Skill 详情
data-analysis
General spreadsheet and CSV analysis, statistics, visualization, and reporting.
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SKILL.md
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# ═══════════════════════════════════════════════════════════════════════════════
# CLAUDE OFFICE SKILL - Enhanced Metadata v2.0
# ═══════════════════════════════════════════════════════════════════════════════
# Basic Information
name: data-analysis
description: "Analyze spreadsheet data, generate insights, create visualizations, and build reports from Excel/CSV data."
version: "1.0.0"
author: claude-office-skills
license: MIT
# Categorization
category: finance
tags:
- data
- analysis
- spreadsheet
- excel
- visualization
- insights
department: All
# AI Model Compatibility
models:
recommended:
- claude-sonnet-4
- claude-opus-4
compatible:
- claude-3-5-sonnet
- gpt-4
- gpt-4o
# MCP Tools Integration
mcp:
server: office-mcp
tools:
- read_xlsx
- analyze_spreadsheet
- create_chart
- pivot_table
optional_tools:
- create_xlsx
- xlsx_to_json
# Skill Capabilities
capabilities:
- data_analysis
- statistical_analysis
- visualization
- trend_detection
- reporting
# Input/Output Specification
input:
required:
- type: file
formats: [xlsx, csv, xls]
description: The spreadsheet data to analyze
optional:
- type: text
name: analysis_goal
description: Specific questions or analysis goals
- type: text
name: output_format
description: Preferred output format (report, chart, summary)
output:
primary:
type: report
format: markdown
sections:
- data_overview
- key_insights
- visualizations
- recommendations
# Language Support
languages:
- en
- zh
# Related Skills
related_skills:
- excel-automation
- report-generator
- xlsx-manipulation
---
# Data Analysis Assistant
Analyze data in spreadsheets, uncover insights, and create compelling visualizations.
## Overview
This skill helps you:
- Understand and explore your data
- Perform statistical analysis
- Generate insights and recommendations
- Create charts and visualizations
- Write formulas and queries
## How to Use
### Getting Started
1. Share your spreadsheet or data file
2. Describe what you want to analyze
3. Get insights, formulas, or visualizations
### Analysis Types
**Exploratory Analysis**
```
"What patterns do you see in this data?"
"Give me an overview of this dataset"
"What are the key statistics?"
```
**Specific Questions**
```
"What was the total revenue by region?"
"Which products had the highest growth?"
"Is there a correlation between X and Y?"
```
**Visualization Requests**
```
"Create a chart showing sales trends"
"Make a comparison chart of Q1 vs Q2"
"Show the distribution of customer ages"
```
## Output Formats
### Data Overview
```markdown
## Dataset Overview
**Rows**: 1,234
**Columns**: 15
**Date Range**: Jan 2025 - Dec 2025
### Column Summary
| Column | Type | Non-null | Unique | Sample Values |
|--------|------|----------|--------|---------------|
| date | Date | 100% | 365 | 2025-01-01 |
| revenue | Number | 98% | 890 | $1,234.56 |
| region | Text | 100% | 5 | North, South |
### Data Quality Issues
- [X] rows have missing values in [column]
- [Y] potential duplicates detected
```
### Statistical Analysis
```markdown
## Statistical Summary
### [Metric Name]
- **Mean**: X
- **Median**: Y
- **Std Dev**: Z
- **Min/Max**: A / B
### Key Findings
1. [Finding with statistical support]
2. [Finding with statistical support]
### Recommendations
- [Action based on analysis]
```
### Insight Report
```markdown
## Analysis Report: [Topic]
### Executive Summary
[2-3 sentence overview of key findings]
### Key Metrics
| Metric | Value | Change |
|--------|-------|--------|
| Total Revenue | $X | +Y% |
| Avg Order Value | $Z | -W% |
### Trends
1. **[Trend 1]**: [Description with data]
2. **[Trend 2]**: [Description with data]
### Recommendations
1. [Actionable recommendation]
2. [Actionable recommendation]
```
## Common Analysis Workflows
### Sales Analysis
```
1. "Show total sales by在 GitHub 阅读完整来源 (打开外部页面)