[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M7BVMWPR2M5P354QSMRYZPVZ":3,"skill-same:01M7BVMWPR2M5P354QSMRYZPVZ":119},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":19,"linkOnly":20,"markdownContent":21,"markdownBody":22,"frontMatter":23,"refName":91,"commitSha":92,"skillDirectory":93,"forksCount":94,"repositoryHtmlUrl":95,"repositoryHomepageUrl":6,"ownerHtmlUrl":96,"ownerBlogUrl":6,"ownerDescription":97,"updatedAt":98,"install":99,"resources":112},"01M7BVMWPR2M5P354QSMRYZPVZ","data-analysis",null,"Analyze spreadsheet data, generate insights, create visualizations, and build reports from Excel\u002FCSV data.","om-scogo\u002Fskillsh-scraper","om-scogo","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F160466840?v=4","01M79AWB6DFVCQ7RK70CS34B96","Om Achrekar","01M79AWB6ZM9SKR8KDH1WSSM22",0,"MIT","https:\u002F\u002Fgithub.com\u002Fom-scogo\u002Fskillsh-scraper\u002Fblob\u002Fmain\u002Fdata\u002Fskills\u002Fclaude-office-skills-skills\u002Fdata-analysis\u002FSkill.md",[],[],"2026-11-15 14:19:17",false,"---\n# ═══════════════════════════════════════════════════════════════════════════════\n# CLAUDE OFFICE SKILL - Enhanced Metadata v2.0\n# ═══════════════════════════════════════════════════════════════════════════════\n\n# Basic Information\nname: data-analysis\ndescription: \"Analyze spreadsheet data, generate insights, create visualizations, and build reports from Excel\u002FCSV data.\"\nversion: \"1.0.0\"\nauthor: claude-office-skills\nlicense: MIT\n\n# Categorization\ncategory: finance\ntags:\n  - data\n  - analysis\n  - spreadsheet\n  - excel\n  - visualization\n  - insights\ndepartment: All\n\n# AI Model Compatibility\nmodels:\n  recommended:\n    - claude-sonnet-4\n    - claude-opus-4\n  compatible:\n    - claude-3-5-sonnet\n    - gpt-4\n    - gpt-4o\n\n# MCP Tools Integration\nmcp:\n  server: office-mcp\n  tools:\n    - read_xlsx\n    - analyze_spreadsheet\n    - create_chart\n    - pivot_table\n  optional_tools:\n    - create_xlsx\n    - xlsx_to_json\n\n# Skill Capabilities\ncapabilities:\n  - data_analysis\n  - statistical_analysis\n  - visualization\n  - trend_detection\n  - reporting\n\n# Input\u002FOutput Specification\ninput:\n  required:\n    - type: file\n      formats: [xlsx, csv, xls]\n      description: The spreadsheet data to analyze\n  optional:\n    - type: text\n      name: analysis_goal\n      description: Specific questions or analysis goals\n    - type: text\n      name: output_format\n      description: Preferred output format (report, chart, summary)\n\noutput:\n  primary:\n    type: report\n    format: markdown\n    sections:\n      - data_overview\n      - key_insights\n      - visualizations\n      - recommendations\n\n# Language Support\nlanguages:\n  - en\n  - zh\n\n# Related Skills\nrelated_skills:\n  - excel-automation\n  - report-generator\n  - xlsx-manipulation\n---\n\n# Data Analysis Assistant\n\nAnalyze data in spreadsheets, uncover insights, and create compelling visualizations.\n\n## Overview\n\nThis skill helps you:\n- Understand and explore your data\n- Perform statistical analysis\n- Generate insights and recommendations\n- Create charts and visualizations\n- Write formulas and queries\n\n## How to Use\n\n### Getting Started\n1. Share your spreadsheet or data file\n2. Describe what you want to analyze\n3. Get insights, formulas, or visualizations\n\n### Analysis Types\n\n**Exploratory Analysis**\n```\n\"What patterns do you see in this data?\"\n\"Give me an overview of this dataset\"\n\"What are the key statistics?