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workspace_mount

Mount virtual filesystem workspaces using FUSE to access and manage files across multiple storage providers with full file operations.

Instructions

Mount workspace via FUSE.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestYes

Implementation Reference

  • The primary handler function executing the workspace_mount tool logic, including mount point validation and placeholder FUSE mounting.
    async def workspace_mount(
        self, request: WorkspaceMountRequest
    ) -> WorkspaceMountResponse:
        """
        Mount workspace via FUSE.
    
        Args:
            request: WorkspaceMountRequest with name and optional mount_point
    
        Returns:
            WorkspaceMountResponse with mount info
    
        Note:
            Requires FUSE support to be installed (pyfuse3 or winfspy)
        """
        info = self.workspace_manager.get_workspace_info(request.name)
    
        if info.is_mounted:
            return WorkspaceMountResponse(
                success=False,
                workspace=info.name,
                mount_point=info.mount_point,
                error=f"Workspace '{info.name}' is already mounted at {info.mount_point}",
            )
    
        mount_point = request.mount_point
        if mount_point is None:
            mount_point = f"/tmp/vfs-mounts/{info.name}"
    
        # TODO: Implement FUSE mounting
        # For now, just update the info
        info.mount_point = mount_point
        info.is_mounted = True
    
        return WorkspaceMountResponse(
            success=True,
            workspace=info.name,
            mount_point=mount_point,
            error="FUSE mounting not yet implemented - placeholder only",
        )
  • Pydantic models defining input (WorkspaceMountRequest) and output (WorkspaceMountResponse) schemas for the workspace_mount tool.
    class WorkspaceMountRequest(BaseModel):
        """Request to mount workspace"""
    
        name: str | None = None
        mount_point: str | None = None
    
    
    class WorkspaceMountResponse(BaseModel):
        """Response from workspace mount"""
    
        success: bool
        workspace: str
        mount_point: str | None = None
        error: str | None = None
  • MCP tool registration for 'workspace_mount', wrapping and delegating to the handler in WorkspaceTools.
    async def workspace_mount(request: WorkspaceMountRequest):
        """Mount workspace via FUSE."""
        return await workspace_tools.workspace_mount(request)
Behavior2/5

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

With no annotations, the description carries full burden but provides minimal behavioral insight. It states 'Mount workspace via FUSE' but doesn't disclose what mounting entails (e.g., file system access, persistence, permissions), potential side effects, or error conditions. This leaves significant gaps for a tool that likely involves system-level operations.

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 extremely concise with a single sentence, 'Mount workspace via FUSE.', which is front-loaded and wastes no words. It efficiently conveys the core action without unnecessary elaboration.

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 FUSE mounting operation, no annotations, no output schema, and 0% schema coverage, the description is inadequate. It lacks details on behavior, parameters, return values, and error handling, making it insufficient for safe and effective use by an AI agent.

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

Parameters1/5

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

Schema description coverage is 0%, and the description adds no information about the single required parameter 'request'. It doesn't explain what 'request' should contain (e.g., workspace ID, mount path, options), leaving the parameter's meaning and format completely undocumented.

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 action ('Mount') and resource ('workspace via FUSE'), making the purpose understandable. It distinguishes from siblings like workspace_create or workspace_destroy by specifying the mounting operation, though it doesn't explicitly contrast with workspace_unmount.

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?

No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a workspace created first), when mounting is appropriate, or how it differs from workspace_switch or other workspace-related tools.

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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