This server has a single tool 'execute_skill_action' with virtually no definition quality. The tool description is a bare 87-character string with no parameter schema visible in the source code. The mcp_server.py file contains only a JSON print statement announcing the server's existence, there is no actual tool registration, parameter validation, or schema definition. The client.py and example_usage.py files show internal business logic but are not part of the MCP interface. No input schema, no parameter descriptions, no output schema documentation, and no error handling are present. This is a stub implementation, not a production-ready MCP server.

• Define execute_skill_action with explicit JSON Schema input parameters. At minimum: audio_chunk_ms (number, 1-1000), speaker_activity (object with agent_speaking: boolean, user_energy_db: number). Reference pattern:constrained-input.
• Expand tool description to 150-250 characters explaining: 'Detects voice interruptions and manages turn-taking in real-time voice conversations. Analyzes acoustic energy to determine if the user is barging in, and recommends synthesis pause/resume actions. Requires speaker_activity with user_energy_db in dB.'
• Rename tool from 'execute_skill_action' to 'detect_voice_interruption' or 'manage_turn_taking' to match pattern:tool naming (verb_noun, action-first). Current name is too generic.
• Document output schema with typed fields: turn_taking_state (enum: AGENT_SPEAKING|USER_BARGING_IN), interrupt_detected (boolean), agent_speech_cutoff_latency_ms (number), natural_turn_taking_confidence (number 0-1), recommended_action (enum: CONTINUE_PLAYBACK|IMMEDIATELY_PAUSE_SYNTHESIS_AND_LISTEN).
• Add error handling: return structured errors with actionable guidance. E.g., 'Invalid user_energy_db: must be a number between -50 and 0 dB. Got: {value}.' Reference pattern:recovery-guide.