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existing features remain unchanged.\n\nv2.0.0 | 2026-05-11T14:31:15.657Z | auto\n\n**Major upgrade with detailed ESG analysis tools and bilingual support.**\n\n- Introduces comprehensive ESG rating comparison and normalization across multiple providers.\n- Adds step-by-step carbon footprint calculation, including Scope 1, 2, and 3 emissions analysis.\n- Provides a structured green bond assessment framework and environmental benefit quantification.\n- Lists industry pain points and how the skill addresses them, for both Chinese and international ESG contexts.\n- Expanded and refined trigger keywords and descriptions in both English and Chinese.\n- Skill documentation and capabilities are now fully bilingual.\n\nArchive index:\n\nArchive v3.0.3: 3 files, 13925 bytes\n\nFiles: skill-card.md (1966b), SKILL.md (30663b), _meta.json (141b)\n\nFile v3.0.3:SKILL.md\n\n---\r\nname: ESG Investment Analysis Assistant\r\nslug: security-esg-investing\r\ndescription: AI-powered ESG investing analysis assistant for China market — compares ESG ratings across providers, screens green bonds, accounts for Scope 1/2/3 carbon emissions, and builds sustainable portfolios. Scope: ESG/sustainability analysis applied to investment decisions only; not general corporate ESG consulting, not climate policy research. Keywords: ESG rating comparison, green bond screening, carbon footprint accounting, Scope 3, sustainable portfolio construction, greenwashing check, China ESG, ESG评级对比, 绿色债券筛选, 碳足迹核算, 碳核算Scope3, 可持续组合构建, 漂绿识别, ESG披露口径.\r\nversion: \"3.0.3\"\r\n---\r\n\r\n# ESG Investment Analysis Assistant / ESG投资分析助手\r\n\r\n> **English:** AI-powered ESG investing analysis assistant — covers ESG rating comparison, green finance products, carbon accounting, and sustainable portfolio construction. Built for ESG analysts and sustainable investors.\r\n>\r\n> **中文:** ESG投资分析助手——覆盖ESG评级对比、绿色金融产品筛选、碳核算、可持续组合构建。适用：ESG分析师、可持续基金经理、机构投资者。\r\n\r\n\r\n## 数据最小化声明与执行边界 / Data Minimisation & Execution Boundary\r\n\r\n**数据最小化前置声明：** 使用本技能时，请只提供ESG分析所必需的输入——标的代码或公司名称、公开披露的排放与能耗数据、外部ESG评级结果、已脱敏的组合权重。**不要**粘贴未公开的企业能耗台账、供应商名单、员工个人信息、客户身份信息或受保密协议约束的尽职调查材料；企业侧数据请用\"行业+量级\"的脱敏形式提供。\r\n\r\n**保存与预览确认：** 本技能不执行任何保存动作。若你在自己环境中依据本技能生成ESG评级报告、碳核算表或绿债筛选结论，请在落盘或对外报送前**先预览结果、确认口径与数据来源无误，再保存或提交**。\r\n\r\n**代码块性质与执行边界**\r\n\r\n| 内容 | 性质 | 谁来执行 |\r\n|------|------|---------|\r\n| `ESGAnalyzer` 类（评级标准化/综合评分） | 评级归一化与加权口径的说明 | 由ESG分析师在自有研究系统中取数复现；技能不取数、不运行 |\r\n| `CarbonAnalyzer` 类（Scope 1/2/3） | 排放因子与核算边界的示意 | 由ESG分析师在自有系统中配置并运行 |\r\n| `calculate_green_benefits()` | 环境效益折算的算法表达 | 同上，属教学示意；折算系数须取自发行文件 |\r\n| 筛选矩阵、打分表、检查表 | 管理用模板 | 由研究/合规人员在机构流程中落实 |\r\n\r\n本技能未配置任何工具调用权限，不执行代码、不读写文件、不访问外部ESG数据库或行情数据源，也不生成可直接报送的监管报表。文中代码块均为口径的教学示意，读者可在自己环境中参考实现；ESG评级与碳核算结果须经独立复核后方可用于决策。\r\n\r\n---\r\n\r\n---\r\n\r\n\r\n### 证券监管最新动态 [2026-10-08更新]\r\n\r\n| 动态类型 | 内容摘要 | 影响范围 | ESG侧应对动作 | 责任岗 | 优先级 | 复核频率 | |\r\n|---------|---------|---------|-------------|-------|-------|---|\r\n| 证券监管 | 2026年Q1：ESG信息披露要求扩大至非上市企业 | ESG投资分析框架需更新最新信披要求和绿色金融政策 | 供应链ESG数据采集范围同步扩大 | 研究 | 高 | 每季 |\r\n| 证券监管 | 绿色金融信贷导向政策升级，ESG投资环境改善 | ESG投资分析框架需更新最新信披要求和绿色金融政策 | 绿色资产识别标准与信贷口径对齐 | 研究 | 中 | 每季 |\r\n| 证券监管 | 证监会加强ESG相关信披监管，ESG评级标准趋严 | ESG投资分析框架需更新最新信披要求和绿色金融政策 | 评级来源与取数日期须在报告中标注 | 合规 | 高 | 每月 |\r\n| 可持续披露 | 可持续披露规则推进，披露范围与颗粒度提升 | ESG评级输入数据、组合披露 | 建立披露数据映射表，统一口径 | 研究 | 高 | 每季 |\r\n| 反漂绿 | 绿色宣传与绿色产品命名合规要求趋严 | 绿色基金命名、宣传物料 | 产品命名与投资范围一致性自查 | 合规 | 高 | 每季 |\r\n| 碳市场 | 碳市场覆盖行业范围与交易规则持续完善 | 碳成本测算、高碳行业敞口 | 碳价情景纳入估值敏感性 | 研究 | 中 | 每月 |\r\n| 绿色债券 | 绿色债券募集资金用途与存续期披露要求细化 | 绿债筛选与投后跟踪 | 存续期环境效益跟踪清单化管理 | 研究 | 中 | 每季 |\r\n| 数据合规 | ESG数据来源与第三方数据使用需合规授权 | 外部评级与数据库采购 | 数据来源授权凭证归档，标注使用范围 | 合规 | 中 | 每季 |\r\n| 可持续披露 | 2026年10月：可持续披露的指标颗粒度与可比性要求进一步细化，跨期数据须可追溯 | ESG评级输入、组合定期披露 | 建立指标口径台账，同一指标的跨期变化须标注统计方法是否变更 | 研究 | 高 | 每季 |\r\n| 碳市场 | 2026年四季度初：碳市场行业覆盖范围与配额分配规则的调整预期增强 | 碳成本测算、高碳行业敞口 | 碳价情景由单档改为上下行双档，敏感性分析同步更新 | 研究 | 中 | 每月 |\r\n\r\n> **数据截止**: 2026-10-08 | 来源：证监会、生态环境部门公开规则、交易所公开信息\r\n> **声明**: 以上动态供参考，具体以官方最新发布为准\r\n\r\n**动态解读示例（四类高频场景）**\r\n\r\n- **场景A｜反漂绿自查**：某产品命名为\"绿色低碳\"但持仓含高碳行业标的 → 命中\"命名与投资范围一致性\"问题 → 要么调整持仓以匹配命名，要么修改产品名称与宣传口径，并留存自查记录。\r\n- **场景B｜披露口径映射**：评级输入中\"碳排放\"既有总量又有强度，混用于同一模型 → 命中\"口径统一\"要求 → 建立披露数据映射表，明确每项指标的来源、单位与报告期。\r\n- **场景C｜碳价情景敏感性**：估值模型未考虑碳成本 → 命中\"碳成本纳入测算\"要求 → 在敏感性分析中增加碳价上下行情景对高碳标的利润率与估值的影响。\r\n- **场景D｜数据授权**：ESG评级数据采购后用于对外报告但无授权范围说明 → 命中\"数据来源合规\"要求 → 归档授权凭证并注明可使用的场景，超范围使用需另行申请。\r\n\r\n## Industry Pain Points / 行业痛点\r\n\r\n| Pain Point / 痛点 | Impact / 影响 | Solution / 本Skill解决方案 | 量化基线指标 / Baseline |\r\n|------------------|-------------|------------------------|----------------------|\r\n| **ESG数据分散** | 评级机构超过10家，标准不统一 | 跨评级对比框架+综合评分 | 覆盖机构 ≥4家，分歧度可量化 |\r\n| **\"漂绿\"风险** | 虚假绿色宣传导致合规风险 | 实质性分析+数据核实 | 绿色收入占比可核查率 100% |\r\n| **碳核算复杂** | Scope 1/2/3核算专业门槛高 | 分级碳核算模板+简化方法 | Scope 1/2 数据覆盖率 100% |\r\n| **政策变化快** | 碳市场/ESG披露要求频繁更新 | 实时政策跟踪+合规提醒 | 政策更新响应 ≤5个工作日 |\r\n| **评级分歧** | 同一公司评级差异大，难以决策 | 分歧归因表+一致性检验 | 分歧>2档时须专项说明 |\r\n| **数据不可比** | 不同来源口径不一致 | 口径映射表 | 指标口径一致率 100% |\r\n| **投后跟踪缺失** | 绿债与绿色项目投后无跟踪 | 存续期跟踪清单 | 环境效益跟踪覆盖率 100% |\r\n| **负面事件滞后** | 重大ESG事件未及时反映 | 事件监控与复核机制 | 重大事件响应 ≤3个工作日 |\r\n\r\n---\r\n\r\n## Trigger Keywords / 触发关键词\r\n\r\n**English Triggers (ESG analysis applied to an investment decision only):** compare ESG ratings, ESG rating divergence, green bond screening, carbon footprint accounting, Scope 3 emissions, sustainable portfolio construction, greenwashing check, ESG disclosure mapping\r\n\r\n**English Non-Triggers:** sustainability, green finance, carbon neutral, ESG reporting, climate policy, corporate social responsibility — these alone do **not** route here unless the task is to analyse or screen an investable asset or portfolio.\r\n\r\n**中文触发词（须落在\"对标的可投组合做ESG分析或筛选\"任务上才触发）：** ESG评级对比 / 跨机构ESG评级分歧 / 绿色债券筛选 / 绿色债券认定 / 碳足迹核算 / Scope 3核算 / 碳强度对标 / 可持续组合构建 / 漂绿识别 / ESG披露口径映射 / ESG负面事件排查 / 高碳敞口测算\r\n\r\n**不触发（Scope Exclusions）：** 以下泛化词单独出现时**不**触发本技能——可持续发展、碳中和、碳达峰、绿色金融、ESG报告、气候政策、企业社会责任。它们只有在明确指向\"对某个标的或组合做ESG评级、碳核算、绿债筛选或可持续构建\"时才路由到本技能；泛化的ESG概念咨询、企业ESG报告代写、气候政策研究请改用对应技能。\r\n\r\n**路由判定三步：** ① 输入是否为可投标的/组合或一只具体债券？② 任务是否为评级对比、碳核算、绿债筛选、漂绿识别或组合构建？③ 两者同时为\"是\"才启用。只问ESG概念定义不启用。\r\n\r\n---\r\n\r\n## Core Capabilities / 核心能力\r\n\r\n### 1. ESG Rating Analysis / ESG评级分析\r\n\r\n```python\r\nclass ESGAnalyzer:\r\n    \"\"\"ESG评级分析\"\"\"\r\n    \r\n    RATING_PROVIDERS = {\r\n        \"MSCI\": {\"scale\": \"CCC-AAA\", \"weight\": {\"E\": 0.25, \"S\": 0.25, \"G\": 0.50}},\r\n        \"Sustainalytics\": {\"scale\": \"0-100\", \"weight\": {\"E\": 0.33, \"S\": 0.33, \"G\": 0.33}},\r\n        \"商道融绿\": {\"scale\": \"D-A+\", \"weight\": {\"E\": 0.30, \"S\": 0.30, \"G\": 0.40}},\r\n        \"中证ESG\": {\"scale\": \"C-AAA\", \"weight\": {\"E\": 0.20, \"S\": 0.20, \"G\": 0.60}},\r\n        \"华证ESG\": {\"scale\": \"C-AAA\", \"weight\": {\"E\": 0.25, \"S\": 0.30, \"G\": 0.45}},\r\n        \"Wind ESG\": {\"scale\": \"1-10\", \"weight\": {\"E\": 0.30, \"S\": 0.30, \"G\": 0.40}}\r\n    }\r\n    \r\n    def normalize_rating(self, provider: str, raw_score: float) -> float:\r\n        \"\"\"标准化评分到0-100\"\"\"\r\n        if provider == \"MSCI\":\r\n            scale = {\"CCC\": 10, \"B\": 20, \"BB\": 35, \"BBB\": 50, \"A\": 65, \"AA\": 80, \"AAA\": 95}\r\n            return scale.get(raw_score, 50)\r\n        elif provider == \"Sustainalytics\":\r\n            return 100 - raw_score  # 反转，风险分数→ESG分数\r\n        elif provider == \"商道融绿\":\r\n            scale = {\"D\": 20, \"C\": 40, \"B\": 60, \"B+\": 70, \"A\": 85, \"A+\": 95}\r\n            return scale.get(raw_score, 50)\r\n        elif provider == \"华证ESG\":\r\n            scale = {\"C\": 20, \"CC\": 30, \"CCC\": 40, \"B\": 50, \"BB\": 60, \"BBB\": 70,\r\n                     \"A\": 80, \"AA\": 90, \"AAA\": 95}\r\n            return scale.get(raw_score, 50)\r\n        elif provider == \"Wind ESG\":\r\n            # Wind 为 1-10 分制，线性映射到 0-100\r\n            return float(raw_score) * 10\r\n        return raw_score\r\n    \r\n    def comprehensive_analysis(self, company: str, \r\n                               ratings: dict) -> dict:\r\n        \"\"\"综合ESG分析\"\"\"\r\n        