财务数据生成分析报告

SKILL研究检索

原名 Financial Report Generator · 标识 financial-report-generator

研究检索 未标注权限 许可证不明确
安装这个技能

上传 Excel 或 CSV 财务数据,即可完成统计分析、生成图表可视化,并整理成适合管理层阅读的 Word 专业报告,报告结构清晰可直接使用。

一句话选型结论

按资料字段整理

财务数据生成分析报告是研究检索类的 Agent Skill,安装方式未标注,权限级别未标注,许可证不明确,有可直接复制的安装命令。技能本质是给模型读的说明书,效果取决于模型与客户端;装完先用一个小任务验证,再放进正式流程。

分类研究检索 安装方式未标注 权限级别未标注权限 许可证许可证不明确
累计安装 未标注 本周 未标注
GitHub 星标 未标注 仓库 未标注
下载量 未标注 技能市场下载数
权限级别 未标注权限 安装前请确认风险范围
许可证 许可证不明确 未说明

安装

未标注
在支持 Skills 的客户端里执行,装完问一句「你有哪些技能」验证
skillhub install user_6723fe8d/ssssaaa3459102
  1. 1
    确认客户端支持

    确认你的客户端支持 Skills(Claude、Codex、Cursor 等),并升级到较新的版本。

  2. 2
    拿到技能文件

    执行上面的命令安装;也可以把仓库里的 SKILL.md 手动放进客户端的 skills 目录。

  3. 3
    刷新技能列表

    重新打开客户端,或刷新技能列表,让新放进来的技能被加载。

  4. 4
    验证是否生效

    问一句「你有哪些技能」,确认列表里出现它,再拿一个小任务试跑。

技能档案

研究检索
字段来自技能仓库与公开索引,中文说明由本站标注
作者 / 维护方user_6723fe8d仓库 未标注 · 版本 未标注
宿主客户端未标注技能可被这些客户端加载
安装方式未标注安装包 community
权限级别未标注权限安装前请确认风险范围
许可证未说明许可证不明确,商用前请自行确认条款
仓库可用性available技能仓库当前是否可访问
最近核验2026-11-06上游最后核验时间 · 数据更新 2026-11-06
正文体量7.7 KBSKILL.md 原文大小,越大说明说明书写得越细

能做什么

0 项能力
上游给出的能力概览与适用场景
财务数据统计分析经营图表可视化制作管理层财务报告撰写

典型使用场景

3 类
按分类整理的常见用法,具体以 SKILL.md 为准
查资料并整理出处

让模型按主题查资料,并把引用来源整理成清单。

网页与文献要点提炼

把长文、论文、网页压成能直接看的要点。

竞品与行业汇总

按关键词汇总竞品动态与行业信息。

选择建议

装之前先看这几条
按条目字段给出的判断,不替你决定用不用

值得选的地方

  • 有可直接复制的安装命令,不用自己翻文档找入口。

先想清楚的地方

  • 没有标注权限级别,实际能做什么要装好后确认。
  • 许可证不明确,商用或二次分发前先到仓库确认条款。
  • 没有做站内核验,内容以作者仓库为准。
  • 技能只是说明书,实际效果取决于模型与客户端,装完先用小任务试一遍。

更适合

  • 需要在研究检索场景里给模型补一套做法的人。
  • 愿意先读一遍 SKILL.md、确认它会让模型做什么的人。

不太适合

  • 对许可证要求很严、必须明确可商用的人。
  • 只想装完就自动变强、不打算看说明书的人。

同类对比

6 个同类
同分类里挑最接近的几条,字段以各自详情页为准
技能权限级别安装方式累计安装宿主客户端安装命令
财务数据生成分析报告当前 未标注权限 未标注 未标注 未标注 有
寻找技能 浏览器控制 GitHub 仓库 3120.0 万 Codex、Claude、Cursor 有
自我改进 Agent 接触敏感数据 ClawHub 市场 1646.4 万 OpenClaw 有
灵魂追踪 联网访问 GitHub 仓库 758.9 万 Codex、Claude、Cursor 有
自我完善 联网访问 ClawHub 市场 682.9 万 OpenClaw 有
微软代工厂 调用外部服务 GitHub 仓库 661.4 万 Codex、Claude、Cursor 有

SKILL.md 全文

7.7 KB
模型实际读到的说明书原文,来自技能仓库

Financial Report Generator

Overview

This skill enables the creation of professional financial and business analysis reports from raw data files. It transforms Excel/CSV data into executive-ready Word documents with intelligent analysis, appropriate charts, and structured insights.

When to use this skill:
- User uploads Excel/CSV files with financial or business data
- User requests data analysis and visualization
- User needs professional reports for management/executives
- User wants monthly/quarterly business analysis reports
- User mentions "financial report", "business analysis", "management report"

Core Workflow

Follow this sequential workflow when generating reports:

1. Data Intake & Analysis

  • Read and parse Excel/CSV files
  • Perform statistical analysis (trends, comparisons, ratios)
  • Identify key metrics and patterns
  • See scripts/analyze_data.py for analysis utilities

2. Chart Generation

  • Select appropriate chart types based on data characteristics
  • Generate charts using Python (matplotlib/seaborn)
  • Save charts as images for embedding in Word
  • See scripts/generate_charts.py for chart generation
  • See references/chart_guide.md for chart selection criteria

3. Report Structure & Content

  • Follow the standard report structure from references/report_structure.md
  • Include: Executive Summary, Key Metrics, Trend Analysis, Insights & Recommendations
  • Use professional formatting and clear data visualization

4. Word Document Generation

  • Use the docx-js library to create formatted Word documents
  • Apply consistent styling and branding
  • Embed charts and tables appropriately
  • See scripts/create_report.py for document generation
  • Reference the report template at assets/report_template.docx

