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create_mortise_tenon

Generate precise mortise and tenon joints between components in Sketchup using specified dimensions and offsets for accurate 3D woodworking designs.

Instructions

Create a mortise and tenon joint between two components

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
depthNo
heightNo
mortise_idYes
offset_xNo
offset_yNo
offset_zNo
tenon_idYes
widthNo

Implementation Reference

  • MCP tool handler that proxies the create_mortise_tenon command to the SketchUp extension socket server using JSON-RPC. The function parameters define the input schema implicitly.
    @mcp.tool()
    def create_mortise_tenon(
        ctx: Context,
        mortise_id: str,
        tenon_id: str,
        width: float = 1.0,
        height: float = 1.0,
        depth: float = 1.0,
        offset_x: float = 0.0,
        offset_y: float = 0.0,
        offset_z: float = 0.0
    ) -> str:
        """Create a mortise and tenon joint between two components"""
        try:
            logger.info(f"create_mortise_tenon called with mortise_id={mortise_id}, tenon_id={tenon_id}, width={width}, height={height}, depth={depth}, offsets=({offset_x}, {offset_y}, {offset_z})")
            
            sketchup = get_sketchup_connection()
            
            result = sketchup.send_command(
                method="tools/call",
                params={
                    "name": "create_mortise_tenon",
                    "arguments": {
                        "mortise_id": mortise_id,
                        "tenon_id": tenon_id,
                        "width": width,
                        "height": height,
                        "depth": depth,
                        "offset_x": offset_x,
                        "offset_y": offset_y,
                        "offset_z": offset_z
                    }
                },
                request_id=ctx.request_id
            )
            
            logger.info(f"create_mortise_tenon result: {result}")
            return json.dumps(result)
        except Exception as e:
            logger.error(f"Error in create_mortise_tenon: {str(e)}")
            return f"Error creating mortise and tenon joint: {str(e)}"
  • FastMCP decorator that registers the create_mortise_tenon tool with the MCP server.
    @mcp.tool()
  • Function signature defining the input parameters (schema) for the create_mortise_tenon tool.
    def create_mortise_tenon(
        ctx: Context,
        mortise_id: str,
        tenon_id: str,
        width: float = 1.0,
        height: float = 1.0,
        depth: float = 1.0,
        offset_x: float = 0.0,
        offset_y: float = 0.0,
        offset_z: float = 0.0
    ) -> str:
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. It states 'Create' which implies a write/mutation operation, but doesn't disclose behavioral traits such as whether this modifies existing components, requires specific permissions, has side effects, or what happens on failure. This is a significant gap for a tool with 8 parameters and no output schema.

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 directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.

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 (8 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain the joint creation process, parameter roles, expected outcomes, or error conditions. For a mutation tool with many parameters, 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.

Parameters1/5

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

Schema description coverage is 0%, meaning none of the 8 parameters have descriptions in the schema. The description adds no information about parameters beyond what's implied by the tool name (e.g., 'mortise_id' and 'tenon_id' relate to components). It doesn't explain what depth, height, offsets, or width mean in this context, failing to compensate for the coverage gap.

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 ('Create') and the specific resource ('a mortise and tenon joint between two components'), which is a woodworking joint type. It distinguishes from siblings like 'create_dovetail' and 'create_finger_joint' by specifying the joint type, though it doesn't explicitly contrast them.

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 like 'create_dovetail' or 'create_finger_joint'. It doesn't mention prerequisites (e.g., existing components), context, or exclusions, leaving the agent to infer usage from the 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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