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 cxcscmu/SkillLearnBench --skill excel-openpyxl-formulasgit clone --depth 1 https://github.com/cxcscmu/SkillLearnBenchWrote 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/cxcscmu/skilllearnbench/excel-openpyxl-formulas)<a href="https://agentmods.dev/skills/cxcscmu/skilllearnbench/excel-openpyxl-formulas"><img src="https://agentmods.dev/badge/skills/cxcscmu/skilllearnbench/excel-openpyxl-formulas/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/cxcscmu/skilllearnbench/excel-openpyxl-formulas"><img src="https://agentmods.dev/badge/skills/cxcscmu/skilllearnbench/excel-openpyxl-formulas.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00030 | $0.00928 |
| Opus 5.5 | $0.00012 | $0.00371 |
| Sonnet 5.5 | $0.00006 | $0.00186 |
| Haiku 4.5 | $0.00003 | $0.00093 |
Grade A, and why
excel-openpyxl-formulas scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
openpyxl: Insert Formulas While Preserving Formatting
Critical Rule: Load Without data_only
from openpyxl import load_workbook
# CORRECT: preserves formulas and formatting
wb = load_workbook('file.xlsx')
# WRONG: replaces formulas with cached values on save
wb = load_workbook('file.xlsx', data_only=True)
Basic Formula Insertion
wb = load_workbook('file.xlsx')
ws = wb['Sheet1']
ws['H12'] = '=INDEX(Data!$H$21:$M$40,MATCH($D12,Data!$B$21:$B$40,0),MATCH(H$10,Data!$H$4:$M$4,0))'
wb.save('file.xlsx')
Iterating Over Cell Ranges
When applying similar formulas to a grid of cells, iterate using row/column indices:
from openpyxl.utils import get_column_letter
# Fill a range (e.g., H12:L17) with formulas
start_row = 12
end_row = 17
start_col = 8 # H = column 8
end_col = 12 # L = column 12
for row in range(start_row, end_row + 1):
for col in range(start_col, end_col + 1):
col_letter = get_column_letter(col)
cell = ws.cell(row=row, column=col)
cell.value = f'=INDEX(Data!$I$21:$M$40,MATCH($D{row},Data!$B$21:$B$40,0),MATCH({col_letter}$10,Data!$I$4:$M$4,0))'
Preserving Cell Formatting
openpyxl preserves existing cell styles when you only change value. Setting a new value does NOT erase fill color, font, borders, etc.:
cell = ws['H12']
cell.value = '=SUM(A1:A10)' # Only changes the value; style is preserved
Row and Column Reference Conversion
from openpyxl.utils import get_column_letter, column_index_from_string
get_column_letter(8) # → 'H'
get_column_letter(12) # → 'L'
column_index_from_string('H') # → 8
column_index_from_string('L') # → 12
Recalculating Formulas After Editing
After saving, run recalc.py to update cached formula values:
python recalc.py file.xlsx
Check output for errors:
{"status": "success", "total_errors": 0, "total_formulas": 42}
If errors found:
{"status": "errors_found", "error_summary": {"#REF!": {"count": 2, "locations": ["Task!H12"]}}}
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.
- 1mo ago First seen · 115 lines · 30 tokens per session scan A 99b72549969c
excel-openpyxl-formulas is a skill published in the GitHub repository cxcscmu/SkillLearnBench (91 stars, last pushed 19d ago), licensed MIT. It adds 30 tokens to every session and 928 once invoked, about $0.0001 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 2026-09-03.
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