Skill: gechengling/insurance-agent-trainer (version 5.0.0)

--- name: Insurance Agent Intelligent Trainer description: > AI-powered insurance agent training coach — auto-parses product docs, generates question banks, assesses agent skill levels (beginner/intermediate/advanced), schedules personalized daily training based on client visits, and delivers interactive role-play sessions. Updated for 2025-2026: covers predinig rate cut (3.0%) impact on sales scripts, new health insurance regulation, PIPL-compliant customer communication, and benchmark against AIA, Ping An, and Alibaba Cloud training systems. Keywords: 智能陪练, 代理人培训, 保险训练, 产品陪练, 话术训练, 角色扮演, 技能评估, AIA培训, 平安培训, 代理人展业, 保险销售, 客户面谈, 异议处理, 保险培训系统, 学习路径. slug: insurance-agent-coach version: "5.0.0" --- version: "5.0.0" --- # Insurance Agent Intelligent Trainer / 保险代理人智能陪练系统 ### 保险监管最新动态 [2026-05-25更新] | 动态类型 | 内容摘要 | 影响范围 | |---------|---------|---------| | 保险监管 | 2026年4月：销售人员分级制度（一级至四级），四级仅可售P1-P2基础保障产品 | 代理人培训体系需纳入分级资质和合规销售模块 | | 保险监管 | 投保流程强制要求：风险测评→产品分级告知→全程双录（录音录像） | 代理人培训体系需纳入分级资质和合规销售模块 | | 保险监管 | 严打违规：禁止返佣、隐瞒风险，违规追回佣金，严重吊销资质 | 代理人培训体系需纳入分级资质和合规销售模块 | > **数据截止**: 2026-05-25 | 来源：国家金融监督管理总局、安永Q1分析、行业公开信息 > **声明**: 以上动态供参考，具体以官方最新发布为准 > **English:** AI-powered insurance agent coaching system — parses product documents, generates > personalized question banks, assesses agent competency levels, schedules daily training based on > client visits, and runs interactive role-play drills. Benchmarked against AIA, Ping An, and > Alibaba Cloud insurance training systems. > > **中文:** 保险代理人智能陪练系统——解析产品文档、自动生成问题库、评估代理人能力等级、 > 结合当日客户拜访行程安排个性化训练、进行情景对练。对标友邦保险、平安保险、阿里云智能陪练水平。 --- ## Trigger Keywords / 触发关键词 Immediately activate when user mentions: - 保险陪练 / 产品陪练 / 智能陪练 / 代理人训练 - 代理人培训 / 新人培训 / 保险话术训练 - 产品演练 / 客户异议处理 / 保险销售训练 - agent training / insurance coaching / product drill / sales training - skill assessment / competency evaluation / agent profiling - daily training plan / training schedule / personalized coaching --- ## Core System Architecture / 核心系统架构 ### 0. 2025-2026 代理人销售环境最新变化 | 变化 | 内容 | 话术调整建议 | |------|------|------------| | **预定利率降至3.0%** | 2024年9月后所有新产品执行 | 强调"锁定3.0%长期确定收益"，对比银行理财波动性 | | **分红险主导市场** | 分红险、万能险替代传统高利率产品 | 学会讲"浮动收益+保底保障"的双重价值 | | **健康险新规上线** | 2025年商业健康险管理办法修订 | 健康告知流程需更规范，禁止误导性说明 | | **代理人资格考试升级** | 2025年加入AI伦理、数字化服务模块 | 新人需补充数字化能力培训 | | **企微客户触达合规** | AI外呼需标注身份，营销需客户授权 | 培训合规营销话术，避免违规外呼 | ``` ┌─────────────────────────────────────────────────────────────────┐ │ Insurance Agent Intelligent Trainer │ ├─────────────────────────────────────────────────────────────────┤ │ ┌──────────────┐ ┌──────────────┐ ┌──────────────────────┐ │ │ │ Product Doc │ │ Agent Profile│ │ Daily Schedule/Routes│ │ │ │ Parser │ │ Engine │ │ Integration │ │ │ │ (PDF/Word/ │ │ (Skill Level │ │ (Today's Visits & │ │ │ │ Images) │ │ Assessment) │ │ Client Profiles) │ │ │ └──────┬───────┘ └──────┬───────┘ └──────────┬───────────┘ │ │ │ │ │ │ │ ▼ ▼ ▼ │ │ ┌──────────────────────────────────────────────────────────┐ │ │ │ Question Bank Generation Engine │ │ │ │ Product Knowledge │ Objection Handling │ Case Analysis │ │ │ │ [5 difficulty tiers × 3 categories = 15 question types] │ │ │ └──────────────────────────┬───────────────────────────────┘ │ │ │ │ │ ▼ │ │ ┌──────────────────────────────────────────────────────────┐ │ │ │ Personalized Training Scheduler │ │ │ │ [Skill Level + Schedule + Product Priority = Daily Plan]│ │ │ └──────────────────────────┬───────────────────────────────┘ │ │ │ │ │ ▼ │ │ ┌──────────────────────────────────────────────────────────┐ │ │ │ Interactive Training Engine │ │ │ │ Role-play │ Real-time Feedback │ Progress Tracking │ │ │ └──────────────────────────────────────────────────────────┘ │ └─────────────────────────────────────────────────────────────────┘ ``` --- ## Core Capabilities / 核心能力 ### 1. Product Document Parser / 产品文档解析引擎 **Supported formats:** PDF, Word (.docx), scanned images (with OCR), plain text **Parsing pipeline:** ``` Document Upload │ ▼ [Format Detection] → PDF / Word / Image / Text │ ▼ [Text Extraction] → Raw text content │ ▼ [Structure Analysis] ├─ Product name, type, target customers ├─ Coverage scope (death, medical, annuity, critical illness, etc.) ├─ Premium levels & payment periods ├─ Policy terms & exclusions ├─ Sales pitch key points ├─ Competitive advantages vs. similar products └─ Compliance notes & regulatory requirements │ ▼ [Structured Product Profile] → Ready for question generation ``` **Output: Structured Product Profile JSON** ```json { "product_name": "XX福享人生终身寿险(万能型)", "product_type": "whole-life insurance with universal account", "insurer": "国联人寿", "target_customers": ["30-50岁中高收入人群", "有财富传承需求"], "coverage": { "death_benefit": "100%-160%账户价值", "annuity_option": "60岁起可转换为年金", "waiver": "可选投保人保费豁免" }, "premium": { "min_annual": 12000, "payment_periods": ["3年", "5年", "10年", "20年"], "min_coverage_years": "终身" }, "key_selling_points": [ "复利增值，万能账户历史结算利率4.5%-5.2%", "灵活追加，额外资金可随时进入万能账户", "身故保障与财富传承双重功能" ], "competitive_edges": ["结算利率优于同类竞品", "追加无上限"], "exclusions": ["投保人对被保险人的故意伤害", "2年内自杀(无民事行为能力人除外)"], "compliance_notes": ["需双录(录音录像)", "犹豫期15天", "等待期90天"], "difficulty_tags": ["新人友好", "需强化健康告知", "财务规划综合能力"] } ``` --- ### 2. Agent Profile & Skill Assessment / 代理人画像与能力评估 **Three skill tiers:** | Tier | Level | Description | Training Focus | |------|-------|-------------|----------------| | 🌱 **L1 - 入门级** | Beginner | < 1 year experience, struggles with product details and objection handling | Foundation: product knowledge, basic sales scripts, simple objection responses | | ⚡ **L2 - 进阶级** | Intermediate | 1-3 years, solid product knowledge but inconsistent closing rate | Application: complex scenarios, multi-product combination, competitive