This server has a single tool 'execute_skill_action' with virtually no implementation visible. The mcp_server.py file contains only a stub that prints a JSON status message, no actual tool registration, schema definition, or parameter handling. The tool name lacks a clear action verb (execute_skill_action is vague; should be something like 'run_sandbox_code' or 'execute_code_in_sandbox'). No input schema, no parameter descriptions, no output schema, and no error handling are visible in the source. The client.py and example_usage.py files show a CloudSandboxEphemeralExecutionEnvironmentClient class, but this is NOT integrated into the MCP server definition. The server does not register tools with the MCP protocol at all, it only prints a static status message. This is a non-functional skeleton.

• Implement proper MCP tool registration using the MCP SDK. Define execute_skill_action (or rename to run_sandbox_code) with a complete JSON Schema input definition including parameters like 'code', 'language', 'timeout_seconds', etc.
• Add a detailed description (100-200 chars) explaining: 'Execute arbitrary code in an isolated ephemeral sandbox. Supports Python, Node.js, and other runtimes. Returns stdout, stderr, exit code, and execution time. Use this to run user code safely without affecting the host system.'
• Define all input parameters with types and descriptions. Example: 'code' (string, required, 'The source code to execute'), 'language' (enum: python_3_13, nodejs_22, etc.), 'timeout_seconds' (integer, 1-300, default 30).
• Document the output schema with fields like 'sandbox_id', 'stdout', 'stderr', 'exit_code', 'execution_time_ms', 'tunnel_url'. Include examples of success and error responses.
• Add error handling that guides recovery. E.g., 'Timeout: code did not complete within 30 seconds. Try reducing complexity or increasing timeout_seconds parameter.' Include actionable next steps for common failures.