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update_work_queue

Modify a Prefect work queue's settings including name, description, paused status, and concurrency limit to control workflow execution behavior.

Instructions

Update a work queue.

Args: work_queue_id: The work queue UUID name: New name description: New description is_paused: New paused status concurrency_limit: New concurrency limit

Returns: Details of the updated work queue

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
concurrency_limitNo
descriptionNo
is_pausedNo
nameNo
work_queue_idYes

Implementation Reference

  • The main handler implementation for the MCP tool 'update_work_queue'. It is decorated with @mcp.tool for registration and handles updating Prefect work queue attributes via the Prefect client, returning the updated queue details as text content.
    @mcp.tool
    async def update_work_queue(
        work_queue_id: str,
        name: Optional[str] = None,
        description: Optional[str] = None,
        is_paused: Optional[bool] = None,
        concurrency_limit: Optional[int] = None,
    ) -> List[Union[types.TextContent, types.ImageContent, types.EmbeddedResource]]:
        """
        Update a work queue.
        
        Args:
            work_queue_id: The work queue UUID
            name: New name
            description: New description
            is_paused: New paused status
            concurrency_limit: New concurrency limit
            
        Returns:
            Details of the updated work queue
        """
        async with get_client() as client:
            # Prepare update data
            update_data = {}
            if name is not None:
                update_data["name"] = name
            if description is not None:
                update_data["description"] = description
            if is_paused is not None:
                update_data["is_paused"] = is_paused
            if concurrency_limit is not None:
                update_data["concurrency_limit"] = concurrency_limit
            
            await client.update_work_queue(
                id=UUID(work_queue_id),
                **update_data
            )
            
            # Read the updated work queue to return its details
            updated_work_queue = await client.read_work_queue(UUID(work_queue_id))
            return [types.TextContent(type="text", text=str(updated_work_queue.model_dump()))]
Behavior2/5

Does 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 states this is an update operation (implying mutation) but doesn't mention required permissions, whether changes are reversible, rate limits, or what happens when only some parameters are provided (given defaults are null). The 'Returns' statement is vague and doesn't describe the response format or potential errors.

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 efficiently structured with a clear purpose statement followed by organized parameter and return sections. Every sentence serves a purpose: the first states the action, the Args section documents parameters, and the Returns section indicates output. It could be slightly more front-loaded by integrating parameter context into the opening sentence.

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?

For a mutation tool with 5 parameters, 0% schema description coverage, and no output schema, the description provides adequate but incomplete context. It documents parameters well but lacks behavioral details (permissions, side effects) and output specifics. Compared to siblings like 'pause_work_queue', it doesn't clarify how partial updates work or error conditions, leaving gaps for the agent.

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 description explicitly lists all 5 parameters with brief explanations that add meaningful context beyond the schema's 0% description coverage. It clarifies that 'work_queue_id' is a UUID, other parameters represent 'new' values, and 'is_paused' relates to 'paused status'. This compensates well for the schema's lack of descriptions, though it doesn't explain constraints like valid ranges for 'concurrency_limit'.

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 verb ('Update') and resource ('a work queue'), making the purpose immediately understandable. It distinguishes this from sibling tools like 'create_work_queue' and 'delete_work_queue' by focusing on modification rather than creation or deletion. However, it doesn't specify what aspects of the work queue are being updated beyond the parameter list.

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 prerequisites (e.g., needing an existing work queue ID), when not to use it, or how it differs from related tools like 'pause_work_queue' or 'resume_work_queue' that also affect work queue status. The agent must infer usage from the tool name alone.

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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