\"\n```\n\n**Specific Questions**\n```\n\"What was the total revenue by region?\"\n\"Which products had the highest growth?\"\n\"Is there a correlation between X and Y?\"\n```\n\n**Visualization Requests**\n```\n\"Create a chart showing sales trends\"\n\"Make a comparison chart of Q1 vs Q2\"\n\"Show the distribution of customer ages\"\n```\n\n## Output Formats\n\n### Data Overview\n```markdown\n## Dataset Overview\n\n**Rows**: 1,234\n**Columns**: 15\n**Date Range**: Jan 2025 - Dec 2025\n\n### Column Summary\n| Column | Type | Non-null | Unique | Sample Values |\n|--------|------|----------|--------|---------------|\n| date | Date | 100% | 365 | 2025-01-01 |\n| revenue | Number | 98% | 890 | $1,234.56 |\n| region | Text | 100% | 5 | North, South |\n\n### Data Quality Issues\n- [X] rows have missing values in [column]\n- [Y] potential duplicates detected\n```\n\n### Statistical Analysis\n```markdown\n## Statistical Summary\n\n### [Metric Name]\n- **Mean**: X\n- **Median**: Y\n- **Std Dev**: Z\n- **Min\u002FMax**: A \u002F B\n\n### Key Findings\n1. [Finding with statistical support]\n2. [Finding with statistical support]\n\n### Recommendations\n- [Action based on analysis]\n```\n\n### Insight Report\n```markdown\n## Analysis Report: [Topic]\n\n### Executive Summary\n[2-3 sentence overview of key findings]\n\n### Key Metrics\n| Metric | Value | Change |\n|--------|-------|--------|\n| Total Revenue | $X | +Y% |\n| Avg Order Value | $Z | -W% |\n\n### Trends\n1. **[Trend 1]**: [Description with data]\n2. **[Trend 2]**: [Description with data]\n\n### Recommendations\n1. [Actionable recommendation]\n2. [Actionable recommendation]\n```\n\n## Common Analysis Workflows\n\n### Sales Analysis\n```\n1. \"Show total sales by month\"\n2. \"Which products are top performers?\"\n3. \"What's the customer segment breakdown?\"\n4. \"Compare this year vs last year\"\n5. \"Forecast next quarter based on trends\"\n```\n\n### Customer Analysis\n```\n1. \"What's the customer distribution by segment?\"\n2. \"Calculate customer lifetime value\"\n3. \"Which customers are at risk of churning?\"\n4. \"What's the acquisition cost vs LTV ratio?\"\n```\n\n### Financial Analysis\n```\n1. \"Calculate profit margins by product\"\n2. \"What's the expense breakdown?\"\n3. \"Show cash flow trends\"\n4. \"Compare budget vs actual\"\n```\n\n## Formula Generation\n\n### Request Formulas\n```\n\"Write a formula to calculate year-over-year growth\"\n\"Create a VLOOKUP to match customer data\"\n\"Make a dynamic sum based on criteria\"\n```\n\n### Formula Output\n```markdown\n## Formula: [Purpose]\n\n### Excel\u002FGoogle Sheets\n```excel\n=SUMIFS(Sales[Amount], Sales[Region], \"North\", Sales[Date], \">=\"&DATE(2025,1,1))\n```\n\n### Explanation\n- `SUMIFS`: Sums values meeting multiple criteria\n- First argument: Column to sum\n- Subsequent pairs: Criteria column + criteria value\n\n### Usage\nPlace in cell [X] where you want the result.\n```\n\n## Visualization Recommendations\n\n### Choose the Right Chart\n| Data Type | Best Chart |\n|-----------|------------|\n| Trends over time | Line chart |\n| Part of whole | Pie\u002FDonut chart |\n| Comparison | Bar chart |\n| Distribution | Histogram |\n| Correlation | Scatter plot |\n| Geographic | Map chart |\n\n### Chart Specifications\n```markdown\n## Recommended Chart: [Type]\n\n**Data Series**:\n- X-axis: [Column] (e.g., Date)\n- Y-axis: [Column] (e.g., Revenue)\n- Series: [Column] (e.g., Region)\n\n**Formatting**:\n- Title: \"[Descriptive