normalized = {\r\n            provider: self.normalize_rating(provider, score)\r\n            for provider, score in ratings.items()\r\n        }\r\n        \r\n        # 加权综合评分\r\n        weights = [0.30, 0.25, 0.25, 0.20]  # 权重分配\r\n        providers = list(normalized.keys())\r\n        comprehensive = sum(\r\n            normalized[p] * w \r\n            for p, w in zip(providers, weights)\r\n        )\r\n        \r\n        return {\r\n            \"comprehensive_score\": round(comprehensive, 1),\r\n            \"rating_level\": self._score_to_level(comprehensive),\r\n            \"individual_ratings\": normalized,\r\n            \"key_strengths\": self._identify_strengths(normalized),\r\n            \"key_concerns\": self._identify_concerns(normalized),\r\n            \"peer_comparison\": self._compare_to_peer(company, comprehensive)\r\n        }\r\n    \r\n    def _score_to_level(self, score: float) -> str:\r\n        levels = {\r\n            (90, 100): \"AAA - 卓越\",\r\n            (80, 90): \"AA - 优秀\",\r\n            (70, 80): \"A - 良好\",\r\n            (60, 70): \"BBB - 平均偏上\",\r\n            (50, 60): \"BB - 平均\",\r\n            (40, 50): \"B - 低于平均\",\r\n            (0, 40): \"CCC/B - 落后\"\r\n        }\r\n        for (low, high), level in levels.items():\r\n            if low <= score <= high:\r\n                return level\r\n        return \"未知\"\r\n```\r\n\r\n**跨评级机构分歧表（分歧本身也是信息）**\r\n\r\n| 评级机构 | 原始评级 | 标准化得分 | 与均值偏离 | 可能的解释 |\r\n|---------|---------|-----------|-----------|-----------|\r\n| MSCI | BB | 35.0 | −18.4 | 对治理与信息披露要求较严 |\r\n| Sustainalytics | 38（风险分） | 62.0 | +8.6 | 偏重风险暴露口径 |\r\n| 商道融绿 | B+ | 70.0 | +16.6 | 侧重国内披露实践 |\r\n| 中证ESG | BBB | 70.0 | +16.6 | 治理权重较高 |\r\n| 综合得分 | — | **53.4（BB-平均）** | — | 分歧较大，需专项说明 |\r\n\r\n**示例 1｜评级分歧的两种处理方式**\r\n\r\n| 分歧程度 | 判定 | 处理方式 | 报告写法 |\r\n|---------|------|---------|---------|\r\n| ≤1档 | 一致 | 直接采用综合得分 | \"各机构评级基本一致\" |\r\n| 2档 | 中度分歧 | 取中位数并说明 | \"评级存在差异，主要源于治理维度权重不同\" |\r\n| >2档 | 高度分歧 | 逐一归因，不强行合并 | \"评级分歧显著，建议以原始披露数据为准做独立判断\" |\r\n\r\n**示例 2｜标准化映射的注意事项**\r\n\r\n| 问题 | 原因 | 正确做法 |\r\n|------|------|---------|\r\n| Sustainalytics 分数越高越差 | 其分制为\"风险分\" | 用 100 减后再入表，并注明已反转 |\r\n| MSCI 无 BBB- 等档位 | 档位为离散七级 | 用映射表而非线性插值 |\r\n| 评级更新不同步 | 各机构更新频率不同 | 每项标注评级发布日期，取最近一期 |\r\n| 分母口径不同 | 有的按市值、有的按营收 | 强度类指标须统一分母并标注 |\r\n\r\n\r\n**示例 3｜评级分歧归因的落地写法（分歧>2档时必做）**\r\n\r\n| 分歧维度 | MSCI 观点 | 商道融绿观点 | 分歧根因 | 处理结论 |\r\n|---------|----------|------------|---------|---------|\r\n| 治理（G） | 权重50%，扣分显著 | 权重40%，扣分较轻 | 权重与扣分门槛不同 | 采用原始披露数据独立判断 |\r\n| 环境（E） | 未纳入供应链排放 | 纳入部分上游排放 | 核算边界不同 | 以范围更宽者做保守口径 |\r\n| 数据时效 | 评级日期2025-11 | 评级日期2026-06 | 更新频率不同 | 以最近一期为主，旧值标注日期 |\r\n\r\n归因要点：分歧>2档时不得强行取平均。正确做法是按维度拆开归因（权重差异/边界差异/时效差异），然后给出\"采用哪一口径、为什么\"的结论；若三个维度都指向同一方向，则说明分歧是实质性的，应在报告中明示并建议以原始披露为准。\r\n\r\n**示例 4｜综合评分权重设定的两种方案**\r\n\r\n| 方案 | 权重逻辑 | 优点 | 局限 | 适用 |\r\n|------|---------|------|------|------|\r\n| 等权 | 各机构各占1/N | 不预设机构优劣 | 忽略评级质量差异 | 机构数量少、质量接近 |\r\n| 质量加权 | 按历史预测力/覆盖率赋权 | 突出更可靠的机构 | 权重设定需说明依据 | 机构数量≥4家 |\r\n| 单机构主口径 | 以一家为主、其余作对照 | 口径清晰可追溯 | 依赖单一来源 | 客户指定评级机构时 |\r\n\r\n使用要点：权重方案一旦选定应跨期保持一致，变更须留记录；报告中须写明所用方案，否则不同期的综合得分不可比。\r\n\r\n### 2. Carbon Footprint Analysis / 碳足迹分析\r\n\r\n```python\r\nclass CarbonAnalyzer:\r\n    \"\"\"碳足迹核算\"\"\"\r\n    \r\n    def calculate_carbon_footprint(self, company_data: dict) -> dict:\r\n        \"\"\"\r\n        计算碳足迹（Scope 1, 2, 3）\r\n        \"\"\"\r\n        # Scope 1: 直接排放\r\n        scope1 = (\r\n            company_data.get(\"fuel_combustion\", 0) * 2.02 +  # CO2系数\r\n            company_data.get(\"vehicle_fleet\", 0) * 2.32 +\r\n            company_data.get(\"fugitive_emissions\", 0) * 25  # CH4当量\r\n        )\r\n        \r\n        # Scope 2: 间接排放（电力）\r\n        scope2 = (\r\n            company_data.get(\"electricity_kwh\", 0) * \r\n            company_data.get(\"grid_emission_factor\", 0.68)  # 中国电网系数\r\n        )\r\n        \r\n        # Scope 3: 价值链排放（简化版）\r\n        scope3 = {\r\n            \"上游采购\": company_data.get(\"purchased_goods\", 0) * 0.5,\r\n            \"运输配送\": company_data.get(\"transportation\", 0) * 0.1,\r\n            \"员工通勤\": company_data.get(\"employee_commute\", 0) * 0.02,\r\n            \"产品使用\": company_data.get(\"product_use\", 0) * 0.8,\r\n            \"报废处理\": company_data.get(\"end_of_life\", 0) * 0.05\r\n        }\r\n        \r\n        total_scope3 = sum(scope3.values())\r\n        \r\n        return {\r\n            \"scope1_tCO2e\": round(scope1, 2),\r\n            \"scope2_tCO2e\": round(scope2, 2),\r\n            \"scope3_tCO2e\": round(total_scope3, 2),\r\n            \"total_emissions\": round(scope1 + scope2 + total_scope3, 2),\r\n            \"intensity_metrics\": {\r\n                \"per_revenue\": round((scope1+scope2+total_scope3) / \r\n                                    max(company_data.get(\"revenue_yuan\", 1), 1) * 1e6, 2),  # tCO2e/百万营收\r\n                \"per_employee\": round((scope1+scope2+total_scope3) / \r\n                                      max(company_data.get(\"employees\", 1), 1), 2)  # tCO2e/人\r\n            },\r\n            \"scope_breakdown\": {\r\n                \"Scope 1\": round(scope1/(scope1+scope2+total_scope3+0.001)*100, 1),\r\n                \"Scope 2\": round(scope2/(scope1+scope2+total_scope3+0.001)*100, 1),\r\n                \"Scope 3\": round(total_scope3/(scope1+scope2+total_scope3+0.001)*100, 1)\r\n            }\r\n        }\r\n```\r\n\r\n**示例 1｜碳核算结果解读（先看结构，再看总量）**\r\n\r\n| 项目 | 数值 | 占比 | 解读 |\r\n|------|------|------|------|\r\n| Scope 1 直接排放 | 12,400 tCO2e | 12.1% | 主要来自燃料燃烧 |\r\n| Scope 2 间接排放（电力） | 21,800 tCO2e | 21.3% | 可用绿电替换下降 |\r\n| Scope 3 价值链排放 | 68,300 tCO2e | 66.6% | 占比最高，减排难度大 |\r\n| 合计 | 102,500 tCO2e | 100% | — |\r\n| 强度（tCO2e/百万营收） | 42.7 | — | 需与行业对标 |\r\n\r\n解读要点：Scope 3 占比超过六成是制造业常态，若报告只强调 Scope 1/2 的减排成绩，容易形成选择性披露；应说明 Scope 3 的核算边界与数据来源可靠度。\r\n\r\n**示例 2｜强度指标行业对标**\r\n\r\n| 行业 | 强度中位数（tCO2e/百万营收） | 标的A | 标的B | 判断 | 数据年份 | |\r\n|------|--------------------------|-------|-------|------|---|\r\n| 建材 | 180 | 165 | 210 | A优于中位数，B偏高 | 2025 |\r\n| 电子制造 | 45 | 42.7 | 38.5 | 均在合理区间 | 2025 |\r\n| 电力 | 320 | 290 | 355 | A优于中位数，B偏高 | 2025 |\r\n| 消费 | 18 | 12 | 9 | 均优于中位数 | 2025 |\r\n\r\n使用要点：强度指标必须限定在同一行业内部比较，跨行业直接比大小没有意义；对标时应注明数据年份与来源。\r\n\r\n**示例 3｜数据缺口处理（不要用0填补）**\r\n\r\n| 缺口情形 | 错误做法 | 正确做法 |\r\n|---------|---------|---------|\r\n| 无 Scope 3 数据 | 记为0 | 标注\"未披露\"，并给出行业估算区间 |\r\n| 仅有集团口径 | 直接按营收比例摊分 | 说明摊分假设，标注为估算值 |\r\n| 电网排放因子过期 | 沿用旧系数 | 使用最新公布系数并标注年份 |\r\n| 子公司未纳入合并 | 忽略 | 明示核算边界，说明未纳入部分 |\r\n\r\n\r\n**示例 4｜碳价敏感性对高碳标的估值的影响**\r\n\r\n| 碳价情景 | 碳价（元/吨） | 标的年排放（万吨） | 年碳成本增加（万元） | 占净利润比 | 估值影响判断 |\r\n|---------|------------|-----------------|-------------------|-----------|------------|\r\n| 基准 | 80 | 120 | 0（已内含） | — | 基准情形 |\r\n| 上行 | 150 | 120 | 8,400 | 12.4% | 显著侵蚀利润，需下调盈利预测 |\r\n| 下行 | 50 | 120 | −3,600 | −5.3% | 成本缓解，但需警惕配额收紧 |\r\n\r\n测算要点：碳成本增量 =（情景碳价 − 基准碳价）× 排放量，须使用标的自身排放量而非行业均值；占比超过净利润10%时应在估值中单列碳成本项，而不是笼统归入\"成本上升\"。配额free allocation（免费配额）比例须单独说明，否则会高估碳成本。\r\n\r\n**示例 5｜绿电替换对 Scope 2 的减排测算**\r\n\r\n| 项目 | 替换前 | 替换后 | 变化 |\r\n|------|-------|-------|------|\r\n| 外购电量（万kWh） | 3,200 | 3,200 | 不变 |\r\n| 其中绿电比例 | 0% | 60% | +60pct |\r\n| 电网排放因子 | 0.68 | 0.68（火电部分） | 不变 |\r\n| Scope 2 排放（tCO2e） | 21,760 | 8,704 | −13,056（−60%） |\r\n\r\n注意：绿电替换只影响 Scope 2，不改变 Scope 1 与 Scope 3；报告中不得把 Scope 2 的降幅表述为\"总排放下降60%\"，须说明其在总排放中的占比。