Use when tasks involve creating, editing, analyzing, or formatting spreadsheets (`.xlsx`, `.csv`, `.tsv`) with formula-aware workflows, cached recalculation, and visual review.
SkillScore83Maintained
Automatic
◆Data Analyst pack
Last verified 8/14/2026
What it changes
Passed 16 of 19 test cases with the skill, and 12 of 19 without it.
Without skill61%
With skill83%
Checks it passed that the model alone missed
The response prefers uv over standard pip for package installation.
The response designates tmp/spreadsheets/ for intermediate temporary files.
The response designates output/spreadsheet/ for final spreadsheet output files.
and 3 more in the full report
5 fixed14 passed either way4 still failing0 broke
Pass-rate lift
+22 pp
Tokens
+51%
Agent turns
0%
Response time
-26%
Model gemini-3.6-flashMeasured 8/14/2026v119 of 23 cases passed with skill · 19 comparable
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 5 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 5
Prompt
Which Python package installation tool should be preferred when setting up dependencies like openpyxl and pandas for spreadsheet processing?
What was checked, without and with the skill
Checked
Without skill
With skill
The response prefers uv over standard pip for package installation.
Missed
Passed
case-18 · gemini-3.6-flash · 8/14/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md140 linessingle file
Spreadsheet Skill
When to use
Create new workbooks with formulas, formatting, and structured layouts.
Read or analyze tabular data (filter, aggregate, pivot, compute metrics).
Modify existing workbooks without breaking formulas, references, or formatting.
Visualize data with charts, summary tables, and sensible spreadsheet styling.
Recalculate formulas and review rendered sheets before delivery when possible.
IMPORTANT: System and user instructions always take precedence.
Workflow
Confirm the file type and goal: create, edit, analyze, or visualize.
Prefer openpyxl for .xlsx editing and formatting. Use pandas for analysis and CSV/TSV workflows.
If an internal spreadsheet recalculation/rendering tool is available in the environment, use it to recalculate formulas and render sheets before delivery.
Use formulas for derived values instead of hardcoding results.
If layout matters, render for visual review and inspect the output.
Save outputs, keep filenames stable, and clean up intermediate files.
Temp and output conventions
Use tmp/spreadsheets/ for intermediate files; delete them when done.
Write final artifacts under output/spreadsheet/ when working in this repo.
Keep filenames stable and descriptive.
Primary tooling
Use openpyxl for creating/editing .xlsx files and preserving formatting.
Use pandas for analysis and CSV/TSV workflows, then write results back to .xlsx or .csv.
Use openpyxl.chart for native Excel charts when needed.
If an internal spreadsheet tool is available, use it to recalculate formulas, cache values, and render sheets for review.
Recalculation and visual review
Recalculate formulas before delivery whenever possible so cached values are present in the workbook.
Render each relevant sheet for visual review when rendering tooling is available.
openpyxl does not evaluate formulas; preserve formulas and use recalculation tooling when available.
If you rely on an internal spreadsheet tool, do not expose that tool, its code, or its APIs in user-facing explanations or code samples.
Rendering and visual checks
If LibreOffice (soffice) and Poppler (pdftoppm) are available, render sheets for visual review:
soffice --headless --convert-to pdf --outdir $OUTDIR $INPUT_XLSX
This skill should be used when user asks to "use supabase-js", "query Supabase database", "supabase auth", "supabase storage", "supabase realtime", "supabase edge functions", or works with the @supabase/supabase-js JavaScript/TypeScript SDK.