XLSX
Read, inspect, edit, or create Microsoft Excel `.xlsx` workbooks, including structured...
Install
npx skills add TokenRhythm/opensquilla --skill xlsx -g -a claude-code -y- Repository
- TokenRhythm/opensquilla7.1k
- Category
- Documents
- Updated
- 3d ago
- License
- Apache-2.0
- Context cost
- Lightabout 1,366 tokens
- Runs scripts
- Yes, review before use
What it does
Read, inspect, edit, or create Microsoft Excel `.xlsx` workbooks, including structured data extraction, formula-aware cell edits, and workbook generation from rows.
xlsx
Work with .xlsx workbooks. The format is OOXML SpreadsheetML, a zip
container of XML parts. Treat each cell as a typed value: a number, a string,
a datetime, or a formula. Mixing the four causes Excel to flag the workbook
or compute incorrect totals.
Decide the path first
| You have | Goal | Path |
|---|---|---|
Existing .xlsx | Read sheets and cells | A. Inspect |
Existing .xlsx | Modify specific cells | B. Edit-in-place |
| Nothing or a brief | Build a new workbook | C. Create from scratch |
If the user provides a workbook to update, default to path B and treat the input as the formatting baseline. Choose path C only when the user says "start fresh".
Execution and delivery
Use execute_code with the Python examples below when it is available. Keep
all input and output files in the active workspace, then call
publish_artifact(path="out.xlsx") to deliver the finished workbook.
In a restricted channel, use openpyxl directly; the shell commands below
are optional shortcuts for sessions that expose exec_command. Do not use
Python subprocesses to bypass an unavailable shell tool or request host
execution when the sandbox fails. If execution or a required library is
unavailable, report that limitation and keep the session read-only.
Path A: Inspect
With execute_code:
from openpyxl import load_workbook
wb = load_workbook("book.xlsx", data_only=False)
for ws in wb.worksheets:
print(ws.title, list(ws.values))
wb.close()
python {baseDir}/scripts/inspect_xlsx.py /path/to/book.xlsx
Output:
{
"sheets": [
{
"name": "Q3",
"max_row": 10,
"max_col": 5,
"rows": [
[
{"value": "Metric", "type": "s"},
{"value": "Value", "type": "s"}
],
[
{"value": "Revenue", "type": "s"},
{"value": 2100000, "type": "n"}
]
]
}
]
}