\r\n\r\n### 3. Green Bond Analysis / 绿色债券分析\r\n\r\n```markdown\r\n## 绿色债券投资分析框架\r\n\r\n### 一、绿色债券认定\r\n| 标准 | 中国绿债标准 | 国际标准（GBP） | 核查要点 |\r\n|-----|------------|---------------|---------|\r\n| 募集资金用途 | ≥80%用于绿色项目 | ≥95%用于绿色项目 | 核对投向清单与项目目录 |\r\n| 项目评估 | 需第三方认证 | 需外部评审 | 核查认证机构资质与结论 |\r\n| 信息披露 | 年度+事件披露 | 发行时+续存期披露 | 是否按期披露环境效益 |\r\n| 募集资金管理 | 专户管理、专款专用 | 独立账户管理 | 核查资金流水与用途一致性 |\r\n| 存续期跟踪 | 需跟踪项目进展 | 需持续报告 | 环境效益指标是否可量化 |\r\n| 目录依据 | 依据绿色债券支持项目目录 | 依据GBP四原则 | 版本年份须标注 |\r\n\r\n### 二、绿色债券筛选矩阵\r\n- [ ] 是否获得绿色债券认证\r\n- [ ] 第三方认证机构资质\r\n- [ ] 募集资金用途透明度\r\n- [ ] 环境效益量化指标\r\n- [ ] 续存期管理机制\r\n\r\n### 三、环境效益量化\r\n```python\r\ndef calculate_green_benefits(bond_data: dict) -> dict:\r\n    \"\"\"计算绿色债券环境效益\"\"\"\r\n    green_proceeds = bond_data[\"total_amount\"] * bond_data[\"green_ratio\"]\r\n    \r\n    benefits = {\r\n        \"annual_co2_reduction\": green_proceeds / 10000 * bond_data[\"carbon_factor\"],  # 吨CO2/年\r\n        \"annual_energy_saving\": green_proceeds / 10000 * bond_data[\"energy_factor\"],  # 吨标煤/年\r\n        \"equivalent_forests\": green_proceeds / 10000 * bond_data[\"forest_factor\"]  # 相当于造林面积(公顷)\r\n    }\r\n    \r\n    return benefits\r\n```\r\n```\r\n\r\n**绿色债券筛选打分表（把清单变成可比较的分数）**\r\n\r\n| 维度 | 权重 | 评分要点 | 分值（1-5） |\r\n|------|------|---------|-----------|\r\n| 认证有效性 | 25% | 是否取得合规第三方认证 | 5 |\r\n| 募集资金投向 | 25% | 绿色项目占比与目录一致性 | 4 |\r\n| 环境效益可量化 | 20% | 是否有明确减排量测算 | 4 |\r\n| 信息披露质量 | 15% | 存续期披露是否及时完整 | 3 |\r\n| 资金管理规范性 | 15% | 专户管理与用途一致性 | 5 |\r\n| **加权得分** | 100% | — | **4.25** |\r\n\r\n判定口径：加权得分 ≥4.0 为优质绿债；3.0-4.0 为合格；<3.0 需评估是否存在\"漂绿\"风险。\r\n\r\n**示例｜环境效益测算的手算核对**\r\n\r\n- 输入：债券规模 10 亿元，绿色用途占比 100%，碳减排系数 0.42 吨CO2/万元。\r\n- 年减排量 = 100,000 万元 × 0.42 = **42,000 吨CO2/年**。\r\n- 折合造林 ≈ 42,000 / 每公顷年固碳 6 吨 ≈ **7,000 公顷**/年（折算系数须注明来源）。\r\n- 报告写法：\"据发行文件披露的测算方法，本期债券对应项目预计年减排CO₂约4.2万吨（折算参数来源：发行文件第X页），该数值为预测值，实际以存续期披露为准。\"\r\n\r\n\r\n**示例｜绿债打分的分歧处置（同一只债两种结论）**\r\n\r\n| 维度 | 分析师甲 | 分析师乙 | 分歧点 | 处置 |\r\n|------|---------|---------|--------|------|\r\n| 认证有效性 | 5 | 3 | 乙方认为认证机构不在认可名单内 | 核查机构资质后取低值 |\r\n| 募集资金投向 | 4 | 4 | 一致 | 取4 |\r\n| 环境效益可量化 | 4 | 2 | 乙方认为减排量无第三方复核 | 要求补充复核文件，未补充前取低值 |\r\n| 加权得分 | 4.25 | 3.25 | 差1.0分 | 结论由\"优质\"变为\"合格\" |\r\n\r\n打分要点：各维度分值应逐个给出依据，不得直接写总分。出现分歧时按\"就低不就高\"处理并说明原因，待补充材料后再复核上调；绿债认定结论改变时须同步更新产品命名与宣传口径的一致性自查。\r\n\r\n**示例｜存续期跟踪的年度对照表**\r\n\r\n| 指标 | 发行时预测 | 第1年实际 | 达成率 | 差异说明 |\r\n|------|-----------|----------|-------|---------|\r\n| 年减排CO₂（吨） | 42,000 | 31,500 | 75% | 项目投产进度晚于计划 |\r\n| 节能量（吨标煤） | 12,000 | 11,400 | 95% | 基本达预期 |\r\n| 募集资金已投放比例 | 100% | 68% | 68% | 部分项目尚未开工 |\r\n\r\n跟踪要点：达成率低于80%须要求发行人说明原因并披露整改计划；募集资金投放进度显著滞后时，应评估是否触发\"资金闲置\"相关的信息披露要求。\r\n\r\n### 4. ESG Portfolio Construction / ESG组合构建\r\n\r\n**三种主流构建方法对比**\r\n\r\n| 方法 | 做法 | 优点 | 局限 | 适用投资者 |\r\n|------|------|------|------|-----------|\r\n| 负面排除 | 剔除烟草、博彩、高碳等行业 | 规则清晰、易执行 | 可能牺牲收益、行业集中 | 有明确价值观约束的机构 |\r\n| ESG整合 | 把ESG评分并入选股模型 | 不显著偏离基准 | 依赖评级质量 | 多数公募与保险资金 |\r\n| 主题投资 | 聚焦低碳、清洁能源等主题 | 契合长期趋势、弹性大 | 波动大、主题可能过窄 | 风险偏好较高的资金 |\r\n| 影响力投资 | 以可量化的社会/环境效益为目标 | 效益可衡量 | 流动性较差 | 长期资金、公益属性资金 |\r\n\r\n**ESG组合构建检查表**\r\n\r\n| 检查项 | 阈值 | 说明 |\r\n|-------|------|------|\r\n| 组合ESG综合得分 | ≥行业基准或基准+5% | 相对基准的改善幅度须可量化 |\r\n| 高碳行业敞口 | ≤基准的80% | 避免名义ESG实则高碳 |\r\n| 单一ESG主题集中度 | ≤25% | 防止主题过度集中 |\r\n| 争议标的剔除 | 100%剔除重大争议标的 | 依据负面事件清单 |\r\n| ESG数据覆盖率 | ≥90% | 覆盖率不足须说明估算方法 |\r\n| 绿色收入占比 | ≥30%（绿色主题产品） | 与产品命名保持一致 |\r\n\r\n**示例｜ESG改善的两种口径**\r\n\r\n| 口径 | 定义 | 示例结果 | 使用时注意 |\r\n|------|------|---------|-----------|\r\n| 相对改善 | 组合得分高于基准的幅度 | 组合62分，基准55分，改善+7分 | 须说明基准选择 |\r\n| 绝对水平 | 组合的绝对得分档位 | 组合62分（BBB档） | 高分不等于低风险 |\r\n| 加权碳强度 | 组合碳强度相对基准变化 | 较基准低22% | 须说明核算边界 |\r\n\r\n\r\n**示例｜负面排除的边界设定（排得太宽会伤基准）**\r\n\r\n| 排除口径 | 排除后剩余标的数 | 相对基准的行业偏离 | 跟踪误差 | 判断 |\r\n|---------|----------------|------------------|---------|------|\r\n| 仅排除烟草、博彩 | 480/500 | 极小 | 0.4% | 可接受的窄口径 |\r\n| 排除全部化石能源 | 402/500 | 能源权重−8.2pct | 2.1% | 偏离显著，需说明 |\r\n| 排除营收>5%来自高碳 | 355/500 | 能源+材料合计−14.5pct | 3.8% | 偏离过大，不适合宽基产品 |\r\n\r\n设定要点：排除口径越宽，相对基准的偏离与跟踪误差越大。宽基产品宜采用窄口径并在报告中披露偏离；主题产品可采用宽口径但须在产品名称与投资范围中明示，避免\"名为宽基、实为排除\"的表述不一致。\r\n\r\n**示例｜ESG整合中的因子中性化处理**\r\n\r\n| 处理前 | 处理后 | 说明 |\r\n|-------|-------|------|\r\n| ESG高分组合行业偏向消费与金融 | 行业内标准化后选股 | 消除行业暴露差异 |\r\n| 市值偏向大盘 | 市值中性化 | 消除规模因子影响 |\r\n| 组合Beta 1.15 | Beta 0.98 | 与基准基本持平 |\r\n\r\n中性化要点：ESG得分与行业、市值存在天然相关性（大市值、消费金融行业ESG披露往往更好），不做中性化的\"ESG整合\"很可能只是行业与规模的隐性暴露。报告须说明是否做了中性化及所用方法。\r\n\r\n---\r\n\r\n## Quick Command Templates / 快速指令模板\r\n\r\n**跨评级对比：**\r\n```\r\n对[公司名称]做跨机构ESG评级对比：\r\n- 机构与评级：[MSCI X / Sustainalytics X / 商道融绿 X / 中证 X]\r\n- 输出：标准化得分、与均值偏离、分歧归因与结论\r\n```\r\n\r\n**碳核算：**\r\n```\r\n按 Scope 1/2/3 为[公司名称]做碳核算：\r\n- 输入：燃料消耗/外购电量/采购金额/运输量\r\n- 输出：分项排放量、强度指标、结构占比与数据缺口说明\r\n```\r\n\r\n**绿色债券筛选：**\r\n```\r\n按认证有效性、募集资金投向、环境效益、信息披露、资金管理五个维度，\r\n对[债券名称]做绿债打分并给出是否认定及漂绿风险提示。\r\n```\r\n\r\n**ESG组合构建：**\r\n```\r\n用[负面排除/ESG整合/主题投资]方法构建组合，\r\n输出组合ESG得分、高碳敞口、主题集中度与数据覆盖率检查结果。\r\n```\r\n\r\n---\r\n\r\n## Changelog / 版本变更\r\n\r\n| 版本 | 日期 | 变更摘要 |\r\n|------|------|---------|\r\n| 3.0.3 | 2026-10-08 | 新增数据最小化声明与执行边界章节；收窄触发词并补充中英文非触发清单（SQP-1/SQP-3）；监管动态更新至2026-10-08并新增可持续披露、碳市场两条与复核频率列；新增示例：评级分歧归因落地写法、综合评分权重方案、碳价敏感性测算、绿电替换Scope 2测算、绿债打分分歧处置、存续期年度对照、负面排除边界设定、ESG整合因子中性化 |\r\n| 3.0.2 | 2026-09-12 | 新增跨评级分歧表与碳核算数据缺口处理 |\r\n\r\n---\r\n\r\n\r\n## Disclaimer\r\n\r\nThis skill provides ESG analysis tools for educational purposes. ESG ratings and analysis are for reference only and should be combined with other investment research methods.\n\nFile v3.0.3:_meta.json\n\n{\n  \"ownerId\": \"kn74e704j3ygjcygnpf02rdvd185js13\",\n  \"slug\": \"security-esg-investing\",\n  \"version\": \"3.0.3\",\n  \"publishedAt\": 1791436202910\n}\n\nFile v3.0.3:skill-card.md\n\n## Description:\n\nHelps ESG analysts compare ratings, estimate Scope 1–3 emissions, screen green bonds, and assess sustainable portfolios for investment decisions in the China market.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[gechengling](https://clawhub.ai/user/gechengling)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nESG analysts and sustainable investors use this skill to compare issuer ratings, evaluate emissions and green bonds, and review portfolio sustainability when assessing investable assets. Outputs are educational inputs to research, not independently verified investment or regulatory advice.\n\n### Deployment Geography for Use:\n\nChina\n\n## Known Risks and Mitigations:\n\nRisk: Stale regulatory claims, ESG ratings, or emissions factors could distort investment decisions or external reports.\n\nMitigation: Verify current rules, source dates, ratings, emissions factors, and calculation assumptions before relying on results or publishing them.\n\nRisk: Sensitive company or personal information could be exposed if supplied for analysis.\n\nMitigation: Use public data and de-identified portfolio inputs; omit confidential records and personal information.\n\n## Reference(s):\n\n- [Security Esg Investing on ClawHub](https://clawhub.ai/gechengling/skills/security-esg-investing)\n\n## Skill Output:\n\n**Output Type(s):** [Analysis, Guidance, Code]\n\n**Output Format:** [Markdown with tables and illustrative Python code]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Example calculations and screening checklists require independent data and source verification.]\n\n## Skill Version(s):\n\n3.0.3 (source: frontmatter, release evidence)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.\n\nArchive v3.0.2: 3 files, 9776 bytes\n\nFiles: skill-card.md (2255b), SKILL.md (20381b), _meta.json (141b)\n\nFile v3.0.2:SKILL.md\n\n---\r\nname: ESG Investment Analysis Assistant\r\nslug: security-esg-investing\r\ndescription: AI-powered ESG investing analysis assistant — covers ESG rating analysis, green finance screening, carbon footprint assessment, and sustainable investment portfolio construction. Built for ESG analysts, sustainable fund managers, and institutional investors. Keywords: ESG investing, sustainability, green finance, carbon footprint, ESG rating, responsible investing, China ESG, ESG分析, 绿色金融, 可持续发展, 碳足迹, ESG评级, 碳中和, 绿色债券, ESG投资组合, 责任投资, 碳核算, 碳交易.\r\nversion: \"3.0.2\"\r\n---\r\n\r\n# ESG Investment Analysis Assistant / ESG投资分析助手\r\n\r\n> **English:** AI-powered ESG investing analysis assistant — covers ESG rating comparison, green finance products, carbon accounting, and sustainable portfolio construction. Built for ESG analysts and sustainable investors.\r\n>\r\n> **中文:** ESG投资分析助手——覆盖ESG评级对比、绿色金融产品筛选、碳核算、可持续组合构建。适用：ESG分析师、可持续基金经理、机构投资者。