)
  • The tool is registered via the @mcp.tool() decorator on line 96, which registers it with the FastMCP server instance (mcp) defined on line 30.
    @mcp.tool()
    async def get_domain_status(order_id: str) -> dict:
  • Input schema: single parameter 'order_id' (str). The return type is dict, documented to contain status, and on timeout includes _poll_timeout and _message fields.
    @mcp.tool()
    async def get_domain_status(order_id: str) -> dict:
        """Get the status of a domain purchase order.
    
        Polls the backend every 3 seconds (up to 120 seconds) until the order
        reaches a terminal state (complete or failed).
    
        Args:
            order_id: The order ID returned from buy_domain (e.g. "ord_abc123").
        """
  • Polling constants used by get_domain_status: POLL_INTERVAL_SECONDS (3) and POLL_TIMEOUT_SECONDS (120).
    POLL_INTERVAL_SECONDS = 3
    POLL_TIMEOUT_SECONDS = 120
  • Backend URL constant used by get_domain_status to make HTTP requests to the /status/{order_id} endpoint.
    BACKEND_URL = os.environ.get("INSTADOMAIN_BACKEND_URL", "https://instadomain.fly.dev")
Behavior4/5

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

Discloses important behavioral details: polling every 3 seconds up to 120 seconds until terminal state. No annotations provided, so description carries full burden. Could mention timeout behavior or error cases.

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?

Two efficient sentences, no fluff, front-loaded with purpose and key behavioral detail.

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

Completeness5/5

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

With a single parameter and output schema present (though not shown), description provides sufficient context for the tool's simple functionality.

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 coverage is 100%, so schema alone adequately describes the order_id parameter. Description adds no extra meaning beyond the schema's description.

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?

Clearly states it gets the status of a domain purchase order, with specific polling behavior, distinguishing it from sibling tools like buy_domain or check_domain.

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

Usage Guidelines4/5

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

Implies use after purchasing a domain to check order status, but lacks explicit when-not-to-use or alternatives. Context is clear enough for agent to infer appropriate usage.

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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