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workspace_info

Retrieve detailed information about a virtual filesystem workspace to understand its structure, scope, and storage configuration.

Instructions

Get detailed information about a workspace.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo

Implementation Reference

  • Handler function for the 'workspace_info' tool that retrieves workspace details by delegating to the WorkspaceManager.
    async def workspace_info(self, name: str | None = None) -> WorkspaceInfo:
        """
        Get detailed information about a workspace.
    
        Args:
            name: Workspace name (None for current workspace)
    
        Returns:
            WorkspaceInfo with full workspace details
        """
        return self.workspace_manager.get_workspace_info(name)
  • Registration of the 'workspace_info' tool using the @server.tool decorator in the MCP server.
    @server.tool
    async def workspace_info(name: str | None = None):
        """Get detailed information about a workspace."""
        return await workspace_tools.workspace_info(name)
  • Pydantic BaseModel defining the structure of the WorkspaceInfo returned by the tool.
    class WorkspaceInfo(BaseModel):
        """Information about a workspace"""
    
        name: str
        provider_type: ProviderType
        created_at: datetime
        current_path: str = "/"
        mount_point: str | None = None
        is_mounted: bool = False
        metadata: dict[str, Any] = Field(default_factory=dict)
    
        model_config = {"use_enum_values": False}
  • Underlying helper method in WorkspaceManager that performs the actual lookup of workspace information.
    def get_workspace_info(self, name: str | None = None) -> WorkspaceInfo:
        """
        Get workspace information.
    
        Args:
            name: Workspace name (None for current workspace)
    
        Returns:
            WorkspaceInfo
    
        Raises:
            ValueError: If workspace doesn't exist or no current workspace
        """
        if name is None:
            if self._current_namespace_id is None:
                raise ValueError("No current workspace")
            return self._namespace_to_info[self._current_namespace_id]
    
        # Find by name
        for info in self._namespace_to_info.values():
            if info.name == name:
                return info
    
        raise ValueError(f"Workspace '{name}' does not exist")
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 'Get detailed information,' which implies a read-only operation, but doesn't specify what 'detailed information' includes (e.g., metadata, permissions, status), whether it requires authentication, if there are rate limits, or what happens if the workspace doesn't exist. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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 a single, efficient sentence that gets straight to the point: 'Get detailed information about a workspace.' It's front-loaded with the core purpose, uses clear language, and avoids unnecessary words. Every part of the sentence earns its place by conveying essential information without redundancy.

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

Completeness2/5

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

Given the complexity of a workspace information tool with no annotations, no output schema, and incomplete parameter documentation (0% coverage), the description is inadequate. It doesn't explain what 'detailed information' entails, how to interpret the 'name' parameter, or what the return value looks like. For a tool that likely provides structured data about workspaces, more context is needed to guide effective use.

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

Parameters2/5

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

The input schema has one parameter ('name') with 0% description coverage, meaning the schema provides no details about this parameter. The description adds no information about parameters—it doesn't explain what 'name' refers to (e.g., workspace identifier, path), its format, or if it's required. With low schema coverage, the description fails to compensate, leaving the parameter's meaning unclear.

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 ('Get') and resource ('detailed information about a workspace'), making the purpose immediately understandable. It distinguishes from siblings like workspace_create, workspace_destroy, and workspace_list by focusing on retrieving information rather than creating, deleting, or listing workspaces. However, it doesn't explicitly differentiate from 'read' or other information-retrieval tools in the sibling 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 when this tool is appropriate (e.g., for getting metadata about a specific workspace) or when not to use it (e.g., use workspace_list for enumerating workspaces). With many sibling tools like workspace_list, read, and ls that might overlap in functionality, this lack of context leaves the agent guessing about the optimal choice.

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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