--- name: a-share-management-quality-0d349c405177 description: A股管理层质量评估/公司治理分析。当用户说"管理层"、"管理层怎么样"、"公司治理"、"management"、"CEO"、"董事长"、"高管"、"治理结构"、"XX的管理层靠谱吗"、"实控人"、"管理层激励"时触发。评估上市公司管理层能力（战略/执行/资本配置）、治理结构（股权制衡/独董/激励机制）、诚信记录，辅助判断管理层是否值得信赖。支持研报风格（formal）和快速评估风格（brief）。 --- # A股管理层质量评估/公司治理分析助手 ## 数据源 ```bash SCRIPTS="$SKILLS_ROOT/cn-stock-data/scripts" # 财务数据（业绩趋势反映执行力） python "$SCRIPTS/cn_stock_data.py" finance --code [CODE] # 十大股东（股权结构/集中度） python -c "import efinance as ef; df=ef.stock.get_top10_stock_holder_info(stock_code='[CODE]'); print(df.to_json(orient='records', force_ascii=False))" # 个股行情 python "$SCRIPTS/cn_stock_data.py" quote --code [CODE] # K线（任期内股价表现） python "$SCRIPTS/cn_stock_data.py" kline --code [CODE] --freq daily --start [日期] ``` 补充：通过 web 搜索获取管理层简历、过往业绩、诚信记录、薪酬数据、年报致辞、投资者关系互动、处罚记录等。 ## Workflow ### Step 1: 管理层画像（Management Profile） 通过 web 搜索获取核心高管信息： - **核心人物**：董事长、总经理/CEO、财务总监（CFO）、实际控制人 - **背景调查**：学历、从业年限、行业经验、过往任职公司及业绩 - **稳定性**：核心高管任期长度、近年是否有频繁离职/更换 - **诚信记录**：是否有证监会处罚、诉讼纠纷、失信记录 ### Step 2: 任期业绩追踪（Track Record） 通过 cn-stock-data finance 获取财务数据，分析管理层任期内： - **营收增长趋势**：是否持续增长、增速变化 - **利润质量**：净利率、经营现金流/净利润比率 - **ROE 变化**：衡量资本配置能力 - **承诺兑现度**：对比历年年报/投资者交流中的目标 vs 实际完成 > 好的管理层 = 说到做到，业绩趋势稳步向上。 ### Step 3: 治理结构分析（Governance Structure） 通过 efinance 十大股东数据 + web 搜索： - **股权集中度**：第一大股东持股比例、前十大股东合计、是否"一股独大" - **股权制衡**：第二大股东能否制衡第一大股东 - **独立董事**：独董占比（≥1/3 为合规底线）、独董背景是否真正独立 - **审计委员会**：是否有效运作、审计机构是否频繁变更 - **关联交易**：关联交易规模和频率、是否存在利益输送嫌疑 > 详见 [references/management-quality-guide.md](references/management-quality-guide.md) 中的治理红旗和A股特色问题。 ### Step 4: 利益一致性检查（Alignment Check） - **管理层持股**：核心高管持股比例、近期增减持行为 - **股权激励**：是否有股权激励计划、行权条件是否合理（过低=送钱、过高=摆设） - **薪酬合理性**：高管薪酬 vs 公司业绩 vs 行业水平 - **分红政策**：分红率是否稳定、是否慷慨但不过度 > 管理层大量增持 = 利益绑定信号；频繁减持 = 需警惕。 ### Step 5: 输出（管理层评分） | 维度 | formal | brief | |------|--------|-------| | 输出格式 | 完整治理分析报告（4-6页） | 快速评估要点 | | 管理层画像 | 核心高管逐人分析 | 仅列关键人物和亮点/风险点 | | 业绩追踪 | 多年财务趋势图表+承诺兑现度 | 仅ROE/营收趋势方向 | | 治理结构 | 股权结构图+独董/委员会详情 | 仅标注治理红旗/绿旗 | | 利益一致性 | 持股/激励/薪酬详细数据 | 仅增减持方向和激励有无 | | 综合评分 | 五维雷达图（能力/诚信/激励/治理/稳定性） | 一句话结论+评级 | | 结论 | 客观陈述各维度评估 | 可加简要判断（"管理层可信"/"需关注XX风险"） | 默认风格：brief。用户要求"详细分析"/"出报告"时用 formal。 综合评级参考： - **A（优秀）**：能力强+诚信好+利益一致+治理规范+团队稳定 - **B（良好）**：多数维度达标，个别有小瑕疵 - **C（一般）**：存在明显短板但无重大红旗 - **D（警惕）**：多个治理红旗，管理层可信度存疑 ## 关键规则 1. **管理层评估主观性强，需多维交叉验证**：不能仅凭单一维度下结论，需财务数据+行为数据+公开信息综合研判 2. **言行一致是核心标准**：对比管理层历年公开承诺与实际业绩，说到做到比什么都重要 3. **关注管理层增减持行为**：管理层用真金白银投票比任何言论更可信 4. **好公司+差管理层=风险**：再好的商业模式也可能被不靠谱的管理层毁掉 5. **不做交易建议**：只评估管理层质量，不建议"因为管理层好所以买入" 6. **数据时效**：管理层信息可能有滞后，分析时注明信息截止日期 ## 使用示例 ### 示例 1: 基本使用 ```python # 调用 skill result = run_skill({ "param1": "value1", "param2": "value2" }) ``` ### 示例 2: 命令行使用 ```bash python scripts/run_skill.py --input data.json ``` --- Source attribution: aifinlab Original project: https://github.com/aifinlab/FinClaw/blob/9e62862d1412157fa03ffd1f0b74969dcf0ed66c/skills/a-share-management-quality/SKILL.md License: Apache-2.0 License information: https://www.apache.org/licenses/LICENSE-2.0 Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. 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See the License for the specific language governing permissions and limitations under the License. # Mega AI Hub resource metadata Creator / publisher: aifinlab Original project: https://github.com/aifinlab/FinClaw/blob/9e62862d1412157fa03ffd1f0b74969dcf0ed66c/skills/a-share-management-quality/SKILL.md Attribution basis: Source repository record Fields of work: Data & Analytics, Finance & Accounting, Sales Roles: Business Development, Financial Analyst, Market Research Analyst Specialties: Specialty not specified Tools: Cn Stock Data, Efinance Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: debc0e553a7de0121bcf3a261720d41823d139301e03e2adb7c7bd4955a4aa47