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/smith-network-solutions/threadknot/xlsxnpx skills add smith-network-solutions/threadknot --skill xlsxgit clone --depth 1 https://github.com/smith-network-solutions/threadknotWhat 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 | $0.00084 | $0.01919 |
| Opus 5 | $0.00042 | $0.00959 |
| Sonnet 5 | $0.00017 | $0.00384 |
| Haiku 4.5 | $0.00008 | $0.00192 |
Grade A, and why
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 3d 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 — 181 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Excel workbooks (.xlsx)
openpyxl for anything that reads or edits. XlsxWriter only when writing a very large file from scratch, where it is faster and lighter but cannot read.
The single fact that causes the most wasted time:
openpyxl does not calculate. Writing
=SUM(B2:B10)stores the formula string. The cached value stays empty until a real spreadsheet application opens and recalculates the file.load_workbook(data_only=True)returnsNonefor every formula cell in a file that Excel has never opened.
So: if the user needs a workbook whose numbers are readable by other tools, run
scripts/recalc.py after writing it. If you need to read values from a file
someone sent you, data_only=True works — Excel already cached them.
Before editing a workbook, look at it
scripts/inspect_xlsx.py budget.xlsx
Prints each sheet with its dimensions, frozen panes, column widths, a preview grid, where the formulas are, merged ranges, named ranges, conditional formatting and charts. Do this first on any file you did not create — a spreadsheet's structure is rarely what the file name suggests.
scripts/inspect_xlsx.py budget.xlsx --sheet Q1 --range A1:F20 # focus
scripts/inspect_xlsx.py budget.xlsx --formulas # every formula
Creating a workbook
from openpyxl import Workbook
from openpyxl.styles import Font, Alignment, PatternFill, Border, Side
from openpyxl.utils import get_column_letter
wb = Workbook()
ws = wb.active
ws.title = "Q1" # sheet names: <=31 chars, no : \ / ? * [ ]
ws.append(["Region", "Revenue", "Cost", "Margin"])
for cell in ws[1]:
cell.font = Font(bold=True, color="FFFFFF")
cell.fill = PatternFill("solid", fgColor="1F4E79")
cell.alignment = Alignment(horizontal="center")
for row, (region, revenue, cost) in enumerate(data, start=2):
ws.cell(row=row, column=1, value=region)
ws.cell(row=row, column=2, value=revenue).number_format = '#,##0.00'
ws.cell(row=row, column=3, value=cost).number_format = '#,##0.00'
ws.cell(row=row, column=4, value=f"=B{row}-C{row}").number_format = '#,##0.00'
ws.freeze_panes = "A2" # header stays visible
ws.auto_filter.ref = ws.dimensions
ws.column_dimensions["A"].width = 18 # openpyxl does NOT auto-size columns
wb.create_sheet("Notes")
wb.save("budget.xlsx")
What ships with it
6 files 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.
- 3d ago First seen · 181 lines · 84 tokens per session scan A 34cbf50f3df1
xlsx is a skill published in the GitHub repository smith-network-solutions/threadknot (5 stars, last pushed 9d ago), licensed Apache-2.0. It adds 84 tokens to every session and 1,919 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.
Other skills, from other repositories
browser4-web-miner
Groups similar web pages together and produces an interactive HTML report with clusters of related pages, plus Excel spreadsheets for analysis. Use when the user wants to cluster downloaded HTML files, convert detail web pages into interactive views, or analyze a folder of web pages locally.
data-analysis
Profile and aggregate a bundled sales dataset - group revenue by region, category, channel or month, apply filters, and compute sums, means, medians and ranges. Use for questions about sales figures, trends, or which segments perform best.
lov-expense-report
Extract invoice data from images or text descriptions and generate a categorized Excel expense report. Supports receipt photos, scanned invoices, and manual text input. Auto-classifies into: business entertainment (客户餐费), travel-transport (机票/火车票/打车), travel-accommodation (酒店), travel-meals, office supplies…
data-analysis
Analyze Excel/CSV files with DuckDB SQL via bash.
Spreadsheets
Create, edit, analyze, and verify standalone spreadsheet files or Google Sheets-ready workbooks, including .xlsx, .xls, .csv, and .tsv. Do not use for live controlling Microsoft Excel app or a live Excel session.
google-workspace
Fetch and query data from Google Workspace using the gws CLI — Gmail, Calendar, Docs, Sheets, Slides, and Drive. Use this skill whenever the user mentions email, inbox, messages, calendar, meetings, schedule, agenda, Google Docs, spreadsheets, presentations, or Drive files. Trigger on phrases like "check my email"…