replacement, high-net-worth clients | | 🎯 **L3 - 专家级** | Advanced | 3+ years, high performance, needs strategy for complex cases | Mastery: enterprise/group clients, tax planning, estate planning, competitive stealing, mentoring skills | **Profile structure:** ```json { "agent_id": "AG20240001", "name": "张明", "level": "L2", "level_label": "进阶级", "tenure_years": 2.5, "certifications": ["保险代理人资格证", "健康险销售资质"], "performance": { "monthly_premium_target": 50000, "monthly_premium_actual": 42000, "closing_rate": 0.32, "avg_policy_size": 18500, "new_customer_rate": 0.45 }, "product_mastery": { "term_life": 0.85, "whole_life": 0.72, "critical_illness": 0.58, "medical_insurance": 0.80, "annuity": 0.45, "investment_linked": 0.38 }, "weak_points": [ "健康险异议处理不够熟练", "不了解高端客户的税务筹划需求", "组合产品销售话术单一" ], "strong_points": [ "老客户维护能力强", "缘故市场开拓优秀" ], "daily_schedule": [ {"time": "09:00-10:00", "activity": "晨会", "location": "营业部"}, {"time": "10:30-12:00", "activity": "拜访客户A（国企中层，有养老需求）", "location": "客户公司"}, {"time": "14:00-15:30", "activity": "拜访客户B（私企业主，健康险需求）", "location": "客户公司"}, {"time": "16:00-17:30", "activity": "缘故客户C（教育金规划）", "location": "咖啡厅"} ] } ``` --- ### 3. Question Bank Generation / 问题库自动生成 **Generated from product profile + agent level + training objectives** #### Question Types (15 categories across 3 dimensions) **By Category:** | Category | Description | Example | |----------|-------------|---------| | **产品知识** | Product features, terms, coverage | "XX福的等待期是多久？" | | **客户画像** | Target customer identification | "什么样的客户适合购买这款产品？" | | **异议处理** | Objection handling scripts | "客户说'我已经有社保了，不需要商业保险'，如何回应？" | | **案例分析** | Real case discussion | "40岁国企中层，年薪50万，如何用这款产品做养老规划？" | | **合规话术** | Compliance-approved scripts | "如何向客户解释犹豫期和退保损失？" | | **竞品对比** | vs. competitors | "相比平安福，这款产品的核心优势是什么？" | | **促成话术** | Closing techniques | "客户表现出购买意向，如何自然促成？" | | **交叉销售** | Multi-product combination | "如何将主险与医疗险组合销售？" | **By Difficulty (5 tiers):** | Level | Target Audience | Question Complexity | |--------|----------------|---------------------| | ⭐ 基础 | L1新人 | 单一产品，单一问题，直接答案 | | ⭐⭐ 入门 | L1-L2 | 单一产品，1-2个知识点，需要解释 | | ⭐⭐⭐ 进阶 | L2 | 单一产品，3-5个知识点，需组合分析 | | ⭐⭐⭐⭐ 高阶 | L2-L3 | 多产品组合，竞争替换，高净值客户 | | ⭐⭐⭐⭐⭐ 专家 | L3 | 综合方案，税务筹划，财富传承 | #### Question Bank Generation Prompt: ``` Based on the product profile provided, generate a question bank with: 1. For each difficulty tier (基础/入门/进阶/高阶/专家): - 5 multiple choice questions (产品知识) - 3 case analysis questions - 3 objection handling scenarios - 2 competitive comparison questions - 1 closing technique exercise 2. Total: 65+ questions per product 3. For each question, provide: - Question text - Difficulty level (1-5) - Category (产品知识/异议处理/案例分析/竞品对比/促成话术) - Ideal answer / model response - Evaluation criteria (excellent/good/needs-improvement) - Coaching tips for the trainer ``` --- ### 4. Personalized Training Scheduler / 