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 ladla90077-web/solidworks-mcp --skill xlsxgit clone --depth 1 https://github.com/ladla90077-web/solidworks-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/ladla90077-web/solidworks-mcp/xlsx)<a href="https://agentmods.dev/skills/ladla90077-web/solidworks-mcp/xlsx"><img src="https://agentmods.dev/badge/skills/ladla90077-web/solidworks-mcp/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/ladla90077-web/solidworks-mcp/xlsx"><img src="https://agentmods.dev/badge/skills/ladla90077-web/solidworks-mcp/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 | $0.00133 | $0.01907 |
| Opus 5 | $0.00067 | $0.00954 |
| Sonnet 5 | $0.00027 | $0.00381 |
| Haiku 4.5 | $0.00013 | $0.00191 |
Grade A, and why
XLSX scanned grade A with 1 finding 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 12d 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
subprocess.run([soffice, "--headless", "--calc", "--convert-to", "xlsx", How it starts
The opening of the file, as written. The whole thing — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Working with spreadsheets (.xlsx / .csv)
You build and edit spreadsheets by writing Python code, not by filling in a
fixed schema. The docgen tool's run_python runs your code in the app's
bundled interpreter. For spreadsheets the available library is:
openpyxl— create/edit.xlsx/.xlsm, read and write cells, formulas, number formats, fonts, fills, column widths, charts, multiple sheets.pandas— fast reading/analysis, bulk operations, and.csv/.tsv↔.xlsxconversion (read_excel,read_csv,to_excel).
Reach for pandas to load, clean, reshape, and analyze tabular data, and for
openpyxl when you need formulas, cell formatting, or to preserve an existing
workbook's structure. csv / json from the standard library also work for
plain delimited text.
run_python is real execution with full filesystem access. print(...) is
captured and returned to you.
Reading / analyzing a spreadsheet
To dump contents, use the files read tool on the .xlsx, or write a script.
Use data_only=True to read the last-calculated values of formula cells —
but never save a workbook opened that way, or the formulas are replaced by
values and lost.
from openpyxl import load_workbook
wb = load_workbook("/path/to/model.xlsx", data_only=True)
for ws in wb.worksheets:
print(f"## Sheet: {ws.title}")
for row in ws.iter_rows(values_only=True):
if any(c is not None for c in row):
print("\t".join("" if c is None else str(c) for c in row))
Creating / editing
from openpyxl import Workbook
from openpyxl.styles import Font, PatternFill, Alignment
wb = Workbook()
ws = wb.active
ws.title = "Summary"
ws.append(["Quarter", "Revenue", "COGS", "Gross profit"])
ws.append(["Q1", 1200, 700, "=B2-C2"])
ws.append(["Q2", 1500, 820, "=B3-C3"])
ws["A1"].font = Font(bold=True)
ws.column_dimensions["A"].width = 14
wb.save("/abs/path/model.xlsx")
Save to a real path, and pass that path to run_python's output_files
argument — the saved workbook then comes back as a downloadable tile the user
can open directly, so you don't have to make them hunt for the path. Still
mention where it landed.
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.
- 12d ago First seen · 161 lines · 133 tokens per session scan A f580f61b0f65
XLSX is a skill published in the GitHub repository ladla90077-web/solidworks-mcp (3 stars, last pushed 2mo ago), licensed MIT. It adds 133 tokens to every session and 1,907 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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