\r\n\r\n---\r\n\r\n\r\n### 证券监管最新动态 [2026-09-12更新]\r\n\r\n| 动态类型 | 内容摘要 | 影响范围 | ESG侧应对动作 | 责任岗 | 优先级 |\r\n|---------|---------|---------|-------------|-------|-------|\r\n| 证券监管 | 2026年Q1：ESG信息披露要求扩大至非上市企业 | ESG投资分析框架需更新最新信披要求和绿色金融政策 | 供应链ESG数据采集范围同步扩大 | 研究 | 高 |\r\n| 证券监管 | 绿色金融信贷导向政策升级，ESG投资环境改善 | ESG投资分析框架需更新最新信披要求和绿色金融政策 | 绿色资产识别标准与信贷口径对齐 | 研究 | 中 |\r\n| 证券监管 | 证监会加强ESG相关信披监管，ESG评级标准趋严 | ESG投资分析框架需更新最新信披要求和绿色金融政策 | 评级来源与取数日期须在报告中标注 | 合规 | 高 |\r\n| 可持续披露 | 可持续披露规则推进，披露范围与颗粒度提升 | ESG评级输入数据、组合披露 | 建立披露数据映射表，统一口径 | 研究 | 高 |\r\n| 反漂绿 | 绿色宣传与绿色产品命名合规要求趋严 | 绿色基金命名、宣传物料 | 产品命名与投资范围一致性自查 | 合规 | 高 |\r\n| 碳市场 | 碳市场覆盖行业范围与交易规则持续完善 | 碳成本测算、高碳行业敞口 | 碳价情景纳入估值敏感性 | 研究 | 中 |\r\n| 绿色债券 | 绿色债券募集资金用途与存续期披露要求细化 | 绿债筛选与投后跟踪 | 存续期环境效益跟踪清单化管理 | 研究 | 中 |\r\n| 数据合规 | ESG数据来源与第三方数据使用需合规授权 | 外部评级与数据库采购 | 数据来源授权凭证归档，标注使用范围 | 合规 | 中 |\r\n\r\n> **数据截止**: 2026-09-12 | 来源：证监会、生态环境部门公开规则、交易所公开信息\r\n> **声明**: 以上动态供参考，具体以官方最新发布为准\r\n\r\n**动态解读示例（四类高频场景）**\r\n\r\n- **场景A｜反漂绿自查**：某产品命名为\"绿色低碳\"但持仓含高碳行业标的 → 命中\"命名与投资范围一致性\"问题 → 要么调整持仓以匹配命名，要么修改产品名称与宣传口径，并留存自查记录。\r\n- **场景B｜披露口径映射**：评级输入中\"碳排放\"既有总量又有强度，混用于同一模型 → 命中\"口径统一\"要求 → 建立披露数据映射表，明确每项指标的来源、单位与报告期。\r\n- **场景C｜碳价情景敏感性**：估值模型未考虑碳成本 → 命中\"碳成本纳入测算\"要求 → 在敏感性分析中增加碳价上下行情景对高碳标的利润率与估值的影响。\r\n- **场景D｜数据授权**：ESG评级数据采购后用于对外报告但无授权范围说明 → 命中\"数据来源合规\"要求 → 归档授权凭证并注明可使用的场景，超范围使用需另行申请。\r\n\r\n## Industry Pain Points / 行业痛点\r\n\r\n| Pain Point / 痛点 | Impact / 影响 | Solution / 本Skill解决方案 | 量化基线指标 / Baseline |\r\n|------------------|-------------|------------------------|----------------------|\r\n| **ESG数据分散** | 评级机构超过10家，标准不统一 | 跨评级对比框架+综合评分 | 覆盖机构 ≥4家，分歧度可量化 |\r\n| **\"漂绿\"风险** | 虚假绿色宣传导致合规风险 | 实质性分析+数据核实 | 绿色收入占比可核查率 100% |\r\n| **碳核算复杂** | Scope 1/2/3核算专业门槛高 | 分级碳核算模板+简化方法 | Scope 1/2 数据覆盖率 100% |\r\n| **政策变化快** | 碳市场/ESG披露要求频繁更新 | 实时政策跟踪+合规提醒 | 政策更新响应 ≤5个工作日 |\r\n| **评级分歧** | 同一公司评级差异大，难以决策 | 分歧归因表+一致性检验 | 分歧>2档时须专项说明 |\r\n| **数据不可比** | 不同来源口径不一致 | 口径映射表 | 指标口径一致率 100% |\r\n| **投后跟踪缺失** | 绿债与绿色项目投后无跟踪 | 存续期跟踪清单 | 环境效益跟踪覆盖率 100% |\r\n| **负面事件滞后** | 重大ESG事件未及时反映 | 事件监控与复核机制 | 重大事件响应 ≤3个工作日 |\r\n\r\n---\r\n\r\n## Trigger Keywords / 触发关键词\r\n\r\n**English Triggers:** ESG investing, sustainability, green finance, carbon footprint, ESG rating, responsible investing, ESG analysis, carbon trading, sustainable portfolio, China ESG\r\n\r\n**中文触发词（优先）：** ESG投资 / 可持续发展 / 绿色金融 / 碳足迹 / ESG评级 / 责任投资 / ESG分析 / 碳交易 / 可持续组合 / 碳中和 / 碳达峰 / 绿色债券 / ESG披露 / MSCI ESG / 责任投资 / 影响力投资\r\n\r\n---\r\n\r\n## Core Capabilities / 核心能力\r\n\r\n### 1. ESG Rating Analysis / ESG评级分析\r\n\r\n```python\r\nclass ESGAnalyzer:\r\n    \"\"\"ESG评级分析\"\"\"\r\n    \r\n    RATING_PROVIDERS = {\r\n        \"MSCI\": {\"scale\": \"CCC-AAA\", \"weight\": {\"E\": 0.25, \"S\": 0.25, \"G\": 0.50}},\r\n        \"Sustainalytics\": {\"scale\": \"0-100\", \"weight\": {\"E\": 0.33, \"S\": 0.33, \"G\": 0.33}},\r\n        \"商道融绿\": {\"scale\": \"D-A+\", \"weight\": {\"E\": 0.30, \"S\": 0.30, \"G\": 0.40}},\r\n        \"中证ESG\": {\"scale\": \"C-AAA\", \"weight\": {\"E\": 0.20, \"S\": 0.20, \"G\": 0.60}},\r\n        \"华证ESG\": {\"scale\": \"C-AAA\", \"weight\": {\"E\": 0.25, \"S\": 0.30, \"G\": 0.45}},\r\n        \"Wind ESG\": {\"scale\": \"1-10\", \"weight\": {\"E\": 0.30, \"S\": 0.30, \"G\": 0.40}}\r\n    }\r\n    \r\n    def normalize_rating(self, provider: str, raw_score: float) -> float:\r\n        \"\"\"标准化评分到0-100\"\"\"\r\n        if provider == \"MSCI\":\r\n            scale = {\"CCC\": 10, \"B\": 20, \"BB\": 35, \"BBB\": 50, \"A\": 65, \"AA\": 80, \"AAA\": 95}\r\n            return scale.get(raw_score, 50)\r\n        elif provider == \"Sustainalytics\":\r\n            return 100 - raw_score  # 反转，风险分数→ESG分数\r\n        elif provider == \"商道融绿\":\r\n            scale = {\"D\": 20, \"C\": 40, \"B\": 60, \"B+\": 70, \"A\": 85, \"A+\": 95}\r\n            return scale.get(raw_score, 50)\r\n        elif provider == \"华证ESG\":\r\n            scale = {\"C\": 20, \"CC\": 30, \"CCC\": 40, \"B\": 50, \"BB\": 60, \"BBB\": 70,\r\n                     \"A\": 80, \"AA\": 90, \"AAA\": 95}\r\n            return scale.get(raw_score, 50)\r\n        elif provider == \"Wind ESG\":\r\n            # Wind 为 1-10 分制，线性映射到 0-100\r\n            return float(raw_score) * 10\r\n        return raw_score\r\n    \r\n    def comprehensive_analysis(self, company: str, \r\n                               ratings: dict) -> dict:\r\n        \"\"\"综合ESG分析\"\"\"\r\n        normalized = {\r\n            provider: self.normalize_rating(provider, score)\r\n            for provider, score in ratings.items()\r\n        }\r\n        \r\n        # 加权综合评分\r\n        weights = [0.30, 0.25, 0.25, 0.20]  # 权重分配\r\n        providers = list(normalized.keys())\r\n        comprehensive = sum(\r\n            normalized[p] * w \r\n            for p, w in zip(providers, weights)\r\n        )\r\n        \r\n        return {\r\n            \"comprehensive_score\": round(comprehensive, 1),\r\n            \"rating_level\": self._score_to_level(comprehensive),\r\n            \"individual_ratings\": normalized,\r\n            \"key_strengths\": self._identify_strengths(normalized),\r\n            \"key_concerns\": self._identify_concerns(normalized),\r\n            \"peer_comparison\": self._compare_to_peer(company, comprehensive)\r\n        }\r\n    \r\n    def _score_to_level(self, score: float) -> str:\r\n        levels = {\r\n            (90, 100): \"AAA - 卓越\",\r\n            (80, 90): \"AA - 优秀\",\r\n            (70, 80): \"A - 良好\",\r\n            (60, 70): \"BBB - 平均偏上\",\r\n            (50, 60): \"BB - 平均\",\r\n            (40, 50): \"B - 低于平均\",\r\n            (0, 40): \"CCC/B - 落后\"\r\n        }\r\n        for (low, high), level in levels.items():\r\n            if low <= score <= high:\r\n                return level\r\n        return \"未知\"\r\n```\r\n\r\n**跨评级机构分歧表（分歧本身也是信息）**\r\n\r\n| 评级机构 | 原始评级 | 标准化得分 | 与均值偏离 | 可能的解释 |\r\n|---------|---------|-----------|-----------|-----------|\r\n| MSCI | BB | 35.0 | −18.4 | 对治理与信息披露要求较严 |\r\n| Sustainalytics | 38（风险分） | 62.0 | +8.6 | 偏重风险暴露口径 |\r\n| 商道融绿 | B+ | 70.0 | +16.6 | 侧重国内披露实践 |\r\n| 中证ESG | BBB | 70.0 | +16.6 | 治理权重较高 |\r\n| 综合得分 | — | **53.4（BB-平均）** | — | 分歧较大，需专项说明 |\r\n\r\n**示例 1｜评级分歧的两种处理方式**\r\n\r\n| 分歧程度 | 判定 | 处理方式 | 报告写法 |\r\n|---------|------|---------|---------|\r\n| ≤1档 | 一致 | 直接采用综合得分 | \"各机构评级基本一致\" |\r\n| 2档 | 中度分歧 | 取中位数并说明 | \"评级存在差异，主要源于治理维度权重不同\" |\r\n| >2档 | 高度分歧 | 逐一归因，不强行合并 | \"评级分歧显著，建议以原始披露数据为准做独立判断\" |\r\n\r\n**示例 2｜标准化映射的注意事项**\r\n\r\n| 问题 | 原因 | 正确做法 |\r\n|------|------|---------|\r\n| Sustainalytics 分数越高越差 | 其分制为\"风险分\" | 用 100 减后再入表，并注明已反转 |\r\n| MSCI 无 BBB- 等档位 | 档位为离散七级 | 用映射表而非线性插值 |\r\n| 评级更新不同步 | 各机构更新频率不同 | 每项标注评级发布日期，取最近一期 |\r\n| 分母口径不同 | 有的按市值、有的按营收 | 强度类指标须统一分母并标注 |\r\n\r\n### 2. Carbon Footprint Analysis / 碳足迹分析\r\n\r\n```python\r\nclass CarbonAnalyzer:\r\n    \"\"\"碳足迹核算\"\"\"\r\n    \r\n    def calculate_carbon_footprint(self, company_data: dict) -> dict:\r\n        \"\"\"\r\n        计算碳足迹（Scope 1, 2, 3）\r\n        \"\"\"\r\n        # Scope 1: 直接排放\r\n        scope1 = (\r\n            company_data.get(\"fuel_combustion\", 0) * 2.02 +  # CO2系数\r\n            company_data.get(\"vehicle_fleet\", 0) * 2.32 +\r\n            company_data.get(\"fugitive_emissions\", 0) * 25  # CH4当量\r\n        )\r\n        \r\n        # Scope 2: 间接排放（电力）\r\n        scope2 = (\r\n            company_data.get(\"electricity_kwh\", 0) * \r\n            company_data.get(\"grid_emission_factor\", 0.68)  # 中国电网系数\r\n        )\r\n        \r\n        # Scope 3: 价值链排放（简化版）\r\n        scope3 = {\r\n            \"上游采购\": company_data.get(\"purchased_goods\", 0) * 0.5,\r\n            \"运输配送\": company_data.get(\"transportation\", 0) * 0.1,\r\n            \"员工通勤\": company_data.get(\"employee_commute\", 0) * 0.02,\r\n            \"产品使用\": company_data.get(\"product_use\", 0) * 0.8,\r\n            \"报废处理\": company_data.get(\"end_of_life\", 0) * 0.05\r\n        }\r\n        \r\n        total_scope3 = sum(scope3.values())\r\n        \r\n        return {\r\n            \"scope1_tCO2e\": round(scope1, 2),\r\n            \"scope2_tCO2e\": round(scope2, 2),\r\n            \"scope3_tCO2e\": round(total_scope3, 2),\r\n            \"total_emissions\": round(scope1 + scope2 + total_scope3, 2),\r\n            \"intensity_metrics\": {\r\n                \"per_revenue\": round((scope1+scope2+total_scope3) / \r\n                                    max(company_data.get(\"revenue_yuan\", 1), 1) * 1e6, 2),  # tCO2e/百万营收\r\n                \"per_employee\": round((scope1+scope2+total_scope3) / \r\n                                      max(company_data.get(\"employees\", 1), 1), 2)  # tCO2e/人\r\n            },\r\n            \"scope_breakdown\": {\r\n                \"Scope 1\": round(scope1/(scope1+scope2+total_scope3+0.001)*100, 1),\r\n                \"Scope 2\": round(scope2/(scope1+scope2+total_scope3+0.001)*100, 1),\r\n                \"Scope 3\": round(total_scope3/(scope1+scope2+total_scope3+0.001)*100, 1)\r\n            }\r\n        }\r\n```\r\n\r\n**示例 1｜碳核算结果解读（先看结构，再看总量）**\r\n\r\n| 项目 | 数值 | 占比 | 解读 |\r\n|------|------|------|------|\r\n| Scope 1 直接排放 | 12,400 tCO2e | 12.1% | 主要来自燃料燃烧 |\r\n| Scope 2 间接排放（电力） | 21,800 tCO2e | 21.3% | 可用绿电替换下降 |\r\n| Scope 3 价值链排放 | 68,300 tCO2e | 66.6% | 占比最高，减排难度大 |\r\n| 合计 | 102,500 tCO2e | 100% | — |\r\n| 强度（tCO2e/百万营收） | 42.7 | — | 需与行业对标 |\r\n\r\n解读要点：Scope 3 占比超过六成是制造业常态，若报告只强调 Scope 1/2 的减排成绩，容易形成选择性披露；应说明 Scope 3 的核算边界与数据来源可靠度。