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get_work_queue

Retrieve work queue details by ID to monitor workflow execution status and manage task processing in Prefect's automation platform.

Instructions

Get details of a specific work queue by ID.

Args: work_queue_id: The work queue UUID

Returns: Work queue details

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
work_queue_idYes

Implementation Reference

  • The main handler function for the 'get_work_queue' MCP tool. Decorated with @mcp.tool, it retrieves the specified work queue by ID using the Prefect client and returns its details as structured text content.
    @mcp.tool
    async def get_work_queue(
        work_queue_id: str,
    ) -> List[Union[types.TextContent, types.ImageContent, types.EmbeddedResource]]:
        """
        Get details of a specific work queue by ID.
        
        Args:
            work_queue_id: The work queue UUID
            
        Returns:
            Work queue details
        """
        async with get_client() as client:
            work_queue = await client.read_work_queue(UUID(work_queue_id))
            
            return [types.TextContent(type="text", text=str(work_queue.model_dump()))]
  • The registration point where the work_queue module is imported during server startup when WORK_QUEUE API is enabled. This import executes the @mcp.tool decorators, registering the 'get_work_queue' tool on the MCP server.
    if APIType.WORK_QUEUE.value in apis:
        info("Loading Work Queue API...")
        from . import work_queue
  • Creation of the FastMCP server instance 'mcp' to which tools like 'get_work_queue' are registered via decorators.
    mcp = FastMCP(f"MCP Prefect {__version__}")
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves details but doesn't mention whether it's a read-only operation, what permissions are required, error handling, or response format. For a tool with zero annotation coverage, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded: the first sentence states the core purpose, followed by structured 'Args' and 'Returns' sections. It avoids redundancy, though the 'Returns' line is vague ('Work queue details') and could be more specific without adding bulk.

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

Completeness3/5

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

Given one parameter, no annotations, and no output schema, the description is minimally adequate. It covers the basic action and parameter but lacks details on behavior, error cases, and return values. For a simple retrieval tool, it meets the minimum viable threshold but has clear gaps in completeness.

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 description coverage is 0%, so the description must compensate. It adds that 'work_queue_id' is a 'UUID', which provides semantic context beyond the schema's 'string' type. However, it doesn't explain format, validation, or where to obtain the ID, leaving gaps. With one parameter and partial compensation, a baseline 3 is appropriate.

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

Purpose4/5

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

The description clearly states the tool's purpose: 'Get details of a specific work queue by ID.' It specifies the verb ('Get details') and resource ('work queue'), making the action unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_work_queue_by_name' or 'get_work_queues', which would require a 5.

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

Usage Guidelines2/5

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. It doesn't mention sibling tools like 'get_work_queue_by_name' (for lookup by name) or 'get_work_queues' (for listing multiple queues), nor does it specify prerequisites or exclusions. This leaves the agent without context for tool selection.

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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