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 Jignesh-Ponamwar/skills-mcp --skill xlsx-creatorgit clone --depth 1 https://github.com/Jignesh-Ponamwar/skills-mcpWrote 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/jignesh-ponamwar/skills-mcp/xlsx-creator)<a href="https://agentmods.dev/skills/jignesh-ponamwar/skills-mcp/xlsx-creator"><img src="https://agentmods.dev/badge/skills/jignesh-ponamwar/skills-mcp/xlsx-creator/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/jignesh-ponamwar/skills-mcp/xlsx-creator"><img src="https://agentmods.dev/badge/skills/jignesh-ponamwar/skills-mcp/xlsx-creator.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 | $0.00089 | $0.02231 |
| Opus 5 | $0.00044 | $0.01115 |
| Sonnet 5 | $0.00018 | $0.00446 |
| Haiku 4.5 | $0.00009 | $0.00223 |
Grade A, and why
xlsx-creator 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 11d 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 — 241 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Excel Spreadsheet Skill (XLSX)
Professional Standards
- Zero formula errors - no #REF!, #DIV/0!, #VALUE!, #N/A, or #NAME? errors allowed
- Always use formulas instead of calculating values in Python and hardcoding them - spreadsheets must remain dynamic
- Consistent fonts throughout - pick one font family (Calibri 11 or Aptos 11 for Excel defaults)
- Document hardcoded values with comments including source, date, and reference URL
Tool Selection
| Use Case | Tool |
|---|---|
| Data analysis, bulk operations, DataFrame export | pandas |
| Complex formatting, formulas, cell styling | openpyxl |
| Both formatting AND data manipulation | Use pandas to build data, openpyxl to format |
Step 1: Setup
pip install openpyxl pandas xlsxwriter
Step 2: Create a Spreadsheet with openpyxl
from openpyxl import Workbook
from openpyxl.styles import Font, PatternFill, Alignment, Border, Side, numbers
from openpyxl.utils import get_column_letter
from openpyxl.chart import BarChart, Reference
wb = Workbook()
ws = wb.active
ws.title = "Revenue Model"
# ─── STYLING HELPERS ─────────────────────────────────────────────────────────
HEADER_FONT = Font(name="Calibri", bold=True, size=11, color="FFFFFF")
HEADER_FILL = PatternFill(fill_type="solid", fgColor="1F4E79") # dark blue
INPUT_FILL = PatternFill(fill_type="solid", fgColor="DDEEFF") # light blue (inputs)
FORMULA_FILL = PatternFill(fill_type="solid", fgColor="FFFFFF") # white (formulas)
ASSUMPTION_FILL = PatternFill(fill_type="solid", fgColor="FFFF99") # yellow (key assumptions)
thin = Side(style="thin", color="000000")
BORDER = Border(left=thin, right=thin, top=thin, bottom=thin)
def style_header(cell):
cell.font = HEADER_FONT
cell.fill = HEADER_FILL
cell.alignment = Alignment(horizontal="center", vertical="center")
cell.border = BORDER
def style_input(cell):
cell.fill = INPUT_FILL # blue = hardcoded input (industry standard)
cell.border = BORDER
def style_formula(cell):
cell.fill = FORMULA_FILL # white/black = formula
cell.border = BORDER
# ─── HEADERS ─────────────────────────────────────────────────────────────────
headers = ["Month", "Units Sold", "Unit Price ($)", "Revenue ($)", "COGS ($)", "Gross Profit ($)"]
for col, h in enumerate(headers, start=1):
cell = ws.cell(row=1, column=col, value=h)
style_header(cell)
ws.column_dimensions[get_column_letter(col)].width = max(len(h) + 2, 14)
# ─── INPUT DATA ──────────────────────────────────────────────────────────────
months = ["Jan", "Feb", "Mar", "Apr", "May", "Jun"]
units = [1200, 1350, 1280, 1500, 1420, 1650]
price = 29.99
cogs_pct = 0.40 # key assumption - put in assumption row
for i, (month, unit) in enumerate(zip(months, units), start=2):
row = i
# Month
ws.cell(row=row, column=1, value=month)
# Units (input - blue)
cell_units = ws.cell(row=row, column=2, value=unit)
style_input(cell_units)
# Unit Price (input - blue)
cell_price = ws.cell(row=row, column=3, value=price)
cell_price.number_format = '"$"#,##0.00'
style_input(cell_price)
# Revenue (formula - always use formula, not Python calculation)
cell_rev = ws.cell(row=row, column=4, value=f"=B{row}*C{row}")
cell_rev.number_format = '"$"#,##0.00'
style_formula(cell_rev)
# COGS (formula referencing assumption)
# Assume COGS % is in cell H2
cell_cogs = ws.cell(row=row, column=5, value=f"=D{row}*$H$2")
cell_cogs.number_format = '"$"#,##0.00'
style_formula(cell_cogs)
# Gross Profit (formula)
cell_gp = ws.cell(row=row, column=6, value=f"=D{row}-E{row}")
cell_gp.number_format = '"$"#,##0.00'
style_formula(cell_gp)
# ─── ASSUMPTIONS BOX ─────────────────────────────────────────────────────────
# Yellow = key assumptions
ws["G1"] = "Key Assumptions"
ws["G1"].font = Font(bold=True)
ws["G2"] = "COGS % of Revenue"
ws["H2"] = cogs_pct
ws["H2"].number_format = "0%"
ws["H2"].comment = "Source: Management estimate, April 2026"
cell_h2 = ws["H2"]
cell_h2.fill = ASSUMPTION_FILL # yellow = key assumption
# ─── TOTALS ROW ──────────────────────────────────────────────────────────────
total_row = len(months) + 2
ws.cell(row=total_row, column=1, value="TOTAL")
ws.cell(row=total_row, column=1).font = Font(bold=True)
for col in range(2, 7):
col_letter = get_column_letter(col)
formula = f"=SUM({col_letter}2:{col_letter}{total_row-1})"
cell = ws.cell(row=total_row, column=col, value=formula)
if col >= 4:
cell.number_format = '"$"#,##0.00'
cell.font = Font(bold=True)
cell.border = BORDER
# ─── CHART ───────────────────────────────────────────────────────────────────
chart = BarChart()
chart.title = "Monthly Revenue"
chart.style = 10
chart.y_axis.title = "Revenue ($)"
chart.x_axis.title = "Month"
data = Reference(ws, min_col=4, min_row=1, max_row=len(months) + 1)
categories = Reference(ws, min_col=1, min_row=2, max_row=len(months) + 1)
chart.add_data(data, titles_from_data=True)
chart.set_categories(categories)
chart.shape = 4
ws.add_chart(chart, "A10")
# ─── SAVE ────────────────────────────────────────────────────────────────────
wb.save("revenue-model.xlsx")
print("Saved: revenue-model.xlsx")
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.
- 11d ago First seen · 241 lines · 89 tokens per session scan A 0cc3c5301776
xlsx-creator is a skill published in the GitHub repository Jignesh-Ponamwar/skills-mcp (7 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 89 tokens to every session and 2,231 once invoked, about $0.0004 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 2026-08-31.
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