Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/aidotnet/opencowork/excel-processornpx skills add AIDotNet/OpenCowork --skill excel-processorgit clone --depth 1 https://github.com/AIDotNet/OpenCoworkWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00055 | $0.01044 |
| Opus 5 | $0.00028 | $0.00522 |
| Sonnet 5 | $0.00011 | $0.00209 |
| Haiku 4.5 | $0.00006 | $0.00104 |
Grade A, and why
excel-processor scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Excel Processor
Read, write, analyze, and format Excel spreadsheets (.xlsx) using Python.
When to use this skill
- User asks to create an Excel spreadsheet
- User wants to read or extract data from an .xlsx file
- User needs to add formulas, formatting, or charts to a spreadsheet
- User wants to convert CSV/JSON data into a formatted Excel file
- User needs Excel report generation with multiple sheets
Scripts overview
| Script | Purpose | Dependencies |
|---|---|---|
excel_tool.py |
Read, write, format, and analyze Excel files | openpyxl |
Steps
1. Install dependencies (first time only)
pip install openpyxl
CRITICAL — Dependency Error Recovery: If the script fails with an
ImportError, install the missing dependency using the command above, then re-run the EXACT SAME script command that failed.
2. Read an Excel file
python scripts/excel_tool.py read "INPUT.xlsx"
Options:
--sheet SHEET_NAME— Read a specific sheet (default: active sheet)--format json— Output as JSON instead of table--format csv— Output as CSV--save OUTPUT_PATH— Save output to file
3. Create a new Excel file from CSV
python scripts/excel_tool.py create "OUTPUT.xlsx" --from-csv "DATA.csv"
Options:
--from-csv PATH— Import data from CSV file--from-json PATH— Import data from JSON file--sheet SHEET_NAME— Set the sheet name (default: Sheet1)--title TITLE— Add a title row with merged cells--auto-width— Auto-adjust column widths to fit content--header-style— Apply bold + colored header row
4. Add a sheet to existing workbook
python scripts/excel_tool.py add-sheet "EXISTING.xlsx" --sheet "NewSheet" --from-csv "DATA.csv"
5. Apply formatting
python scripts/excel_tool.py format "FILE.xlsx" --auto-width --header-style --freeze-header
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 124 lines · 55 tokens per session scan A 2d8e51437cbc
excel-processor is a skill published in the GitHub repository AIDotNet/OpenCowork (632 stars, last pushed 4d ago), licensed Apache-2.0. It adds 55 tokens to every session and 1,044 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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