---
id: sm-finance-manager
name: "finance-manager"
url: https://skills.yangsir.net/skill/sm-finance-manager
author: ailabs-393
domain: finance
tags: ["financial-management", "budgeting", "expense-tracking", "investment-analysis", "personal-finance"]
install_count: 1600
rating: 4.30 (20 reviews)
github: https://github.com/ailabs-393/ai-labs-claude-skills
---

# finance-manager

> 提供全面的个人财务管理工具包，处理交易数据，进行复杂财务分析并生成可操作的洞察。

**Stats**: 1,600 installs · 4.3/5 (20 reviews)

## Before / After 对比

### 个人财务管理效率与洞察

| Metric | Before | After | Change |
|---|---|---|---|
| - | - | - | - |
| - | - | - | - |
| - | - | - | - |

## Readme

# finance-manager

# Finance Manager

A comprehensive toolkit for personal finance management that processes transaction data, performs sophisticated financial analysis, generates actionable insights, and creates beautiful visual reports.

## Core Capabilities

- **Transaction Data Processing**: Extract financial data from PDFs, CSVs, or JSON files

- **Financial Analysis**: Calculate key metrics, identify spending patterns, and track savings

- **Visualization**: Generate interactive HTML reports with charts and graphs

- **Budget Recommendations**: Provide personalized, actionable advice based on spending patterns

- **Trend Analysis**: Identify spending patterns, anomalies, and opportunities for optimization

## Workflow

### 1. Data Extraction and Preparation

**For PDF files:**

```
python scripts/extract_pdf_data.py <input.pdf> <output.csv>

```

**For CSV/JSON files:**

- Ensure data has columns: `Date`, `Description`, `Income` (category), `Type`, `Amount`

- Date format: YYYY-MM-DD or parseable date string

- Amount: Positive for income, negative for expenses

### 2. Financial Analysis

Run comprehensive analysis on transaction data:

```
python scripts/analyze_finances.py <transactions.csv> > analysis_output.json

```

**Output includes:**

- Summary statistics (total income, expenses, net savings, savings rate)

- Spending trends (daily averages, top expenses, category percentages)

- Budget recommendations (personalized based on spending patterns)

- Visualization data (prepared for charting)

### 3. Report Generation

Create interactive HTML report with visualizations:

```
python scripts/generate_report.py <analysis_output.json> <report.html>

```

**Report features:**

- Summary dashboard with key metrics

- Interactive pie chart showing spending by category

- Bar chart comparing income vs expenses over time

- Color-coded indicators (green for positive, red for negative)

- Personalized recommendations section

- Responsive design for all devices

### 4. Complete Workflow Example

```
# Extract data from PDF
python scripts/extract_pdf_data.py finance_data.pdf transactions.csv

# Analyze the data
python scripts/analyze_finances.py transactions.csv > analysis.json

# Generate visual report
python scripts/generate_report.py analysis.json financial_report.html

```

## Key Metrics and Benchmarks

### Savings Rate

```
Savings Rate = (Total Income - Total Expenses) / Total Income × 100

```

**Benchmarks:**

- Below 10%: Needs improvement

- 10-20%: Good

- 20-30%: Excellent

- Above 30%: Outstanding

### Category Guidelines (% of income)

- Housing: 25-30%

- Transportation: 10-15%

- Food: 10-15%

- Utilities: 5-10%

- Savings: Minimum 20%

For detailed frameworks and methodologies, see `references/financial_frameworks.md`.

## Analysis Features

### Summary Statistics

- Total income and expenses for the period

- Net savings (can be positive or negative)

- Savings rate percentage

- Transaction count

- Date range covered

### Spending Trends

- Daily average spending

- Top 5 largest expenses with details

- Category percentage breakdown

- Spending patterns over time

### Budget Recommendations

The system generates personalized recommendations based on:

- Savings rate thresholds

- Category spending percentages

- Income diversification

- Budget guideline comparisons

**Example recommendations:**

- "⚠️ Your savings rate is below 10%. Consider reducing discretionary spending."