title]\"\n- Colors: Use consistent color scheme\n- Labels: Show values on data points\n\n**Chart Description**:\n[What this chart shows and why it's useful]\n```\n\n## Advanced Analysis\n\n### Pivot Table Design\n```markdown\n## Pivot Table: [Purpose]\n\n**Rows**: [Field 1], [Field 2]\n**Columns**: [Field 3]\n**Values**: SUM of [Field 4], AVG of [Field 5]\n**Filters**: [Field 6]\n\nExpected Output:\n| Region | Q1 | Q2 | Q3 | Q4 | Total |\n|--------|----|----|----|----|-------|\n| North | $X | $X | $X | $X | $X |\n| South | $X | $X | $X | $X | $X |\n```\n\n### Cohort Analysis\n```markdown\n## Cohort Analysis\n\n**Cohort Definition**: Customers grouped by [first purchase month]\n**Metric**: [Retention rate \u002F Revenue \u002F etc.]\n**Time Period**: [12 months]\n\n| Cohort | M0 | M1 | M2 | M3 | ... |\n|--------|-----|-----|-----|-----|-----|\n| Jan 25 | 100%| 45% | 32% | 28% | ... |\n| Feb 25 | 100%| 48% | 35% | 30% | ... |\n```\n\n## Best Practices\n\n### For Better Analysis\n1. **Clean data first**: Handle missing values, duplicates\n2. **Define metrics clearly**: What exactly are you measuring?\n3. **Consider context**: Industry benchmarks, seasonality\n4. **Validate findings**: Cross-check with other data sources\n\n### For Better Visualizations\n1. **Keep it simple**: One main message per chart\n2. **Label clearly**: Title, axes, legend\n3. **Use appropriate scale**: Don't truncate misleadingly\n4. **Consider colorblind users**: Use patterns or distinct colors\n\n## Limitations\n\n- Cannot directly execute code on your data\n- Large datasets may need sampling\n- Complex statistical models need specialized tools\n- Real-time data requires live connections\n- Cannot guarantee 100% accuracy on OCR'd data\n","# Data Analysis Assistant\n\nAnalyze data in spreadsheets, uncover insights, and create compelling visualizations.\n\n## Overview\n\nThis skill helps you:\n- Understand and explore your data\n- Perform statistical analysis\n- Generate insights and recommendations\n- Create charts and visualizations\n- Write formulas and queries\n\n## How to Use\n\n### Getting Started\n1. Share your spreadsheet or data file\n2. Describe what you want to analyze\n3. Get insights, formulas, or visualizations\n\n### Analysis Types\n\n**Exploratory Analysis**\n```\n\"What patterns do you see in this data?\"\n\"Give me an overview of this dataset\"\n\"What are the key statistics?\"\n```\n\n**Specific Questions**\n```\n\"What was the total revenue by region?\"\n\"Which products had the highest growth?\"\n\"Is there a correlation between X and Y?\"\n```\n\n**Visualization Requests**\n```\n\"Create a chart showing sales trends\"\n\"Make a comparison chart of Q1 vs Q2\"\n\"Show the distribution of customer ages\"\n```\n\n## Output Formats\n\n### Data Overview\n```markdown\n## Dataset Overview\n\n**Rows**: 1,234\n**Columns**: 15\n**Date Range**: Jan 2025 - Dec 2025\n\n### Column Summary\n| Column | Type | Non-null | Unique | Sample Values |\n|--------|------|----------|--------|---------------|\n| date | Date | 100% | 365 | 2025-01-01 |\n| revenue | Number | 98% | 890 | $1,234.56 |\n| region | Text | 100% | 5 | North, South |\n\n### Data Quality Issues\n- [X] rows have missing values in [column]\n- [Y] potential duplicates detected\n```\n\n### Statistical Analysis\n```markdown\n## Statistical Summary\n\n### [Metric Name]\n- **Mean**: X\n- **Median**: Y\n- **Std Dev**: Z\n- **Min\u002FMax**: A \u002F B\n\n### Key Findings\n1. [Finding with statistical support]\n2. [Finding with statistical