Skip to main content
Glama

eval_ruby

Execute Ruby code directly in Sketchup through the SketchupMCP server, enabling dynamic 3D modeling, scene manipulation, and integration with AI-driven workflows.

Instructions

Evaluate arbitrary Ruby code in Sketchup

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYes

Implementation Reference

  • The core handler function for the 'eval_ruby' tool. It is decorated with @mcp.tool() for automatic registration and schema inference from type hints and docstring. The function evaluates the provided Ruby code by forwarding it to the SketchUp connection.
    @mcp.tool()
    def eval_ruby(
        ctx: Context,
        code: str
    ) -> str:
        """Evaluate arbitrary Ruby code in Sketchup"""
        try:
            logger.info(f"eval_ruby called with code length: {len(code)}")
            
            sketchup = get_sketchup_connection()
            
            result = sketchup.send_command(
                method="tools/call",
                params={
                    "name": "eval_ruby",
                    "arguments": {
                        "code": code
                    }
                },
                request_id=ctx.request_id
            )
            
            logger.info(f"eval_ruby result: {result}")
            
            # Format the response to include the result
            response = {
                "success": True,
                "result": result.get("content", [{"text": "Success"}])[0].get("text", "Success") if isinstance(result.get("content"), list) and len(result.get("content", [])) > 0 else "Success"
            }
            
            return json.dumps(response)
        except Exception as e:
            logger.error(f"Error in eval_ruby: {str(e)}")
            return json.dumps({
                "success": False,
                "error": str(e)
            })
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 the action ('Evaluate arbitrary Ruby code') but does not disclose critical traits such as security implications, execution environment constraints, error handling, or output format. This is a significant gap for a tool that executes arbitrary code.

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 with zero waste. It is appropriately sized and front-loaded, directly stating the tool's purpose without unnecessary elaboration, 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 of executing arbitrary code, lack of annotations, no output schema, and low schema coverage, the description is incomplete. It fails to address safety, permissions, or result handling, which are crucial for such a tool. The agent would lack sufficient context to use it effectively.

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?

Schema description coverage is 0%, so the description must compensate. It mentions 'Ruby code' which aligns with the 'code' parameter, but adds minimal semantic value beyond what the parameter name implies. No details on code format, examples, or constraints are provided, leaving the parameter poorly documented.

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 specific action ('Evaluate arbitrary Ruby code') and the target resource/environment ('in Sketchup'). It distinguishes itself from sibling tools that focus on CAD operations like creating components or manipulating geometry, making it uniquely about code execution.

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 does not mention prerequisites, risks, or typical use cases, leaving the agent to infer usage based on the purpose alone. No explicit when/when-not or alternative tools are referenced.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Related Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/BearNetwork-BRNKC/SketchUp-MCP'

If you have feedback or need assistance with the MCP directory API, please join our Discord server