Critical gaps across all dimensions. Tool definitions are minimal and lack essential structure. execute_skill_action has no visible input schema in source code (mcp_server.py shows only a JSON status message, not tool registration). negotiate_order_concession has a schema with 3 parameters but descriptions are generic and lack actionable guidance. No output schemas documented. No error handling or recovery guidance. Tool names are vague (execute_skill_action uses generic 'execute' verb). Descriptions under 100 chars lack context for LLM selection. No parameter validation rules, constraints, or format guidance. No security considerations visible.

• Rename execute_skill_action to a verb_noun pair that reflects the actual action (e.g., calculate_negotiation_discount, apply_concession_offer). Avoid generic verbs like 'execute'.
• Add explicit input schema to execute_skill_action in mcp_server.py tool registration. Currently no parameters are visible; define what inputs this tool accepts.
• Document output schemas for both tools. For negotiate_order_concession, declare the response structure: {negotiation_session_id: string, original_price_usd: number, concession_discount_pct: number, final_negotiated_price_usd: number, merchant_margin_floor_protected: boolean, authorized_coupon_code: string, concession_contract_token_url: string}.
• Convert parameter descriptions to formal constraints. Replace 'e.g., HIGH, MEDIUM, LOW' with an enum: {"type": "string", "enum": ["HIGH", "MEDIUM", "LOW"]}. Add min/max for numeric parameters (e.g., listed_cart_total_usd: min 0, max 999999).
• Add error handling with recovery guidance. E.g., 'If customer_lifetime_value is unknown, call search_customer_history() first.' Define error categories (retryable, user-fixable, fatal) and return actionable messages.