excel

name	excel
description	Read, analyze, and generate Excel/CSV files. Triggers: excel, spreadsheet, csv, export data, create table, .xlsx, .csv.
effort	medium
context	inline

/excel — Excel & CSV Processing

Read, analyze, and generate spreadsheet files. Always respond in the user's language.

Prerequisites

• CSV: built-in Python csv module (no deps)
• XLSX: requires pip install openpyxl

Algorithm

1. Determine Input

• $ARGUMENTS = path to file → go to step 2
• $ARGUMENTS = "create" + description → go to step 4
• $ARGUMENTS = empty → search for spreadsheets:

  Glob "**/*.{xlsx,csv,tsv}"
  

  List found files with sizes. Ask which to process.

2. Read File

Detect format and read:

# CSV (no deps)
import csv
with open("file.csv", encoding="utf-8") as f:
    reader = csv.DictReader(f)
    rows = list(reader)

# Excel (requires openpyxl)
import openpyxl
wb = openpyxl.load_workbook("file.xlsx", data_only=True)
ws = wb.active

3. Analyze and Present

Report:

• Format, sheet count (xlsx), column names
• Row count
• Data types per column
• First 10 rows as markdown table

Ask user what to do next.

4. Generate File

When creating new spreadsheet:

# CSV
import csv
with open("output.csv", "w", newline="", encoding="utf-8") as f:
    writer = csv.writer(f)
    writer.writerow(headers)
    writer.writerows(data)

# Excel
wb = openpyxl.Workbook()
ws = wb.active
ws.append(headers)
for row in data:
    ws.append(row)
wb.save("output.xlsx")

5. Suggest Next Steps

Based on content:

• Data analysis → "Generate summary statistics? Visualize?"
• Import data → "Create migration script?"
• Export request → "Which format: .xlsx, .csv, .json?"
• Task list in spreadsheet → "Import as tasks with /plan?"

Rules

• Always show column names and sample rows before processing
• Preserve data types (dates, numbers) when converting formats
• For large files (>1000 rows), show summary stats instead of all rows
• Suggest next: /pdf for PDF data, /plan for task lists, /docs for data documentation

Gotchas

• openpyxl is not in stdlib — check if installed before attempting XLSX. CSV works without deps.
• Encoding — CSV files may be in cp1251 (Russian Windows), not utf-8. Try utf-8 first, fall back to cp1251.
• Large XLSX files (>10MB) load slowly with openpyxl. Use read_only=True mode for reading.