个性化训练调度引擎 **Input factors:** ``` Agent Profile (Level + Weak Points) + Today's Client Schedule (Who → What need → What product) + Product Priority Matrix = Personalized Daily Training Plan ``` **Scheduling Algorithm:** ```python def generate_daily_training_plan(agent_profile, daily_schedule, products): """ Generate personalized training plan for the day. """ # Step 1: Identify today's client visit products today_products = extract_products_from_schedule(daily_schedule) # Step 2: Get agent's weakness areas for these products weakness_map = get_weakness_for_products( agent_profile.weak_points, today_products ) # Step 3: Calculate training time available available_minutes = calculate_available_training_time(daily_schedule) # Step 4: Prioritize by impact × weakness × product value training_queue = prioritize_training( weakness_map, today_products, agent_profile.level, time_constraint=available_minutes ) # Step 5: Generate session plan sessions = split_into_sessions(training_queue, available_minutes) return { "date": today, "agent": agent_profile.name, "total_minutes": available_minutes, "sessions": sessions, "focus_products": today_products, "key_objectives": get_key_objectives(training_queue) } ``` **Example Daily Training Plan:** ```json { "date": "2026-05-05", "agent": "张明", "level": "L2", "total_minutes": 90, "sessions": [ { "time": "08:00-08:20", "duration": 20, "type": "晨间快练", "mode": "快问快答", "focus": "年金险产品知识（高频问题5题）", "product": "福享人生终身寿险", "objective": "巩固年金转换权的计算逻辑" }, { "time": "12:30-13:00", "duration": 30, "type": "午间强化", "mode": "情景对练", "focus": "健康险异议处理", "scenario": "客户："我有社保，不需要商业医疗险"", "product": "康健医疗保险", "level": "⭐⭐⭐ 进阶", "coaching_tips": "引导客户认识到社保报销比例上限，用自费药比例对比引发需求" }, { "time": "17:30-18:30", "duration": 40, "type": "晚间复盘", "mode": "案例分析 + 角色扮演", "focus": "私企业主综合保障方案", "scenario": "45岁私企老板，年收入200万，已有多份保单，如何做加保方案？", "products": ["终身寿险+万能账户", "高端医疗", "企业财产险"], "level": "⭐⭐⭐⭐ 高阶", "model_response_guide": "从家庭资产与企业资产隔离角度切入，引出终身寿险的债务隔离和传承功能" } ], "key_metrics_to_track": [ "异议处理响应时间（目标<30秒）", "产品知识点正确率（目标>85%）", "方案组合完整性（3单以上产品覆盖）" ] } ``` --- ### 5. Interactive Training Session / 智能陪练对话引擎 **Session modes:** | Mode | Description | Duration | Best For | |------|-------------|----------|----------| | **快问快答** | Rapid-fire Q&A | 5-10 min | Pre-meeting warmup | | **情景对练** | Role-play (client vs. agent) | 15-30 min | Skill practice | | **案例研讨** | Real case analysis | 20-40 min | Advanced agents | | **异议攻关** | Objection busting focus | 10-15 min | Weak point training | | **综合考核** | Full simulation exam | 30-60 min | Level assessment | **Real-time coaching during training:** ``` Agent Response │ ▼ [Natural Language Understanding] → Extract key claims, tone, strategy │ ▼ [Evaluation Engine] ├─ Product knowledge accuracy ✓/✗ ├─ Objection handling effectiveness (1-5) ├─ Compliance adherence ✓/✗ ├─ Closing attempt timing (good/early/late/missing) ├─ Client empathy signals ✓/✗ └─ Product combination logic ✓/✗ │ ▼ [Real-time Coaching Feedback] ├─ Immediate tip (if struggling): "💡 提示：可以先问客户目前的保障缺口..." ├─ Completion praise (if excellent): "🌟 完美！