← 返回 Skills 市场
gechengling

Finance Data Analysis

作者 lingfeng-19 · GitHub ↗ · v3.0.1 · MIT-0
cross-platform ✓ 安全检测通过
54
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install finance-data-analysis
功能描述
Provides AI-driven financial data analysis including KPI tracking, financial statement evaluation, data visualization, and automated reporting for decision s...
使用说明 (SKILL.md)

\r \r

Financial Industry Data Analysis Expert / 金融数据分析专家\r

\r

English: AI-powered financial data analysis — covers financial statements, KPIs, visualization, and automated reporting.\r \r 中文: 金融数据分析——覆盖财务报表、KPI、可视化、自动化报告。\r \r ---\r \r \r

金融监管最新动态 [2026-05-25更新]\r

\r | 动态类型 | 内容摘要 | 影响范围 |\r |---------|---------|---------|\r | 金融监管 | 2026年Q1:金融数据合规要求提升 | 数据分析框架需纳入合规和信披新标准 |\r | 金融监管 | 理财信息披露'三清'推进,数据分析需关注新标准 | 数据分析框架需纳入合规和信披新标准 |\r | 金融监管 | 反洗钱数据监控要求加强 | 数据分析框架需纳入合规和信披新标准 |\r \r

数据截止: 2026-05-25 | 来源:证监会、NFRA、中证协、安永Q1分析\r 声明: 以上动态供参考,具体以官方最新发布为准\r \r

Industry Pain Points / 行业痛点\r

\r | Pain Point / 痛点 | Impact / 影响 | Solution / 本Skill解决方案 |\r |------------------|-------------|------------------------|\r | 数据分散 | 数据源多,整合耗时 | 统一数据模型 |\r | 手工报表多 | 月报/季报重复劳动 | 自动报告生成 |\r | 分析浅 | 只看表面数字 | 深度归因分析 |\r | 可视化差 | 图表不直观 | 专业可视化模板 |\r \r ---\r \r

Trigger Keywords / 触发关键词\r

\r English Triggers: financial data analysis, KPI dashboard, data visualization, financial reporting, Python analysis\r \r 中文触发词(优先): 数据分析 / 财务分析 / KPI追踪 / 数据可视化 / 自动化报告 / Python分析 / SQL查询 / 数据看板 / 经营分析 / 业绩分析 / 同比环比\r \r ---\r \r

Core Capabilities / 核心能力\r

\r

1. Financial Analysis Templates / 财务分析模板\r

\r

class FinancialAnalyzer:\r
    """财务分析引擎"""\r
    \r
    def income_statement_analysis(self, data: dict) -> dict:\r
        """损益表分析"""\r
        return {\r
            "收入趋势": self._trend_analysis(data["revenue"]),\r
            "毛利率分析": self._gross_margin_analysis(data),\r
            "费用结构": self._expense_breakdown(data),\r
            "利润质量": self._profit_quality_analysis(data)\r
        }\r
    \r
    def ratio_analysis(self, financial_data: dict) -> dict:\r
        """比率分析"""\r
        ratios = {\r
            "盈利能力": {\r
                "毛利率": data["gross_profit"] / data["revenue"],\r
                "净利率": data["net_profit"] / data["revenue"],\r
                "ROE": data["net_profit"] / data["equity"]\r
            },\r
            "运营效率": {\r
                "存货周转": data["cogs"] / data["inventory"],\r
                "应收账款周转": data["revenue"] / data["ar"]\r
            },\r
            "偿债能力": {\r
                "流动比率": data["current_assets"] / data["current_liabilities"],\r
                "资产负债率": data["total_liabilities"] / data["total_assets"]\r
            }\r
        }\r
        return ratios\r
```\r
\r
### 2. Dashboard Templates / 数据看板模板\r
\r
```python\r
DASHBOARD_TEMPLATES = {\r
    "CFO驾驶舱": {\r
        "widgets": [\r
            {"type": "kpi_card", "metrics": ["营收", "利润", "ROE"]},\r
            {"type": "line_chart", "data": "收入趋势"},\r
            {"type": "bar_chart", "data": "各业务线收入"},\r
            {"type": "waterfall", "data": "利润变动归因"},\r
            {"type": "gauge", "data": "KPI完成率"}\r
        ]\r
    },\r
    "业务分析看板": {\r
        "widgets": [\r
            {"type": "funnel", "data": "转化漏斗"},\r
            {"type": "heat_map", "data": "客户活跃度"},\r
            {"type": "pie_chart", "data": "客户分布"},\r
            {"type": "trend", "data": "关键指标趋势"}\r
        ]\r
    }\r
}\r
```\r
\r
---\r
\r
## Disclaimer\r
\r
This skill provides data analysis tools for educational purposes.\r
安全使用建议
Install only if you want a finance-oriented analysis assistant. Do not paste confidential, nonpublic, personal, customer, or regulated financial data unless your organization allows it, and be explicit that you want finance-specific analysis so the broad triggers do not activate unintentionally.
能力评估
Purpose & Capability
The described purpose, financial data analysis, is coherent with analysis workflows such as SQL, Python, visualization, and finance-focused reporting.
Instruction Scope
The trigger language is broad and may activate for generic data or SQL requests, so users should invoke it only when they clearly want finance-related analysis.
Install Mechanism
No suspicious install mechanism, executable component, package install, or hidden setup behavior was identified from the supplied evidence.
Credentials
Financial analysis may involve confidential or regulated data, but the evidence does not show automatic file access, credential use, network exfiltration, or mutation authority.
Persistence & Privilege
No persistence, privilege escalation, background worker, credential store access, or long-running process behavior was identified.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install finance-data-analysis
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /finance-data-analysis 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v3.0.1
- Enhanced skill description to clearly outline key features and target users in both English and Chinese. - Added latest financial regulatory updates (as of 2026-05-25), emphasizing new compliance and disclosure standards impacting data analysis. - Explicitly listed industry pain points and mapped each to skill-specific solutions. - Defined and expanded English and Chinese trigger keywords for easier access. - Detailed core capabilities with ready-to-use financial analysis and dashboard Python templates. - Included a disclaimer clarifying the tool’s educational purpose.
元数据
Slug finance-data-analysis
版本 3.0.1
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Finance Data Analysis 是什么?

Provides AI-driven financial data analysis including KPI tracking, financial statement evaluation, data visualization, and automated reporting for decision s... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 54 次。

如何安装 Finance Data Analysis?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install finance-data-analysis」即可一键安装,无需额外配置。

Finance Data Analysis 是免费的吗?

是的,Finance Data Analysis 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Finance Data Analysis 支持哪些平台?

Finance Data Analysis 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Finance Data Analysis?

由 lingfeng-19(@gechengling)开发并维护,当前版本 v3.0.1。

💬 留言讨论