Single tool 'execute_skill_action' has a basic description (56 chars) and minimal input schema. Schema defines two parameters with types and descriptions, meeting baseline requirements. However, NO output schema is documented, critical gap per pattern:tool. The tool description lacks WHEN to use it, WHAT it returns, and any prerequisites. Parameters lack constraints (enums, ranges, format specs). No error handling guidance. The implementation in mcp_server.py is a stub that prints JSON and exits, it does not actually implement the MCP protocol (no request/response loop, no tool invocation handling). This is a non-functional skeleton, not a production server.

• Document the output schema with all returned fields, types, and descriptions. Example: {"winning_hook_copy": string, "predicted_ctr_boost_pct": number, "channel_variants_count": integer}.
• Expand tool description to 100 - 200 characters explaining: (1) What it does (generates ad variants), (2) WHEN to use it (when you need social media ad copy), (3) What it returns (hook copy, CTR prediction, variant count).
• Add enum constraint to 'target_channel' parameter: ["Twitter_X", "LinkedIn", "Facebook", "Instagram", "TikTok"] to prevent hallucinated channel names.
• Implement actual MCP protocol in mcp_server.py: add a request/response loop that reads JSON-RPC messages from stdin, dispatches to tool handlers, and writes responses to stdout.
• Add error handling guidance: document what happens if product_usp is empty, if target_channel is invalid, or if the generation service fails. Include recovery hints.