- "🍽️ Food spending is 18% of expenses. Consider meal planning to reduce costs."

- "✅ Excellent savings rate! You're on track for strong financial health."

## Visualization Components

### Category Spending Chart (Doughnut)

Shows proportional breakdown of expenses by category with color coding.

### Income vs Expenses Chart (Bar)

Displays monthly comparison of income and expenses to identify cash flow trends.

### Interactive Features

- Hover tooltips showing exact values

- Responsive design adapting to screen size

- Color-coded positive (green) and negative (red) indicators

## Tips for Best Results

### Data Quality

- Ensure all transactions are properly categorized

- Use consistent category names

- Include complete date information

- Verify amounts are correctly signed (+ for income, - for expenses)

### Analysis Frequency

- Run monthly analysis for trend tracking

- Generate reports at month-end for review

- Compare month-over-month to identify changes

### Action on Recommendations

- Prioritize recommendations by potential impact

- Set specific, measurable goals based on insights

- Track progress by re-running analysis regularly

## Dependencies

All scripts require Python 3.7+ with standard libraries. Additional requirements:

**For PDF extraction:**

```
pip install pdfplumber --break-system-packages

```

**For data analysis:**

```
pip install pandas --break-system-packages

```

All visualization dependencies are loaded from CDN in the HTML output (Chart.js).

## File Organization

```
finance-manager/
├── scripts/
│   ├── extract_pdf_data.py     # PDF → CSV conversion
│   ├── analyze_finances.py     # Financial analysis engine
│   └── generate_report.py      # HTML report generator
└── references/
    └── financial_frameworks.md # Detailed analysis methodologies

```

## Customization

### Adding Custom Categories

Edit the category definitions in `analyze_finances.py` to match your tracking system.

### Adjusting Thresholds

Modify recommendation thresholds in the `generate_budget_recommendations()` function to match personal goals.

### Styling Reports

Customize the HTML_TEMPLATE in `generate_report.py` to adjust colors, fonts, or layout.

## Common Use Cases

**Monthly Review:**
"Analyze my October spending and create a report"

**Budget Optimization:**

"Where am I spending too much money?"

**Trend Analysis:**
"How does my spending this month compare to last month?"

**Goal Setting:**
"What's my savings rate and how can I improve it?"

**Category Insights:**
"Break down my food spending by transaction"

**PDF Processing:**
"Extract all transactions from my bank statement PDF"

## Best Practices

- **Consistent Categorization**: Use the same category names across all transactions

- **Regular Analysis**: Run monthly to spot trends early

- **Act on Insights**: Use recommendations to make specific spending changes

- **Track Progress**: Compare reports month-over-month

- **Verify Data**: Always check extracted PDF data for accuracy before analysis

## Reference Materials

For comprehensive financial frameworks, budgeting guidelines, and analysis methodologies, read:

```
view references/financial_frameworks.md

```

This includes:

- The 50/30/20 budget rule

- Category spending benchmarks

- Financial health indicators

- Analysis workflow details

- Visualization best practices

- Recommendation logic

Weekly Installs481Repository[ailabs-393/ai-l…e-skills](https://github.com/ailabs-393/ai-labs-claude-skills)GitHub Stars329First SeenJan 23, 2026Security Audits[Gen Agent Trust HubPass](/ailabs-393/ai-labs-claude-skills/finance-manager/security/agent-trust-hub)[SocketPass](/ailabs-393/ai-labs-claude-skills/finance-manager/security/socket)[SnykWarn](/ailabs-393/ai-labs-claude-skills/finance-manager/security/snyk)Installed onopencode397gemini-cli373codex373github-copilot354cursor348kimi-cli324

---
*Source: https://skills.yangsir.net/skill/sm-finance-manager*
*Markdown mirror: https://skills.yangsir.net/api/skill/sm-finance-manager/markdown*