您已经很好地识别了客户需求" └─ Post-question summary: "本轮得分 85/100。建议加强：竞品对比环节" ``` **Training session flow:** ``` 1. 导入 (5%) → 介绍训练目标和产品背景 2. 暖场 (10%) → 快问快答热身，激活产品知识 3. 主体 (60%) → 情景对练：客户角色扮演 + 实时点评 4. 复盘 (20%) → AI给出详细反馈：优点/不足/改进建议 5. 行动 (5%) → 下次拜访的具体行动计划 ``` --- ### 6. Effect Assessment & Progress Tracking / 效果评估与进度追踪 **Metrics tracked per session:** | Metric | Definition | Target | |--------|------------|--------| | **产品知识得分** | 知识点正确率 | L1: ≥70%, L2: ≥80%, L3: ≥90% | | **异议处理时效** | 从异议提出到满意回答的时间 | < 30秒 | | **促成成功率** | 能否自然引入促成信号 | ≥ 1次有效尝试 | | **话术合规率** | 合规敏感词使用正确性 | 100% | | **方案完整性** | 保障覆盖广度 | ≥ 3个维度 | **Progress report structure:** ```markdown ## 📊 代理人张明 训练报告 - 2026-05-05 ### 综合得分: ⭐⭐⭐⭐ (78/100) | 维度 | 本次得分 | 较上次 | 目标 | |------|---------|--------|------| | 产品知识 | 82/100 | ↑5 | 80+ | | 异议处理 | 71/100 | ↓3 | 75+ | | 促成技巧 | 85/100 | ↑8 | 80+ | | 合规话术 | 95/100 | →0 | 100 | | 方案设计 | 72/100 | ↑12 | 75+ | ### 🔥 本次表现亮点 1. 养老规划方案逻辑清晰，能结合客户生命周期讲解 2. 合规话术使用规范，犹豫期/退保说明完整 ### ⚠️ 需要加强 1. 健康险异议处理：回应"已有社保"时过于被动，应主动算账 2. 竞品对比：对中国平安主要产品线不够熟悉 ### 📅 明日训练重点 - 产品：康健医疗保险（健康告知流程） - 场景：竞品替换（平安福 vs. XX福） - 时长：30分钟情景对练 + 10分钟快问快答 ``` --- ## Workflow / 标准工作流程 ### Mode 1: Quick Start (已知产品 + 快速训练) ``` User: "帮我准备明天拜访客户B的训练，他是私企老板，对健康险感兴趣" │ ▼ [Step 1] 获取代理人信息 → 张明，L2，弱项：健康险异议处理 [Step 2] 识别拜访产品 → 康健医疗保险（目标：替换平安福） [Step 3] 生成训练计划 → 午间30分钟：健康险异议处理对练 [Step 4] 开始陪练 → 情景对练：私企业主健康险需求挖掘 [Step 5] 实时反馈 → 异议处理评分：71/100，给出改进建议 [Step 6] 报告输出 → 训练报告 + 明日拜访话术优化建议 ``` ### Mode 2: Product Document Upload (上传产品文档) ``` User: [上传 XX保险公司福享人生终身寿险 产品手册 PDF] │ ▼ [Step 1] 解析文档 → 提取产品结构、条款、卖点 [Step 2] 生成产品画像 → Structured JSON Profile [Step 3] 生成问题库 → 65+道题目（5难度×8类别） [Step 4] 与现有产品库合并 → 更新知识库 [Step 5] 等待选择 → "请选择训练模式：快问快答 / 情景对练 / 案例研讨" ``` ### Mode 3: Full Agent Assessment (全面能力评估) ``` User: "帮我评估代理人李华的综合能力，她入职8个月，主要卖重疾险" │ ▼ [Step 1] 建立代理人档案 → L1入门级，8个月，重疾险方向 [Step 2] 产品文档上传 → 重疾险产品手册 [Step 3] 综合考核 → 30题产品知识 + 5个情景对练 [Step 4] 生成能力雷达图 → 6维度能力可视化 [Step 5] 制定成长路径 → 90天训练计划 ``` --- ## Input / Output Specifications / 输入输出规范 ### Input | Input Type | Description | Example | |------------|-------------|---------| | 代理人档案 | JSON/文本描述 | 姓名、级别、工龄、业绩、弱项 | | 产品文档 | PDF/Word/TXT/图片 | 保险产品手册、条款、计划书 | | 当日行程 | 文本/日历 | 09:00晨会 / 10:30拜访客户A | | 训练指令 | 自然语言 | "帮我准备健康险的陪练" | | 客户信息 | 文本描述 | "45岁私企老板，年收入200万" | ### Output | Output Type | Description | |-------------|-------------| | 产品画像JSON | 结构化产品信息 | | 问题库 | 65+道分类分级题目 | | 训练计划 | 分钟级个性化日程 | | 陪练对话 | 实时AI角色扮演 | | 评估报告 | 评分 + 改进建议 + 雷达图 | | 成长路径 | 30/60/90天训练建议 | --- ## Integration Notes / 集成说明 **Data privacy:** - All agent and client data remains local / within the company's system - No sensitive PII should be included in training documents - Comply with China CBIRC insurance sales compliance regulations **Lianxi with other Skills:** - `insurance-bidding-pro`: Use product analysis for bidding scenarios - `insurance-private-domain-ops`: Link training completion to customer follow-up - `insurance-claims-intelligence`: Train agents on claim processes for better client communication --- ## Disclaimer / 免责声明 > ⚠️ **Training is advisory only.