\r\n\r\n**示例 2｜强度指标行业对标**\r\n\r\n| 行业 | 强度中位数（tCO2e/百万营收） | 标的A | 标的B | 判断 |\r\n|------|--------------------------|-------|-------|------|\r\n| 建材 | 180 | 165 | 210 | A优于中位数，B偏高 |\r\n| 电子制造 | 45 | 42.7 | 38.5 | 均在合理区间 |\r\n| 电力 | 320 | 290 | 355 | A优于中位数，B偏高 |\r\n| 消费 | 18 | 12 | 9 | 均优于中位数 |\r\n\r\n使用要点：强度指标必须限定在同一行业内部比较，跨行业直接比大小没有意义；对标时应注明数据年份与来源。\r\n\r\n**示例 3｜数据缺口处理（不要用0填补）**\r\n\r\n| 缺口情形 | 错误做法 | 正确做法 |\r\n|---------|---------|---------|\r\n| 无 Scope 3 数据 | 记为0 | 标注\"未披露\"，并给出行业估算区间 |\r\n| 仅有集团口径 | 直接按营收比例摊分 | 说明摊分假设，标注为估算值 |\r\n| 电网排放因子过期 | 沿用旧系数 | 使用最新公布系数并标注年份 |\r\n| 子公司未纳入合并 | 忽略 | 明示核算边界，说明未纳入部分 |\r\n\r\n### 3. Green Bond Analysis / 绿色债券分析\r\n\r\n```markdown\r\n## 绿色债券投资分析框架\r\n\r\n### 一、绿色债券认定\r\n| 标准 | 中国绿债标准 | 国际标准（GBP） | 核查要点 |\r\n|-----|------------|---------------|---------|\r\n| 募集资金用途 | ≥80%用于绿色项目 | ≥95%用于绿色项目 | 核对投向清单与项目目录 |\r\n| 项目评估 | 需第三方认证 | 需外部评审 | 核查认证机构资质与结论 |\r\n| 信息披露 | 年度+事件披露 | 发行时+续存期披露 | 是否按期披露环境效益 |\r\n| 募集资金管理 | 专户管理、专款专用 | 独立账户管理 | 核查资金流水与用途一致性 |\r\n| 存续期跟踪 | 需跟踪项目进展 | 需持续报告 | 环境效益指标是否可量化 |\r\n| 目录依据 | 依据绿色债券支持项目目录 | 依据GBP四原则 | 版本年份须标注 |\r\n\r\n### 二、绿色债券筛选矩阵\r\n- [ ] 是否获得绿色债券认证\r\n- [ ] 第三方认证机构资质\r\n- [ ] 募集资金用途透明度\r\n- [ ] 环境效益量化指标\r\n- [ ] 续存期管理机制\r\n\r\n### 三、环境效益量化\r\n```python\r\ndef calculate_green_benefits(bond_data: dict) -> dict:\r\n    \"\"\"计算绿色债券环境效益\"\"\"\r\n    green_proceeds = bond_data[\"total_amount\"] * bond_data[\"green_ratio\"]\r\n    \r\n    benefits = {\r\n        \"annual_co2_reduction\": green_proceeds / 10000 * bond_data[\"carbon_factor\"],  # 吨CO2/年\r\n        \"annual_energy_saving\": green_proceeds / 10000 * bond_data[\"energy_factor\"],  # 吨标煤/年\r\n        \"equivalent_forests\": green_proceeds / 10000 * bond_data[\"forest_factor\"]  # 相当于造林面积(公顷)\r\n    }\r\n    \r\n    return benefits\r\n```\r\n```\r\n\r\n**绿色债券筛选打分表（把清单变成可比较的分数）**\r\n\r\n| 维度 | 权重 | 评分要点 | 分值（1-5） |\r\n|------|------|---------|-----------|\r\n| 认证有效性 | 25% | 是否取得合规第三方认证 | 5 |\r\n| 募集资金投向 | 25% | 绿色项目占比与目录一致性 | 4 |\r\n| 环境效益可量化 | 20% | 是否有明确减排量测算 | 4 |\r\n| 信息披露质量 | 15% | 存续期披露是否及时完整 | 3 |\r\n| 资金管理规范性 | 15% | 专户管理与用途一致性 | 5 |\r\n| **加权得分** | 100% | — | **4.25** |\r\n\r\n判定口径：加权得分 ≥4.0 为优质绿债；3.0-4.0 为合格；<3.0 需评估是否存在\"漂绿\"风险。\r\n\r\n**示例｜环境效益测算的手算核对**\r\n\r\n- 输入：债券规模 10 亿元，绿色用途占比 100%，碳减排系数 0.42 吨CO2/万元。\r\n- 年减排量 = 100,000 万元 × 0.42 = **42,000 吨CO2/年**。\r\n- 折合造林 ≈ 42,000 / 每公顷年固碳 6 吨 ≈ **7,000 公顷**/年（折算系数须注明来源）。\r\n- 报告写法：\"据发行文件披露的测算方法，本期债券对应项目预计年减排CO₂约4.2万吨（折算参数来源：发行文件第X页），该数值为预测值，实际以存续期披露为准。\"\r\n\r\n### 4. ESG Portfolio Construction / ESG组合构建\r\n\r\n**三种主流构建方法对比**\r\n\r\n| 方法 | 做法 | 优点 | 局限 | 适用投资者 |\r\n|------|------|------|------|-----------|\r\n| 负面排除 | 剔除烟草、博彩、高碳等行业 | 规则清晰、易执行 | 可能牺牲收益、行业集中 | 有明确价值观约束的机构 |\r\n| ESG整合 | 把ESG评分并入选股模型 | 不显著偏离基准 | 依赖评级质量 | 多数公募与保险资金 |\r\n| 主题投资 | 聚焦低碳、清洁能源等主题 | 契合长期趋势、弹性大 | 波动大、主题可能过窄 | 风险偏好较高的资金 |\r\n| 影响力投资 | 以可量化的社会/环境效益为目标 | 效益可衡量 | 流动性较差 | 长期资金、公益属性资金 |\r\n\r\n**ESG组合构建检查表**\r\n\r\n| 检查项 | 阈值 | 说明 |\r\n|-------|------|------|\r\n| 组合ESG综合得分 | ≥行业基准或基准+5% | 相对基准的改善幅度须可量化 |\r\n| 高碳行业敞口 | ≤基准的80% | 避免名义ESG实则高碳 |\r\n| 单一ESG主题集中度 | ≤25% | 防止主题过度集中 |\r\n| 争议标的剔除 | 100%剔除重大争议标的 | 依据负面事件清单 |\r\n| ESG数据覆盖率 | ≥90% | 覆盖率不足须说明估算方法 |\r\n| 绿色收入占比 | ≥30%（绿色主题产品） | 与产品命名保持一致 |\r\n\r\n**示例｜ESG改善的两种口径**\r\n\r\n| 口径 | 定义 | 示例结果 | 使用时注意 |\r\n|------|------|---------|-----------|\r\n| 相对改善 | 组合得分高于基准的幅度 | 组合62分，基准55分，改善+7分 | 须说明基准选择 |\r\n| 绝对水平 | 组合的绝对得分档位 | 组合62分（BBB档） | 高分不等于低风险 |\r\n| 加权碳强度 | 组合碳强度相对基准变化 | 较基准低22% | 须说明核算边界 |\r\n\r\n---\r\n\r\n## Quick Command Templates / 快速指令模板\r\n\r\n**跨评级对比：**\r\n```\r\n对[公司名称]做跨机构ESG评级对比：\r\n- 机构与评级：[MSCI X / Sustainalytics X / 商道融绿 X / 中证 X]\r\n- 输出：标准化得分、与均值偏离、分歧归因与结论\r\n```\r\n\r\n**碳核算：**\r\n```\r\n按 Scope 1/2/3 为[公司名称]做碳核算：\r\n- 输入：燃料消耗/外购电量/采购金额/运输量\r\n- 输出：分项排放量、强度指标、结构占比与数据缺口说明\r\n```\r\n\r\n**绿色债券筛选：**\r\n```\r\n按认证有效性、募集资金投向、环境效益、信息披露、资金管理五个维度，\r\n对[债券名称]做绿债打分并给出是否认定及漂绿风险提示。\r\n```\r\n\r\n**ESG组合构建：**\r\n```\r\n用[负面排除/ESG整合/主题投资]方法构建组合，\r\n输出组合ESG得分、高碳敞口、主题集中度与数据覆盖率检查结果。\r\n```\r\n\r\n---\r\n\r\n## Disclaimer\r\n\r\nThis skill provides ESG analysis tools for educational purposes. ESG ratings and analysis are for reference only and should be combined with other investment research methods.\n\nFile v3.0.2:_meta.json\n\n{\n  \"ownerId\": \"kn74e704j3ygjcygnpf02rdvd185js13\",\n  \"slug\": \"security-esg-investing\",\n  \"version\": \"3.0.2\",\n  \"publishedAt\": 1789197773945\n}\n\nFile v3.0.2:skill-card.md\n\n## Description:\n\nProvides ESG rating comparison, green finance screening, carbon footprint assessment, and sustainable portfolio construction guidance for ESG analysts, sustainable fund managers, and institutional investors.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[gechengling](https://clawhub.ai/user/gechengling)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nExternal ESG analysts, sustainable investment teams, and institutional investors use this skill to structure ESG rating comparisons, carbon-accounting checks, green bond screening, and sustainable portfolio analysis. Its outputs are reference material to combine with independent investment research.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: ESG, sustainability, and green-finance outputs may be mistaken for current professional investment advice.\n\nMitigation: Treat outputs as reference material and verify regulations, rating data, carbon factors, and financial conclusions independently before use.\n\nRisk: The skill can frame sustainability discussions as investment analysis, which may affect decisions if data or assumptions are stale.\n\nMitigation: Check source dates, official disclosures, rating-provider updates, and applicable financial or regulatory requirements before relying on the analysis.\n\n## Reference(s):\n\n- [ClawHub skill page](https://clawhub.ai/gechengling/skills/security-esg-investing)\n- [ClawHub publisher profile](https://clawhub.ai/user/gechengling)\n\n## Skill Output:\n\n**Output Type(s):** [Text, Markdown, Code, Guidance]\n\n**Output Format:** [Markdown with structured tables, checklists, and code snippets]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Reference-only ESG and investment analysis; users should verify current regulations, rating data, carbon factors, and financial conclusions independently.]\n\n## Skill Version(s):\n\n3.0.2 (source: SKILL.md frontmatter and server release metadata)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.\n\nArchive v3.0.1: 3 files, 5184 bytes\n\nFiles: skill-card.md (2178b), SKILL.md (9302b), _meta.json (141b)\n\nFile v3.0.1:SKILL.md\n\n---\r\nname: ESG Investment Analysis Assistant\r\nslug: security-esg-investing\r\ndescription: AI-powered ESG investing analysis assistant — covers ESG rating analysis, green finance screening, carbon footprint assessment, and sustainable investment portfolio construction. Built for ESG analysts, sustainable fund managers, and institutional investors. Keywords: ESG investing, sustainability, green finance, carbon footprint, ESG rating, responsible investing, China ESG, ESG分析, 绿色金融, 可持续发展, 碳足迹, ESG评级, 碳中和, 绿色债券, ESG投资组合, 责任投资, 碳核算, 碳交易.