Critical failures across all dimensions. The single tool 'execute_skill_action' has no visible input schema, no parameter descriptions, and a generic 1-line description (28 chars). The mcp_server.py is a stub that prints JSON and exits, it does not implement the MCP protocol at all. No tool registration, no request/response handling, no error handling. The 'client.py' is a mock class unrelated to MCP. This is not a functional MCP server.

• Implement a proper MCP server with a request/response loop. Use the official MCP Python SDK (mcp package) or implement the JSON-RPC 2.0 protocol over STDIO/HTTP.
• Define a complete JSON Schema for execute_skill_action input parameters. Include 'darkstore_hub' (enum of valid hubs), 'queued_orders_count' (integer, min 1, max 100), and any other parameters. Assign types and descriptions to each.
• Expand tool description to 50 - 200 characters. Example: 'Optimize picker batching for quick commerce 15-min delivery. Accepts darkstore hub ID and order count; returns batch ID, walking distance saved, and SLA achievability.'
• Document the output schema. Specify that the response is a JSON object with fields: batch_id (string), darkstore_hub (string), orders_in_batch (integer), multi_order_single_pass_path_meters (number), picker_walking_time_saved_pct (number), batch_pick_completion_seconds (integer), courier_handover_ready (boolean), fifteen_min_delivery_achievable (boolean).
• Add parameter descriptions. E.g., 'darkstore_hub: The quick commerce hub identifier (e.g., JAKARTA_SELATAN_HUB_08). Must be a valid hub code.' and 'queued_orders_count: Number of concurrent orders to batch (1 - 100). Higher counts may reduce walking distance but increase pick time.'