Quick Reference

Task Approach Script/Reference
Read Excel/CSV Use pandas to parse data scripts/analyze_data.py
Generate charts Match chart type to data scripts/generate_charts.py, references/chart_guide.md
Create report structure Follow standard template references/report_structure.md
Generate Word doc Use docx-js library scripts/create_report.py

Report Structure Guidelines

All reports should follow this professional structure:

1. Executive Summary (执行摘要)

  • Key findings and insights
  • Critical metrics and trends
  • Strategic recommendations

2. Business Overview (经营概况)

  • Revenue and growth metrics
  • Market position and competitive landscape
  • Industry context and benchmarks

3. Financial Analysis (财务分析)

  • Revenue analysis by segment/product
  • Cost structure and profitability
  • Key financial ratios and indicators
  • Month-over-month and year-over-year comparisons

4. Key Performance Indicators (关键指标)

  • Market share and growth rates
  • Customer acquisition and retention
  • Operational efficiency metrics

5. Insights & Recommendations (专业建议)

  • Strategic opportunities
  • Risk factors and mitigation
  • Actionable recommendations for management

For detailed structure and examples, see references/report_structure.md.

Chart Selection Guide

Choose chart types based on data characteristics:

Data Type Recommended Chart When to Use
Time series/trends Line chart Showing trends over time
Comparisons Bar/Column chart Comparing categories or periods
Composition Pie/Doughnut chart Showing parts of a whole
Relationships Scatter plot Correlation between variables
Distribution Histogram Frequency distribution
Multi-dimensional Stacked bar/area chart Multiple data series

For detailed guidance, see references/chart_guide.md.

Technical Implementation

Data Analysis

Use Python with pandas for data processing:

import pandas as pd

# Read Excel file
df = pd.read_excel('data.xlsx', sheet_name='Sheet1')

# Basic statistics
summary = df.describe()

# Time series analysis
monthly_trend = df.groupby('Month')[['Revenue', 'Profit']].sum()

# Calculate ratios
df['Profit_Margin'] = df['Profit'] / df['Revenue'] * 100

For advanced analysis functions, see scripts/analyze_data.py.

Chart Generation

Generate charts using matplotlib and save as PNG for Word embedding:

import matplotlib.pyplot as plt
import seaborn as sns

# Line chart for trends
plt.figure(figsize=(10, 6))
plt.plot(df['Month'], df['Revenue'])
plt.title('Monthly Revenue Trend')
plt.savefig('revenue_trend.png', dpi=300, bbox_inches='tight')

For chart generation utilities, see scripts/generate_charts.py.

Word Document Creation

Use docx-js (Node.js) to create formatted Word documents:

const { Document, Packer, Paragraph, TextRun, Table, ImageRun } = require('docx');

// Create document with professional formatting
const doc = new Document({
  sections: [{
    children: [
      new Paragraph({
        text: 'Monthly Business Analysis Report',
        heading: HeadingLevel.HEADING_1
      }),
      // Add content, tables, and images
    ]
  }]
});

// Save document
Packer.toBuffer(doc).then(buffer => {
  fs.writeFileSync('report.docx', buffer);
});

For document generation utilities, see scripts/create_report.py.

Examples

Example 1: Monthly Business Analysis Report

User request: "我上传了公司2024年5月的经营数据(Excel文件),帮我生成一份给老板看的月度经营分析报告。"

Skill workflow:
1. Read Excel file with revenue, cost, profit data by department
2. Calculate key metrics: total revenue, profit margin, YoY growth
3. Generate charts: revenue trend (line), cost breakdown (pie), profit by department (bar)
4. Structure report: Executive Summary → Business Overview → Financial Analysis → KPIs → Recommendations
5. Generate Word document with professional formatting and embedded charts

Example 2: Financial Performance Report

User request: "基于这份财务年报,生成一份专业的财务分析报告,包括盈利能力、偿债能力和运营效率分析。"

Skill workflow:
1. Parse financial statements from the annual report
2. Calculate financial ratios: ROE, ROA, current ratio, asset turnover
3. Generate charts: ratio trends, comparative analysis
4. Structure report with financial analysis focus
5. Output Word document with detailed financial insights

Resources

This skill includes the following resources:

scripts/

  • analyze_data.py - Data analysis and statistical utilities
  • generate_charts.py - Chart generation with matplotlib
  • create_report.py - Word document creation utilities

references/

  • report_structure.md - Detailed report structure and formatting guidelines
  • chart_guide.md - Chart selection criteria and best practices
  • financial_metrics.md - Common financial metrics and calculations

assets/

  • report_template.docx - Word document template with professional formatting

常见问题

5 问
答案由本站依据条目字段整理
财务数据生成分析报告怎么安装?

在支持 Skills 的客户端里执行:skillhub install user_6723fe8d/ssssaaa3459102。安装方式为未标注。装完刷新技能列表或重开客户端。

财务数据生成分析报告支持哪些客户端?

资料没有标注宿主客户端,但只要客户端支持 Skills(Claude、Codex、Cursor 等),一般都能加载。

财务数据生成分析报告权限高吗,安全吗?

权限级别为未标注权限。安装前先看它会读取或写入哪些内容。

财务数据生成分析报告收费吗?

本站不代收费用,也没有标注具体价格。是否收费取决于技能本身和所用的模型或客户端,正式使用前按作者说明确认。

财务数据生成分析报告用什么许可证?

许可证标注为 未说明(许可证不明确)。商用或二次分发前请到仓库确认条款原文。

热门专题

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技能内容以作者仓库为准;分类、权限级别与许可证状态的中文说明为中文整理,最近核验 2026-11-06。