support]\n\n### Recommendations\n- [Action based on analysis]\n```\n\n### Insight Report\n```markdown\n## Analysis Report: [Topic]\n\n### Executive Summary\n[2-3 sentence overview of key findings]\n\n### Key Metrics\n| Metric | Value | Change |\n|--------|-------|--------|\n| Total Revenue | $X | +Y% |\n| Avg Order Value | $Z | -W% |\n\n### Trends\n1. **[Trend 1]**: [Description with data]\n2. **[Trend 2]**: [Description with data]\n\n### Recommendations\n1. [Actionable recommendation]\n2. [Actionable recommendation]\n```\n\n## Common Analysis Workflows\n\n### Sales Analysis\n```\n1. \"Show total sales by month\"\n2. \"Which products are top performers?\"\n3. \"What's the customer segment breakdown?\"\n4. \"Compare this year vs last year\"\n5. \"Forecast next quarter based on trends\"\n```\n\n### Customer Analysis\n```\n1. \"What's the customer distribution by segment?\"\n2. \"Calculate customer lifetime value\"\n3. \"Which customers are at risk of churning?\"\n4. \"What's the acquisition cost vs LTV ratio?\"\n```\n\n### Financial Analysis\n```\n1. \"Calculate profit margins by product\"\n2. \"What's the expense breakdown?\"\n3. \"Show cash flow trends\"\n4. \"Compare budget vs actual\"\n```\n\n## Formula Generation\n\n### Request Formulas\n```\n\"Write a formula to calculate year-over-year growth\"\n\"Create a VLOOKUP to match customer data\"\n\"Make a dynamic sum based on criteria\"\n```\n\n### Formula Output\n```markdown\n## Formula: [Purpose]\n\n### Excel\u002FGoogle Sheets\n```excel\n=SUMIFS(Sales[Amount], Sales[Region], \"North\", Sales[Date], \">=\"&DATE(2025,1,1))\n```\n\n### Explanation\n- `SUMIFS`: Sums values meeting multiple criteria\n- First argument: Column to sum\n- Subsequent pairs: Criteria column + criteria value\n\n### Usage\nPlace in cell [X] where you want the result.\n```\n\n## Visualization Recommendations\n\n### Choose the Right Chart\n| Data Type | Best Chart |\n|-----------|------------|\n| Trends over time | Line chart |\n| Part of whole | Pie\u002FDonut chart |\n| Comparison | Bar chart |\n| Distribution | Histogram |\n| Correlation | Scatter plot |\n| Geographic | Map chart |\n\n### Chart Specifications\n```markdown\n## Recommended Chart: [Type]\n\n**Data Series**:\n- X-axis: [Column] (e.g., Date)\n- Y-axis: [Column] (e.g., Revenue)\n- Series: [Column] (e.g., Region)\n\n**Formatting**:\n- Title: \"[Descriptive title]\"\n- Colors: Use consistent color scheme\n- Labels: Show values on data points\n\n**Chart Description**:\n[What this chart shows and why it's useful]\n```\n\n## Advanced Analysis\n\n### Pivot Table Design\n```markdown\n## Pivot Table: [Purpose]\n\n**Rows**: [Field 1], [Field 2]\n**Columns**: [Field 3]\n**Values**: SUM of [Field 4], AVG of [Field 5]\n**Filters**: [Field 6]\n\nExpected Output:\n| Region | Q1 | Q2 | Q3 | Q4 | Total |\n|--------|----|----|----|----|-------|\n| North | $X | $X | $X | $X | $X |\n| South | $X | $X | $X | $X | $X |\n```\n\n### Cohort Analysis\n```markdown\n## Cohort Analysis\n\n**Cohort Definition**: Customers grouped by [first purchase month]\n**Metric**: [Retention rate \u002F Revenue \u002F etc.]\n**Time Period**: [12 months]\n\n| Cohort | M0 | M1 | M2 | M3 | ... |\n|--------|-----|-----|-----|-----|-----|\n| Jan 25 | 100%| 45% | 32% | 28% | ... |\n| Feb 25 | 100%| 48% | 35% | 30% | ... |\n```\n\n## Best Practices\n\n### For Better Analysis\n1. **Clean data first**: Handle missing values, duplicates\n2. **Define metrics clearly**: What exactly 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