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Vortiago
by Vortiago

get_work_item_type

Retrieve detailed information about a specific work item type in Azure DevOps, including states, transitions, color, and icon, to understand its configuration and workflow.

Instructions

    Gets detailed information about a specific work item type.
    
    Use this tool when you need to:
    - Get complete details about a work item type
    - Understand the states and transitions for a work item type
    - Learn about the color and icon for a work item type
    
    Args:
        project: Project ID or project name
        type_name: The name of the work item type
        
    Returns:
        Detailed information about the work item type including states,
        color, icon, and reference name
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectYes
type_nameYes

Implementation Reference

  • MCP tool handler for 'get_work_item_type'. Obtains the WorkItemTrackingClient and delegates to the implementation function, handling errors.
    @mcp.tool()
    def get_work_item_type(project: str, type_name: str) -> str:
        """
        Gets detailed information about a specific work item type.
        
        Use this tool when you need to:
        - Get complete details about a work item type
        - Understand the states and transitions for a work item type
        - Learn about the color and icon for a work item type
        
        Args:
            project: Project ID or project name
            type_name: The name of the work item type
            
        Returns:
            Detailed information about the work item type including states,
            color, icon, and reference name
        """
        try:
            wit_client = get_work_item_client()
            return _get_work_item_type_impl(project, type_name, wit_client)
        except AzureDevOpsClientError as e:
            return f"Error: {str(e)}"
  • Core helper function that calls the Azure DevOps WorkItemTrackingClient.get_work_item_type API and formats the result or handles not found case.
    def _get_work_item_type_impl(project: str, type_name: str, 
                                 wit_client: WorkItemTrackingClient) -> str:
        """Implementation of work item type detail retrieval."""
        work_item_type = wit_client.get_work_item_type(project, type_name)
        
        if not work_item_type:
            return f"Work item type '{type_name}' not found in project {project}."
        
        return _format_work_item_type(work_item_type)
  • Helper function to format the work item type details into markdown, including description, attributes, and states.
    def _format_work_item_type(wit):
        """Format work item type data for display."""
        result = [f"# Work Item Type: {wit.name}"]
        
        description = getattr(wit, "description", None)
        if description:
            result.append(f"\nDescription: {description}")
        
        for attr in ["color", "icon", "reference_name"]:
            value = getattr(wit, attr, None)
            if value:
                result.append(f"{attr.capitalize()}: {value}")
        
        is_disabled = getattr(wit, "is_disabled", None)
        if is_disabled is not None:
            result.append(f"Is Disabled: {is_disabled}")
        
        states = getattr(wit, "states", None)
        if states:
            result.append("\n## States")
            for state in states:
                state_info = f"- {state.name} (Category: {state.category}, " \
                             f"Color: {state.color})"
                order = getattr(state, "order", None)
                if order is not None:
                    state_info += f", Order: {order}"
                result.append(state_info)
        
        return "\n".join(result)
  • Registration point where types.register_tools(mcp) is called, which registers the get_work_item_type tool among others.
    def register_tools(mcp) -> None:
        """
        Register all work item tools with the MCP server.
        
        Args:
            mcp: The FastMCP server instance
        """
        query.register_tools(mcp)
        read.register_tools(mcp)
        comments.register_tools(mcp)
        create.register_tools(mcp)
        types.register_tools(mcp)
  • Higher-level registration that calls tools.register_tools(mcp), leading to the work item types tools.
    def register(mcp):
        """
        Register all work items components with the MCP server.
        
        Args:
            mcp: The FastMCP server instance
        """
        tools.register_tools(mcp)
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 this is a read operation ('Gets'), which implies non-destructive behavior, but doesn't mention authentication requirements, rate limits, error conditions, or whether it returns all details in one call. It adds some context about what information is returned, 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 well-structured with a clear purpose statement, bulleted usage guidelines, and separate Args/Returns sections. Every sentence adds value without redundancy. It's appropriately sized for a tool with two parameters and no output schema.

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 moderate complexity (2 required parameters, no output schema, no annotations), the description is largely complete. It covers purpose, usage, parameters, and return details. However, it lacks information about authentication, errors, or pagination, which could be relevant for API interactions.

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 schema description coverage is 0%, so the description must compensate. It explains both parameters: 'project' as 'Project ID or project name' and 'type_name' as 'The name of the work item type', adding meaningful context beyond the schema's basic titles. However, it doesn't provide examples or format specifics (e.g., case sensitivity).

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 verb ('Gets') and resource ('detailed information about a specific work item type'), distinguishing it from siblings like 'get_work_item_types' (plural) which likely lists types, and 'get_work_item' which retrieves individual work items rather than type definitions. The purpose is specific and 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 explicitly lists three use cases: getting complete details, understanding states/transitions, and learning about color/icon. This provides clear guidance on when to use this tool versus alternatives like 'get_work_item_types' (for listing) or 'get_work_item' (for item data).

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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