Single tool 'execute_skill_action' has a generic, vague name that violates verb_noun conventions. Description is 127 chars but lacks WHAT/WHEN/WHY context required for LLM selection. Input schema exists but parameter 'query_payload' is a free-form string with no format constraints, validation rules, or examples. No output schema documented, LLM cannot predict response structure. No error handling guidance. Tool appears to be a catch-all governance wrapper rather than a focused, composable action. Hard cap applied: tool definition is visible but schema is minimal and description is insufficient.

• Rename tool to a specific action: 'monitor_agent_toxicity_drift', 'detect_sentiment_anomaly', or 'assess_governance_risk'. Each should be a separate tool if they perform different operations.
• Replace 'query_payload' string parameter with structured fields: 'conversation_text' (string), 'baseline_sentiment' (float, -1.0 to 1.0), 'alert_threshold' (float, 0.0 to 1.0). Add enum or range constraints.
• Document output schema explicitly: {status: 'SUCCESS'|'ERROR', toxicity_score: float, sentiment_valence: float, drift_from_baseline: float, alert_triggered: boolean, recommended_remedy: string}.
• Expand description to 100-200 chars: 'Monitor conversation toxicity and sentiment drift in real-time. Detects civility risks and recommends de-escalation strategies. Call when agent responses may trigger user frustration or escalate conflict.'
• Add error handling: return {status: 'ERROR', code: 'INVALID_PAYLOAD', message: 'query_payload must be valid JSON with conversation_text field', recovery: 'Ensure payload is JSON and includes conversation_text'} on failure.