** This skill provides coaching materials, question banks, > and simulation training for insurance agent development. All final sales advice, > compliance decisions, and product recommendations must be reviewed by licensed > insurance professionals and comply with CBIRC regulations. Model answers represent > reference best practices, not guaranteed outcomes. --- ## 附录G：阿里点金(Dianjin)融合精华 — 客户画像与保障缺口分析 ### G.1 核心工作流程（Dianjin融合版） #### 步骤1：客户画像构建 | 画像维度 | 分析要点 | 输出成果 | |---------|---------|---------| | **人口统计** | 年龄、性别、职业、收入、家庭结构 | 客户基础画像报告 | | **风险偏好** | 风险承受能力、投资经验、理财目标 | 风险偏好评级（保守/稳健/进取） | | **保险需求** | 保障缺口、责任负担、未来规划 | 保险需求分析报告 | | **购买行为** | 历史购买、决策风格、信息渠道 | 销售策略建议 | #### 步骤2：保障缺口分析 | 缺口类型 | 计算方法 | 建议策略 | |---------|---------|---------| | **寿险缺口** | 责任负担-已有保额-可变现资产 | 定期寿险/终身寿险建议 | | **重疾缺口** | 治疗费用+收入损失-已有保额 | 重疾险/医疗险建议 | | **医疗缺口** | 预期医疗费-社保报销-已有保险 | 百万医疗/高端医疗建议 | | **养老缺口** | 预期养老支出-社保养老金-个人储蓄 | 年金险/养老社区建议 | #### 步骤3：计划书生成 - **计划书结构**：客户画像 → 保障缺口 → 产品方案 → 利益演示 → 对比分析 - **方案设计**：主险+附加险组合、保额/期限/缴费期设计 - **利益演示**：现金价值表、保障利益表、分红/万能演示 #### 步骤4：异议处理与成交 - **异议类型**：价格异议、需求异议、产品异议、公司异议 - **处理话术**：同理心+专业解释+案例佐证+促成技巧 - **成交信号**：肢体语言、提问细节、主动要求方案 --- ### G.2 风险评分机制（Dianjin精髓） | 风险维度 | 评分指标 | 权重 | 风险阈值 | |---------|---------|------|---------| | 需求匹配 | 产品与客户需求匹配度 | 30% | 匹配度<60% | | 负担能力 | 保费/收入比、续保能力 | 25% | 保费/收入比>20% | | 诚信风险 | 告知真实性、历史记录 | 20% | 告知不实或历史违规 | | 合规风险 | 销售合规、适当性管理 | 15% | 销售过程不合规 | | 声誉风险 | 客户满意度、投诉记录 | 10% | 客户投诉或负面评价 | **综合风险等级**： - 低风险（0-20分）：需求匹配，正常承保 - 中风险（21-40分）：需求基本匹配，关注负担能力 - 高风险（41-60分）：需求不匹配或负担能力不足，审慎承保 - 极高风险（61-80分）：诚信风险或合规风险，拒绝承保或报警 --- ### G.3 合规约束（Dianjin精髓） 1. **不适用边界**：本技能不适用于医学诊断、法律建议，此类需求需转交医疗或法律专业人士 2. **禁止承诺**：不使用"一定赔付""guaranteed payout"等承诺性表述 3. **禁止替代决策**：仅输出分析建议，最终承保决策由核保师/核保主管出具 4. **数据溯源**：客户数据、健康状况必须标注来源和获取日期 5. **隐私保护**：客户信息、健康状况必须保密 6. **客观中立**：销售不得误导客户，须客观呈现产品利弊 --- ### G.4 测试用例（Dianjin精髓） | 用例ID | 输入场景 | 预期输出 | 验证点 | |--------|---------|---------|---------| | TC001 | 客户35岁，家庭年收入50万，有房贷200万，已有寿险100万 | 寿险缺口100万，建议加保100万定期寿险 | 缺口计算准确 | | TC002 | 客户45岁，家庭年收入30万，保费预算5万/年 | 保费/收入比16.7%，建议控制在4-6万/年 | 负担能力评估合理 | | TC003 | 客户55岁，有高血压糖尿病史，未如实告知 | 极高风险（70分），建议如实告知或拒保 | 诚信风险评估准确 | --- ### G.5 关联技能（Dianjin精髓） - **保险理赔专家**（`insurance-claims-intelligence`）：提供理赔材料分析、责任认定、欺诈检测 - **保险反欺诈**（`insurance-anti-fraud`）：提供欺诈检测、风险评分、异常模式识别 - **保险核保专家**（`insurance-actuarial-cn`）：提供核保规则、健康核验、风险分类 --- *融合来源：阿里点金(Dianjin) insurance-agent* *融合时间：2026-05-31*


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)