open-claw-team/.openclaw/workspace/skills/excel-operations/SKILL.md

name, description

name	description
excel-operations	Read, write, and manipulate Excel (.xlsx) and CSV files

When to use

Use when the user asks to:

• Read data from Excel or CSV files
• Create new spreadsheets
• Update existing spreadsheet data
• Perform calculations or data transformations
• Export data to CSV/Excel format
• Validate spreadsheet structure

Workflow

1. Identify the file

Determine file path and format (.xlsx, .csv, .tsv).

2. Read the data

OpenClaw's read is for text files. For Excel/CSV:

For CSV (plain text):

read path/to/data.csv

For .xlsx (binary): Use Python or other tools:

python -c "
import pandas as pd, json, sys;
df = pd.read_excel('data.xlsx');
print(df.to_json(orient='records'))
"

Or install xlsx2csv and convert first:

xlsx2csv data.xlsx temp.csv
read temp.csv

3. Process the data

• Parse into structured format (list of objects, 2D array)
• Validate headers/columns if needed
• Perform transformations (filter, map, aggregate)

4. Write results

For CSV:

write output.csv --data "$csv_string"

For .xlsx: Use Python:

python -c "
import pandas as pd, json, sys;
data = json.loads(sys.argv[1]);
pd.DataFrame(data).to_excel('output.xlsx', index=False)
" "$structured_data"

Supported Formats

• .xlsx (Excel Open XML) — full support for sheets, formulas, formatting
• .csv (Comma-separated) — plain text, delimiter detection
• .tsv (Tab-separated) — tab delimiter

Common Operations

Read specific sheet

read file.xlsx --sheet "Sheet2"

Read with range

read file.xlsx --range "A1:D100"

Write with formatting

write report.xlsx \
  --data "$table" \
  --header true \
  --autofit columns

Append to existing file

write file.xlsx --data "$new_rows" --append true

Data Structures

Reading returns:

{
  "headers": ["Name", "Email", "Score"],
  "rows": [
    {"Name": "Alice", "Email": "a@example.com", "Score": 95},
    ...
  ]
}

Writing accepts:

• JSON array of objects
• 2D array (array of arrays)
• CSV string (if format=csv)

Examples

User: "Tạo báo cáo điểm từ scores.csv" Assistant: 1. Đọc scores.csv 2. Tính toán điểm trung bình, xếp loại 3. Ghi vào report.xlsx với định dạng đẹp 4. Trả về đường dẫn file và tóm tắt kết quả Ghi đè file gốc mà không backup, không thông báo.

Error Handling

• File not found: Kiểm tra đường dẫn, dùng glob để tìm
• Format mismatch: Đảm bảo file đúng định dạng, kiểm tra extension
• Large files: Có thể cần chunk processing, kiểm tra memory limits
• Corrupted data: Catch parse errors, report specific row/column

Validation Checklist

• File exists and is readable
• Format matches extension
• Headers are present and correct
• Data types are correct (numbers, dates, strings)
• No missing values in required columns
• Output file is well-formed and complete