\r\nversion: \"3.0.1\"\r\n---\r\n\r\n# ESG Investment Analysis Assistant / ESG投资分析助手\r\n\r\n> **English:** AI-powered ESG investing analysis assistant — covers ESG rating comparison, green finance products, carbon accounting, and sustainable portfolio construction. Built for ESG analysts and sustainable investors.\r\n>\r\n> **中文:** ESG投资分析助手——覆盖ESG评级对比、绿色金融产品筛选、碳核算、可持续组合构建。适用：ESG分析师、可持续基金经理、机构投资者。\r\n\r\n---\r\n\r\n\r\n### 证券监管最新动态 [2026-05-25更新]\r\n\r\n| 动态类型 | 内容摘要 | 影响范围 |\r\n|---------|---------|---------|\r\n| 证券监管 | 2026年Q1：ESG信息披露要求扩大至非上市企业 | ESG投资分析框架需更新最新信披要求和绿色金融政策 |\r\n| 证券监管 | 绿色金融信贷导向政策升级，ESG投资环境改善 | ESG投资分析框架需更新最新信披要求和绿色金融政策 |\r\n| 证券监管 | 证监会加强ESG相关信披监管，ESG评级标准趋严 | ESG投资分析框架需更新最新信披要求和绿色金融政策 |\r\n\r\n> **数据截止**: 2026-05-25 | 来源：证监会、NFRA、中证协、安永Q1分析\r\n> **声明**: 以上动态供参考，具体以官方最新发布为准\r\n\r\n## Industry Pain Points / 行业痛点\r\n\r\n| Pain Point / 痛点 | Impact / 影响 | Solution / 本Skill解决方案 |\r\n|------------------|-------------|------------------------|\r\n| **ESG数据分散** | 评级机构超过10家，标准不统一 | 跨评级对比框架+综合评分 |\r\n| **\"漂绿\"风险** | 虚假绿色宣传导致合规风险 | 实质性分析+数据核实 |\r\n| **碳核算复杂** | Scope 1/2/3核算专业门槛高 | 分级碳核算模板+简化方法 |\r\n| **政策变化快** | 碳市场/ESG披露要求频繁更新 | 实时政策跟踪+合规提醒 |\r\n\r\n---\r\n\r\n## Trigger Keywords / 触发关键词\r\n\r\n**English Triggers:** ESG investing, sustainability, green finance, carbon footprint, ESG rating, responsible investing, ESG analysis, carbon trading, sustainable portfolio, China ESG\r\n\r\n**中文触发词（优先）：** ESG投资 / 可持续发展 / 绿色金融 / 碳足迹 / ESG评级 / 责任投资 / ESG分析 / 碳交易 / 可持续组合 / 碳中和 / 碳达峰 / 绿色债券 / ESG披露 / MSCI ESG / 责任投资 / 影响力投资\r\n\r\n---\r\n\r\n## Core Capabilities / 核心能力\r\n\r\n### 1. ESG Rating Analysis / ESG评级分析\r\n\r\n```python\r\nclass ESGAnalyzer:\r\n    \"\"\"ESG评级分析\"\"\"\r\n    \r\n    RATING_PROVIDERS = {\r\n        \"MSCI\": {\"scale\": \"CCC-AAA\", \"weight\": {\"E\": 0.25, \"S\": 0.25, \"G\": 0.50}},\r\n        \"Sustainalytics\": {\"scale\": \"0-100\", \"weight\": {\"E\": 0.33, \"S\": 0.33, \"G\": 0.33}},\r\n        \"商道融绿\": {\"scale\": \"D-A+\", \"weight\": {\"E\": 0.30, \"S\": 0.30, \"G\": 0.40}},\r\n        \"中证ESG\": {\"scale\": \"C-AAA\", \"weight\": {\"E\": 0.20, \"S\": 0.20, \"G\": 0.60}}\r\n    }\r\n    \r\n    def normalize_rating(self, provider: str, raw_score: float) -> float:\r\n        \"\"\"标准化评分到0-100\"\"\"\r\n        if provider == \"MSCI\":\r\n            scale = {\"CCC\": 10, \"B\": 20, \"BB\": 35, \"BBB\": 50, \"A\": 65, \"AA\": 80, \"AAA\": 95}\r\n            return scale.get(raw_score, 50)\r\n        elif provider == \"Sustainalytics\":\r\n            return 100 - raw_score  # 反转，风险分数→ESG分数\r\n        elif provider == \"商道融绿\":\r\n            scale = {\"D\": 20, \"C\": 40, \"B\": 60, \"B+\": 70, \"A\": 85, \"A+\": 95}\r\n            return scale.get(raw_score, 50)\r\n        return raw_score\r\n    \r\n    def comprehensive_analysis(self, company: str, \r\n                               ratings: dict) -> dict:\r\n        \"\"\"综合ESG分析\"\"\"\r\n        normalized = {\r\n            provider: self.normalize_rating(provider, score)\r\n            for provider, score in ratings.items()\r\n        }\r\n        \r\n        # 加权综合评分\r\n        weights = [0.30, 0.25, 0.25, 0.20]  # 权重分配\r\n        providers = list(normalized.keys())\r\n        comprehensive = sum(\r\n            normalized[p] * w \r\n            for p, w in zip(providers, weights)\r\n        )\r\n        \r\n        return {\r\n            \"comprehensive_score\": round(comprehensive, 1),\r\n            \"rating_level\": self._score_to_level(comprehensive),\r\n            \"individual_ratings\": normalized,\r\n            \"key_strengths\": self._identify_strengths(normalized),\r\n            \"key_concerns\": self._identify_concerns(normalized),\r\n            \"peer_comparison\": self._compare_to_peer(company, comprehensive)\r\n        }\r\n    \r\n    def _score_to_level(self, score: float) -> str:\r\n        levels = {\r\n            (90, 100): \"AAA - 卓越\",\r\n            (80, 90): \"AA - 优秀\",\r\n            (70, 80): \"A - 良好\",\r\n            (60, 70): \"BBB - 平均偏上\",\r\n            (50, 60): \"BB - 平均\",\r\n            (40, 50): \"B - 低于平均\",\r\n            (0, 40): \"CCC/B - 落后\"\r\n        }\r\n        for (low, high), level in levels.items():\r\n            if low <= score <= high:\r\n                return level\r\n        return \"未知\"\r\n```\r\n\r\n### 2. Carbon Footprint Analysis / 碳足迹分析\r\n\r\n```python\r\nclass CarbonAnalyzer:\r\n    \"\"\"碳足迹核算\"\"\"\r\n    \r\n    def calculate_carbon_footprint(self, company_data: dict) -> dict:\r\n        \"\"\"\r\n        计算碳足迹（Scope 1, 2, 3）\r\n        \"\"\"\r\n        # Scope 1: 直接排放\r\n        scope1 = (\r\n            company_data.get(\"fuel_combustion\", 0) * 2.02 +  # CO2系数\r\n            company_data.get(\"vehicle_fleet\", 0) * 2.32 +\r\n            company_data.get(\"fugitive_emissions\", 0) * 25  # CH4当量\r\n        )\r\n        \r\n        # Scope 2: 间接排放（电力）\r\n        scope2 = (\r\n            company_data.get(\"electricity_kwh\", 0) * \r\n            company_data.get(\"grid_emission_factor\", 0.68)  # 中国电网系数\r\n        )\r\n        \r\n        # Scope 3: 价值链排放（简化版）\r\n        scope3 = {\r\n            \"上游采购\": company_data.get(\"purchased_goods\", 0) * 0.5,\r\n            \"运输配送\": company_data.get(\"transportation\", 0) * 0.1,\r\n            \"员工通勤\": company_data.get(\"employee_commute\", 0) * 0.02,\r\n            \"产品使用\": company_data.get(\"product_use\", 0) * 0.8,\r\n            \"报废处理\": company_data.get(\"end_of_life\", 0) * 0.05\r\n        }\r\n        \r\n        total_scope3 = sum(scope3.values())\r\n        \r\n        return {\r\n            \"scope1_tCO2e\": round(scope1, 2),\r\n            \"scope2_tCO2e\": round(scope2, 2),\r\n            \"scope3_tCO2e\": round(total_scope3, 2),\r\n            \"total_emissions\": round(scope1 + scope2 + total_scope3, 2),\r\n            \"intensity_metrics\": {\r\n                \"per_revenue\": round((scope1+scope2+total_scope3) / \r\n                                    max(company_data.get(\"revenue_yuan\", 1), 1) * 1e6, 2),  # tCO2e/百万营收\r\n                \"per_employee\": round((scope1+scope2+total_scope3) / \r\n                                      max(company_data.get(\"employees\", 1), 1), 2)  # tCO2e/人\r\n            },\r\n            \"scope_breakdown\": {\r\n                \"Scope 1\": round(scope1/(scope1+scope2+total_scope3+0.001)*100, 1),\r\n                \"Scope 2\": round(scope2/(scope1+scope2+total_scope3+0.001)*100, 1),\r\n                \"Scope 3\": round(total_scope3/(scope1+scope2+total_scope3+0.001)*100, 1)\r\n            }\r\n        }\r\n```\r\n\r\n### 3. Green Bond Analysis / 绿色债券分析\r\n\r\n```markdown\r\n## 绿色债券投资分析框架\r\n\r\n### 一、绿色债券认定\r\n| 标准 | 中国绿债标准 | 国际标准（GBP） |\r\n|-----|------------|---------------|\r\n| 募集资金用途 | ≥80%用于绿色项目 | ≥95%用于绿色项目 |\r\n| 项目评估 | 需第三方认证 | 需外部评审 |\r\n| 信息披露 | 年度+事件披露 | 发行时+续存期披露 |\r\n\r\n### 二、绿色债券筛选矩阵\r\n- [ ] 是否获得绿色债券认证\r\n- [ ] 第三方认证机构资质\r\n- [ ] 募集资金用途透明度\r\n- [ ] 环境效益量化指标\r\n- [ ] 续存期管理机制\r\n\r\n### 三、环境效益量化\r\n```python\r\ndef calculate_green_benefits(bond_data: dict) -> dict:\r\n    \"\"\"计算绿色债券环境效益\"\"\"\r\n    green_proceeds = bond_data[\"total_amount\"] * bond_data[\"green_ratio\"]\r\n    \r\n    benefits = {\r\n        \"annual_co2_reduction\": green_proceeds / 10000 * bond_data[\"carbon_factor\"],  # 吨CO2/年\r\n        \"annual_energy_saving\": green_proceeds / 10000 * bond_data[\"energy_factor\"],  # 吨标煤/年\r\n        \"equivalent_forests\": green_proceeds / 10000 * bond_data[\"forest_factor\"]  # 相当于造林面积(公顷)\r\n    }\r\n    \r\n    return benefits\r\n```\r\n```\r\n\r\n---\r\n\r\n## Disclaimer\r\n\r\nThis skill provides ESG analysis tools for educational purposes. ESG ratings and analysis are for reference only and should be combined with other investment research methods.