excel-analysis

Excel Analysis Skill

This skill enables AI agents to perform data analysis on Excel files using statistical operations, filtering, and grouping.

When to Use

Use this skill when the user wants to:

• Get statistical summaries of data
• Filter rows based on conditions
• Group data by columns and aggregate
• Identify patterns or anomalies
• Generate insights from spreadsheets

Prerequisites

• MCP Excel Server must be running
• Data must be in tabular format with headers
• File path must be absolute

Analysis Strategies

1. Column Statistics

Use get_column_stats for statistical summaries:

Tool: get_column_stats
Parameters:
  file_path: "absolute/path/to/file.xlsx"
  sheet_name: "Sheet1"
  column: "B"

Returns:

• Count, sum, mean, median
• Min, max, range
• Standard deviation, variance
• Null count
• Data type information

2. Filtering Rows

Use filter_rows to subset data:

Tool: filter_rows
Parameters:
  file_path: "absolute/path/to/file.xlsx"
  sheet_name: "Sheet1"
  filters: [
    {"column": "B", "operator": ">", "value": 100},
    {"column": "C", "operator": "==", "value": "Active"}
  ]
  logic: "AND"

Operators:

• Comparison: ==, !=, >, <, >=, <=
• Text: contains, startswith, endswith
• Set: in, not_in
• Null: is_null, is_not_null

3. Grouping and Aggregation

Use group_by for pivot-like analysis:

Tool: group_by
Parameters:
  file_path: "absolute/path/to/file.xlsx"
  sheet_name: "Sheet1"
  columns: ["Category", "Region"]
  agg_column: "Sales"
  agg_func: "sum"

Aggregation Functions:

• sum - Total
• mean - Average
• median - Middle value
• count - Count of rows
• min - Minimum
• max - Maximum
• std - Standard deviation

Common Workflows

Workflow 1: Data Exploration

1. Call get_sheet_info to understand structure
2. Call read_range to examine sample data
3. Call get_column_stats for each important column
4. Identify key patterns and insights