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 skills add waterfeet/DoroPet_V3 --skill excel-xlsxgit clone --depth 1 https://github.com/waterfeet/DoroPet_V3Wrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/waterfeet/doropet_v3/excel-xlsx)<a href="https://agentmods.dev/skills/waterfeet/doropet_v3/excel-xlsx"><img src="https://agentmods.dev/badge/skills/waterfeet/doropet_v3/excel-xlsx/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/waterfeet/doropet_v3/excel-xlsx"><img src="https://agentmods.dev/badge/skills/waterfeet/doropet_v3/excel-xlsx.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00090 | $0.01457 |
| Opus 5.5 | $0.00036 | $0.00583 |
| Sonnet 5.5 | $0.00018 | $0.00291 |
| Haiku 4.5 | $0.00009 | $0.00146 |
Grade A, and why
Excel / XLSX 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 2mo 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 — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When to Use
Use when the main artifact is a Microsoft Excel workbook or spreadsheet file, especially when formulas, dates, formatting, merged cells, workbook structure, or cross-platform behavior matter.
Core Rules
1. Choose the workflow by job, not by habit
- Use
pandasfor analysis, reshaping, and CSV-like tasks. - Use
openpyxlwhen formulas, styles, sheets, comments, merged cells, or workbook preservation matter. - Treat CSV as plain data exchange, not as an Excel feature-complete format.
- Reading values, preserving a live workbook, and building a model from scratch are different spreadsheet jobs.
2. Dates are serial numbers with legacy quirks
- Excel stores dates as serial numbers, not real date objects.
- The 1900 date system includes the false leap-day bug, and some workbooks use the 1904 system.
- Time is fractional day data, so formatting and conversion both matter.
- Date correctness is not enough if the number format still displays the wrong thing to the user.
3. Keep calculations in Excel when the workbook should stay live
- Write formulas into cells instead of hardcoding derived results from Python.
- Use references to assumption cells instead of magic numbers inside formulas.
- Cached formula values can be stale, so do not trust them blindly after edits.
- Check copied formulas for wrong ranges, wrong sheets, and silent off-by-one drift before delivery.
- Absolute and relative references are part of the logic, so copied formulas can be wrong even when they still "work".
- Test new formulas on a few representative cells before filling them across a whole block.
- Verify denominators, named ranges, and precedent cells before shipping formulas that depend on them.
- A workbook should ship with zero formula errors, not with known
#REF!,#DIV/0!,#VALUE!,#NAME?, or circular-reference fallout left for the user to fix. - For model-style work, document non-obvious hardcodes, assumptions, or source inputs in comments or nearby notes.
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.
- 2mo ago First seen · 104 lines · 90 tokens per session scan A 52421d9fba8f
Excel / XLSX is a skill published in the GitHub repository waterfeet/DoroPet_V3 (30 stars, last pushed 3d ago), licensed Apache-2.0. It adds 90 tokens to every session and 1,457 once invoked, about $0.0004 per session on Opus 5.5. 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.
Other skills, from other repositories
xberg-extracting-tables
Use when extracting tabular data from PDFs, spreadsheets, or images. Covers layout-aware table detection, table model selection, output formats (markdown / JSON cells), and known limits.
batch_rename_by_excel
A Python utility that renames first-level files in a folder using an old-name to new-name mapping stored in an Excel spreadsheet. It can also produce a dry-run plan without changing files.
excel2csv
A spreadsheet conversion tool that exports one or more Excel worksheets as CSV files, a plain-text table format. It can use UTF-8 with a marker that helps Excel display Chinese correctly.
excel2json
An Excel conversion tool that turns worksheet data into JSON, a structured text format commonly used by programs and web APIs. It supports row-based, column-based, and two-dimensional output, and converts dates to a standard text form.
excel_column_stats
An Excel worksheet profiling tool that reports missing values, data types, distinct-value counts, and numeric distributions for each column. A data profile is a quick summary used to inspect a dataset before processing it.
excel_dedupe
An Excel deduplication tool that identifies repeated rows using selected columns or the whole row. It reports which row was kept and which rows matched it, and can write a cleaned workbook.