\n\nFile v3.0.1:_meta.json\n\n{\n  \"ownerId\": \"kn74e704j3ygjcygnpf02rdvd185js13\",\n  \"slug\": \"security-esg-investing\",\n  \"version\": \"3.0.1\",\n  \"publishedAt\": 1779680443871\n}\n\nFile v3.0.1:skill-card.md\n\n## Description: <br>\nAI-powered ESG investing analysis assistant covering ESG rating analysis, green finance screening, carbon footprint assessment, and sustainable investment portfolio construction. <br>\n\nThis skill is ready for commercial/non-commercial use. <br>\n\n## Publisher: <br>\n[gechengling](https://clawhub.ai/user/gechengling) <br>\n\n### License/Terms of Use: <br>\nMIT-0 <br>\n\n\n## Use Case: <br>\nESG analysts, sustainable fund managers, institutional investors, and agents serving them use this skill to compare ESG ratings, screen green finance products, estimate carbon footprint inputs, and structure sustainable investment portfolio analysis. <br>\n\n### Deployment Geography for Use: <br>\nGlobal <br>\n\n## Known Risks and Mitigations: <br>\nRisk: Financial, regulatory, and carbon-accounting outputs may be outdated or incomplete if used as authoritative advice. <br>\nMitigation: Treat outputs as reference material and verify current rules, market data, ESG ratings, and emissions factors against authoritative sources before making decisions. <br>\nRisk: Broad ESG and sustainability trigger terms may activate the skill for general sustainability requests. <br>\nMitigation: Confirm the user needs ESG investing or sustainable finance analysis before applying the skill's frameworks. <br>\n\n\n## Reference(s): <br>\n- [ClawHub skill page](https://clawhub.ai/gechengling/security-esg-investing) <br>\n- [Publisher profile](https://clawhub.ai/user/gechengling) <br>\n\n\n## Skill Output: <br>\n**Output Type(s):** [text, markdown, code, guidance] <br>\n**Output Format:** [Markdown with example Python code blocks and analysis frameworks] <br>\n**Output Parameters:** [1D] <br>\n**Other Properties Related to Output:** [Reference-oriented ESG, green finance, carbon accounting, and portfolio analysis guidance] <br>\n\n## Skill Version(s): <br>\n3.0.1 (source: frontmatter and server release evidence) <br>\n\n## Ethical Considerations: <br>\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment. <br>\n\nArchive v2.0.0: 2 files, 3736 bytes\n\nFiles: SKILL.md (8544b), _meta.json (141b)\n\nFile v2.0.0:SKILL.md\n\n---\r\nname: ESG Investment Analysis Assistant\r\nslug: security-esg-investing\r\ndescription: AI-powered ESG investing analysis assistant — covers ESG rating analysis, green finance screening, carbon footprint assessment, and sustainable investment portfolio construction. Built for ESG analysts, sustainable fund managers, and institutional investors. Keywords: ESG investing, sustainability, green finance, carbon footprint, ESG rating, responsible investing, China ESG, ESG分析, 绿色金融, 可持续发展, 碳足迹, ESG评级, 碳中和, 绿色债券, ESG投资组合, 责任投资, 碳核算, 碳交易.\r\nversion: 1.0.0\r\n---\r\n\r\n# ESG Investment Analysis Assistant / ESG投资分析助手\r\n\r\n> **English:** AI-powered ESG investing analysis assistant — covers ESG rating comparison, green finance products, carbon accounting, and sustainable portfolio construction. Built for ESG analysts and sustainable investors.\r\n>\r\n> **中文:** ESG投资分析助手——覆盖ESG评级对比、绿色金融产品筛选、碳核算、可持续组合构建。适用：ESG分析师、可持续基金经理、机构投资者。\r\n\r\n---\r\n\r\n## Industry Pain Points / 行业痛点\r\n\r\n| Pain Point / 痛点 | Impact / 影响 | Solution / 本Skill解决方案 |\r\n|------------------|-------------|------------------------|\r\n| **ESG数据分散** | 评级机构超过10家，标准不统一 | 跨评级对比框架+综合评分 |\r\n| **\"漂绿\"风险** | 虚假绿色宣传导致合规风险 | 实质性分析+数据核实 |\r\n| **碳核算复杂** | Scope 1/2/3核算专业门槛高 | 分级碳核算模板+简化方法 |\r\n| **政策变化快** | 碳市场/ESG披露要求频繁更新 | 实时政策跟踪+合规提醒 |\r\n\r\n---\r\n\r\n## Trigger Keywords / 触发关键词\r\n\r\n**English Triggers:** ESG investing, sustainability, green finance, carbon footprint, ESG rating, responsible investing, ESG analysis, carbon trading, sustainable portfolio, China ESG\r\n\r\n**中文触发词（优先）：** ESG投资 / 可持续发展 / 绿色金融 / 碳足迹 / ESG评级 / 责任投资 / ESG分析 / 碳交易 / 可持续组合 / 碳中和 / 碳达峰 / 绿色债券 / ESG披露 / MSCI ESG / 责任投资 / 影响力投资\r\n\r\n---\r\n\r\n## Core Capabilities / 核心能力\r\n\r\n### 1. ESG Rating Analysis / ESG评级分析\r\n\r\n```python\r\nclass ESGAnalyzer:\r\n    \"\"\"ESG评级分析\"\"\"\r\n    \r\n    RATING_PROVIDERS = {\r\n        \"MSCI\": {\"scale\": \"CCC-AAA\", \"weight\": {\"E\": 0.25, \"S\": 0.25, \"G\": 0.50}},\r\n        \"Sustainalytics\": {\"scale\": \"0-100\", \"weight\": {\"E\": 0.33, \"S\": 0.33, \"G\": 0.33}},\r\n        \"商道融绿\": {\"scale\": \"D-A+\", \"weight\": {\"E\": 0.30, \"S\": 0.30, \"G\": 0.40}},\r\n        \"中证ESG\": {\"scale\": \"C-AAA\", \"weight\": {\"E\": 0.20, \"S\": 0.20, \"G\": 0.60}}\r\n    }\r\n    \r\n    def normalize_rating(self, provider: str, raw_score: float) -> float:\r\n        \"\"\"标准化评分到0-100\"\"\"\r\n        if provider == \"MSCI\":\r\n            scale = {\"CCC\": 10, \"B\": 20, \"BB\": 35, \"BBB\": 50, \"A\": 65, \"AA\": 80, \"AAA\": 95}\r\n            return scale.get(raw_score, 50)\r\n        elif provider == \"Sustainalytics\":\r\n            return 100 - raw_score  # 反转，风险分数→ESG分数\r\n        elif provider == \"商道融绿\":\r\n            scale = {\"D\": 20, \"C\": 40, \"B\": 60, \"B+\": 70, \"A\": 85, \"A+\": 95}\r\n            return scale.get(raw_score, 50)\r\n        return raw_score\r\n    \r\n    def comprehensive_analysis(self, company: str, \r\n                               ratings: dict) -> dict:\r\n        \"\"\"综合ESG分析\"\"\"\r\n        normalized = {\r\n            provider: self.normalize_rating(provider, score)\r\n            for provider, score in ratings.items()\r\n        }\r\n        \r\n        # 加权综合评分\r\n        weights = [0.30, 0.25, 0.25, 0.20]  # 权重分配\r\n        providers = list(normalized.keys())\r\n        comprehensive = sum(\r\n            normalized[p] * w \r\n            for p, w in zip(providers, weights)\r\n        )\r\n        \r\n        return {\r\n            \"comprehensive_score\": round(comprehensive, 1),\r\n            \"rating_level\": self._score_to_level(comprehensive),\r\n            \"individual_ratings\": normalized,\r\n            \"key_strengths\": self._identify_strengths(normalized),\r\n            \"key_concerns\": self._identify_concerns(normalized),\r\n            \"peer_comparison\": self._compare_to_peer(company, comprehensive)\r\n        }\r\n    \r\n    def _score_to_level(self, score: float) -> str:\r\n        levels = {\r\n            (90, 100): \"AAA - 卓越\",\r\n            (80, 90): \"AA - 优秀\",\r\n            (70, 80): \"A - 良好\",\r\n            (60, 70): \"BBB - 平均偏上\",\r\n            (50, 60): \"BB - 平均\",\r\n            (40, 50): \"B - 低于平均\",\r\n            (0, 40): \"CCC/B - 落后\"\r\n        }\r\n        for (low, high), level in levels.items():\r\n            if low <= score <= high:\r\n                return level\r\n        return \"未知\"\r\n```\r\n\r\n### 2. Carbon Footprint Analysis / 碳足迹分析\r\n\r\n```python\r\nclass CarbonAnalyzer:\r\n    \"\"\"碳足迹核算\"\"\"\r\n    \r\n    def calculate_carbon_footprint(self, company_data: dict) -> dict:\r\n        \"\"\"\r\n        计算碳足迹（Scope 1, 2, 3）\r\n        \"\"\"\r\n        # Scope 1: 直接排放\r\n        scope1 = (\r\n            company_data.get(\"fuel_combustion\", 0) * 2.02 +  # CO2系数\r\n            company_data.get(\"vehicle_fleet\", 0) * 2.32 +\r\n            company_data.get(\"fugitive_emissions\", 0) * 25  # CH4当量\r\n        )\r\n        \r\n        # Scope 2: 间接排放（电力）\r\n        scope2 = (\r\n            company_data.get(\"electricity_kwh\", 0) * \r\n            company_data.get(\"grid_emission_factor\", 0.68)  # 中国电网系数\r\n        )\r\n        \r\n        # Scope 3: 价值链排放（简化版）\r\n        scope3 = {\r\n            \"上游采购\": company_data.get(\"purchased_goods\", 0) * 0.5,\r\n            \"运输配送\": company_data.get(\"transportation\", 0) * 0.1,\r\n            \"员工通勤\": company_data.get(\"employee_commute\", 0) * 0.02,\r\n            \"产品使用\": company_data.get(\"product_use\", 0) * 0.8,\r\n            \"报废处理\": company_data.get(\"end_of_life\", 0) * 0.05\r\n        }\r\n        \r\n        total_scope3 = sum(scope3.values())\r\n        \r\n        return {\r\n            \"scope1_tCO2e\": round(scope1, 2),\r\n            \"scope2_tCO2e\": round(scope2, 2),\r\n            \"scope3_tCO2e\": round(total_scope3, 2),\r\n            \"total_emissions\": round(scope1 + scope2 + total_scope3, 2),\r\n            \"intensity_metrics\": {\r\n                \"per_revenue\": round((scope1+scope2+total_scope3) / \r\n                                    max(company_data.get(\"revenue_yuan\", 1), 1) * 1e6, 2),  # tCO2e/百万营收\r\n                \"per_employee\": round((scope1+scope2+total_scope3) / \r\n                                      max(company_data.get(\"employees\", 1), 1), 2)  # tCO2e/人\r\n            },\r\n            \"scope_breakdown\": {\r\n                \"Scope 1\": round(scope1/(scope1+scope2+total_scope3+0.001)*100, 1),\r\n                \"Scope 2\": round(scope2/(scope1+scope2+total_scope3+0.001)*100, 1),\r\n                \"Scope 3\": round(total_scope3/(scope1+scope2+total_scope3+0.001)*100, 1)\r\n            }\r\n        }\r\n```\r\n\r\n### 3. Green Bond Analysis / 绿色债券分析\r\n\r\n```markdown\r\n## 绿色债券投资分析框架\r\n\r\n### 一、绿色债券认定\r\n| 标准 | 中国绿债标准 | 国际标准（GBP） |\r\n|-----|------------|---------------|\r\n| 募集资金用途 | ≥80%用于绿色项目 | ≥95%用于绿色项目 |\r\n| 项目评估 | 需第三方认证 | 需外部评审 |\r\n| 信息披露 | 年度+事件披露 | 发行时+续存期披露 |\r\n\r\n### 二、绿色债券筛选矩阵\r\n- [ ] 是否获得绿色债券认证\r\n- [ ] 第三方认证机构资质\r\n- [ ] 募集资金用途透明度\r\n- [ ] 环境效益量化指标\r\n- [ ] 续存期管理机制\r\n\r\n### 三、环境效益量化\r\n```python\r\ndef calculate_green_benefits(bond_data: dict) -> dict:\r\n    \"\"\"计算绿色债券环境效益\"\"\"\r\n    green_proceeds = bond_data[\"total_amount\"] * bond_data[\"green_ratio\"]\r\n    \r\n    benefits = {\r\n        \"annual_co2_reduction\": green_proceeds / 10000 * bond_data[\"carbon_factor\"],  # 吨CO2/年\r\n        \"annual_energy_saving\": green_proceeds / 10000 * bond_data[\"energy_factor\"],  # 吨标煤/年\r\n        \"equivalent_forests\": green_proceeds / 10000 * bond_data[\"forest_factor\"]  # 相当于造林面积(公顷)\r\n    }\r\n    \r\n    return benefits\r\n```\r\n```\r\n\r\n---\r\n\r\n## Disclaimer\r\n\r\nThis skill provides ESG analysis tools for educational purposes. ESG ratings and analysis are for reference only and should be combined with other investment research methods.\n\nFile v2.0.0:_meta.json\n\n{\n  \"ownerId\": \"kn74e704j3ygjcygnpf02rdvd185js13\",\n  \"slug\": \"security-esg-investing\",\n  \"version\": \"2.0.0\",\n  \"publishedAt\": 1778509875657\n}","readmeExcerpt":"Skill: Security Esg Investing Owner: gechengling Summary: Provides AI-powered ESG rating comparison, carbon footprint calculation, green bond evaluation, and sustainable portfolio construction for ESG analysts and i... Tags: latest:3.0.3, security-esg-investing:3.0.3 Version history: v3.0.3 | 2026-10-08T05:10:02.910Z | user 3.0.3: content update v3.0.2 | 2026-09-12T07:22:53.945Z | user 内容增强：评级机构扩充至6家并补映射规则，新增分歧处理与映射注","codeSnippets":[],"executableExamples":[],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[{"path":"SKILL.md","content":"---\r\nname: ESG Investment Analysis Assistant\r\nslug: security-esg-investing\r\ndescription: AI-powered ESG investing analysis assistant for China market — compares ESG ratings across providers, screens green bonds, accounts for Scope 1/2/3 carbon emissions, and builds sustainable portfolios. Scope: ESG/sustainability analysis applied to investment decisions only; not general corporate ESG consulting, not climate policy research. Keywords: ESG rating comparison, green bond screening, carbon footprint accounting, Scope 3, sustainable portfolio construction, greenwashing check, China ESG, ESG评级对比, 绿色债券筛选, 碳足迹核算, 碳核算Scope3, 可持续组合构建, 漂绿识别, ESG披露口径.\r\nversion: \"3.0.3\"\r\n---\r\n\r\n# ESG Investment Analysis Assistant / ESG投资分析助手\r\n\r\n> **English:** AI-powered ESG investing analysis assistant — covers ESG rating comparison, green finance products, carbon accounting, and sustainable portfolio construction. Built for ESG analysts and sustainable investors.\r\n>\r\n> **中文:** ESG投资分析助手——覆盖ESG评级对比、绿色金融产品筛选、碳核算、可持续组合构建。适用：ESG分析师、可持续基金经理、机构投资者。\r\n\r\n\r\n## 数据最小化声明与执行边界 / Data Minimisation & Execution Boundary\r\n\r\n**数据最小化前置声明：** 使用本技能时，请只提供ESG分析所必需的输入——标的代码或公司名称、公开披露的排放与能耗数据、外部ESG评级结果、已脱敏的组合权重。**不要**粘贴未公开的企业能耗台账、供应商名单、员工个人信息、客户身份信息或受保密协议约束的尽职调查材料；企业侧数据请用\"行业+量级\"的脱敏形式提供。\r\n\r\n**保存与预览确认：** 本技能不执行任何保存动作。若你在自己环境中依据本技能生成ESG评级报告、碳核算表或绿债筛选结论，请在落盘或对外报送前**先预览结果、确认口径与数据来源无误，再保存或提交**。\r\n\r\n**代码块性质与执行边界**\r\n\r\n| 内容 | 性质 | 谁来执行 |\r\n|------|------|---------|\r\n| `ESGAnalyzer` 类（评级标准化/综合评分） | 评级归一化与加权口径的说明 | 由ESG分析师在自有研究系统中取数复现；技能不取数、不运行 |\r\n| `CarbonAnalyzer` 类（Scope 1/2/3） | 排放因子与核算边界的示意 | 由ESG分析师在自有系统中配置并运行 |\r\n| `calculate_green_benefits()` | 环境效益折算的算法表达 | 同上，属教学示意；折算系数须取自发行文件 |\r\n| 筛选矩阵、打分表、检查表 | 管理用模板 | 由研究/合规人员在机构流程中落实 |\r\n\r\n本技能未配置任何工具调用权限，不执行代码、不读写文件、不访问外部ESG数据库或行情数据源，也不生成可直接报送的监管报表。文中代码块均为口径的教学示意，读者可在自己环境中参考实现；ESG评级与碳核算结果须经独立复核后方可用于决策。\r\n\r\n---\r\n\r\n---\r\n\r\n\r\n### 证券监管最新动态 [2026-10-08更新]\r\n\r\n| 动态类型 | 内容摘要 | 影响范围 | ESG侧应对动作 | 责任岗 | 优先级 | 复核频率 | |\r\n|---------|---------|---------|-------------|-------|-------|---|\r\n| 证券监管 | 2026年Q1：ESG信息披露要求扩大至非上市企业 | ESG投资分析框架需更新最新信披要求和绿色金融政策 | 供应链ESG数据采集范围同步扩大 | 研究 | 高 | 每季 |\r\n| 证券监管 | 绿色金融信贷导向政策升级，ESG投资环境改善 | ESG投资分析框架需更新最新信披要求和绿色金融政策 | 绿色资产识别标准与信贷口径对齐 | 研究 | 中 | 每季 |\r\n| 证券监管 | 证监会加强ESG相关信披监管，ESG评级标准趋严 | ESG投资分析框架需更新最新信披要求和绿色金融政策 | 评级来源与取数日期须在报告中标注 | 合规 | 高 | 每月 |\r\n| 可持续披露 | 可持续披露规则推进，披露范围与颗粒度提升 | ESG评级输入数据、组合披露 | 建立披露数据映射表，统一口径 | 研究 | 高 | 每季 |\r\n| 反漂绿 | 绿色宣传与绿色产品命名合规要求趋严 | 绿色基金命名、宣传物料 | 产品命名与投资范围一致性自查 | 合规 | 高 | 每季 |\r\n| 碳市场 | 碳市场覆盖行业范围与交易规则持续完善 | 碳成本测算、高碳行业敞口 | 碳价情景纳入估值敏感性 | 研究 | 中 | 每月 |\r\n| 绿色债券 | 绿色债券募集资金用途与存续期披露要求细化 | 绿债筛选与投后跟踪 | 存续期环境效益跟踪清单化管理 | 研究 | 中 | 每季 |\r\n| 数据合规 | ESG数据来源与第三方数据使用需合规授权 | 外部评级与数据库采购 | 数据来源授权凭证归档，标注使用范围 | 合规 | 中 | 每季 |\r\n| 可持续披露 | 2026年10月：可持续披露的指标颗粒度与可比性要求进一步细化，跨期数据须可追溯 | ESG评级输入、组合定期披露 | 建立指标口径台账，同一指标的跨期变化须标注统计方法是否变更 | 研究 | 高 | 每季 |\r\n| 碳市场 | 2026年四季度初：碳市场行业覆盖范围与配额分配规则的调整预期增强 | 碳成本测算、高碳行业敞口 | 碳价情景由单档改为上下行双档，敏感性分析同步更新 | 研究 | 中 | 每月 |\r\n\r\n> **数据截止**: 2026-10-08 | 来源：证监会、生态环境部门公开规则、交易所公开信息\r\n> **声明**: 以上动态供参考，具体以官方最新发布为准\r\n\r\n**动态解读示例（四类高频场景）**\r\n\r\n- **场景A｜反漂"},{"path":"_meta.json","content":"{\n  \"ownerId\": \"kn74e704j3ygjcygnpf02rdvd185js13\",\n  \"slug\": \"security-esg-investing\",\n  \"version\": \"3.0.3\",\n  \"publishedAt\": 1791436202910\n}"},{"path":"skill-card.md","content":"## Description:\n\nHelps ESG analysts compare ratings, estimate Scope 1–3 emissions, screen green bonds, and assess sustainable portfolios for investment decisions in the China market.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[gechengling](https://clawhub.ai/user/gechengling)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nESG analysts and sustainable investors use this skill to compare issuer ratings, evaluate emissions and green bonds, and review portfolio sustainability when assessing investable assets. Outputs are educational inputs to research, not independently verified investment or regulatory advice.\n\n### Deployment Geography for Use:\n\nChina\n\n## Known Risks and Mitigations:\n\nRisk: Stale regulatory claims, ESG ratings, or emissions factors could distort investment decisions or external reports.\n\nMitigation: Verify current rules, source dates, ratings, emissions factors, and calculation assumptions before relying on results or publishing them.\n\nRisk: Sensitive company or personal information could be exposed if supplied for analysis.\n\nMitigation: Use public data and de-identified portfolio inputs; omit confidential records and personal information.\n\n## Reference(s):\n\n- [Security Esg Investing on ClawHub](https://clawhub.ai/gechengling/skills/security-esg-investing)\n\n## Skill Output:\n\n**Output Type(s):** [Analysis, Guidance, Code]\n\n**Output Format:** [Markdown with tables and illustrative Python code]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Example calculations and screening checklists require independent data and source verification.]\n\n## Skill Version(s):\n\n3.0.3 (source: frontmatter, release evidence)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment."}],"languages":[],"docsSourceLabel":"CLAWHUB","editorialOverview":"Provides AI-powered ESG rating comparison, carbon footprint calculation, green bond evaluation, and sustainable portfolio construction for ESG analysts and i... Skill: Security Esg Investing Owner: gechengling Summary: Provides AI-powered ESG rating comparison, carbon footprint calculation, green bond evaluation, and sustainable portfolio construction for ESG analysts and i... 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