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 pyxll/pyxll-agent-skills --skill pywin32-excel-docsgit clone --depth 1 https://github.com/pyxll/pyxll-agent-skillsWrote 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/pyxll/pyxll-agent-skills/pywin32-excel-docs)<a href="https://agentmods.dev/skills/pyxll/pyxll-agent-skills/pywin32-excel-docs"><img src="https://agentmods.dev/badge/skills/pyxll/pyxll-agent-skills/pywin32-excel-docs/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/pyxll/pyxll-agent-skills/pywin32-excel-docs"><img src="https://agentmods.dev/badge/skills/pyxll/pyxll-agent-skills/pywin32-excel-docs.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 | $0.00097 | $0.02053 |
| Opus 5 | $0.00048 | $0.01026 |
| Sonnet 5 | $0.00019 | $0.00411 |
| Haiku 4.5 | $0.00010 | $0.00205 |
Grade A, and why
pywin32-excel-docs 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 9d 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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Excel COM API Reference Skill
This skill provides an API reference for Microsoft Excel COM objects accessed via pywin32.
It is primarily intended for use with the PyXLL Excel add-in, but applies equally to any
Python code that drives Excel via COM.
Prerequisite: PyXLL Code
BEFORE writing any code that uses a PyXLL decorator, function, or config key (
@xl_func,@xl_menu,@xl_macro,xl_app,pyxll.cfg, etc.) — invoke thefetch-pyxll-docsskill using the Skill tool. Do this before writing any code. PyXLL APIs are not covered by this skill; the live docs are the only authoritative source.
Rules for AI Agents
These rules are mandatory. Follow them before writing any Excel COM code.
-
Always read the relevant reference file before using any Excel COM class. Do not rely on training-data knowledge of the Excel COM API — method signatures, parameter names, and property types must be verified from the
resources/docs. The API is large and easy to misremember. -
Before using any class, look it up in
resources/index.mdto find which file covers it, then read its section in that file. At minimum, check: which members are properties vs methods vs property accessors, and what the parameter names and types are. -
Never guess a method or property name. If you cannot find a member in the docs, say so rather than inventing one. COM errors from wrong names surface only at runtime.
-
Property accessors (
GetX/SetX) must be called as methods, not accessed as attributes. They appear under "Property Accessors" in the docs. Example:rng.GetOffset(1, 0)— NOTrng.Offset. -
Always use
win32com.client.constants.<name>for enum/constant values. Never use bare integer literals for constants. The constant name (e.g.xlCenter) is the authoritative identifier; its integer value can change across Excel versions. The integer values inresources/enums_xl.mdare for reference only — use the named constant, not the number.
What ships with it
14 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.
- resources/addins.md 11 KB
- resources/application.md 46 KB
- resources/charts.md 33 KB
- resources/enums_xl.md 93 KB
- resources/formatting.md 14 KB
- resources/index.md 19 KB
- resources/model.md 8.9 KB
- resources/pivot.md 25 KB
- resources/range.md 23 KB
- resources/shapes.md 70 KB
- resources/tables.md 14 KB
- resources/window.md 4.9 KB
- resources/workbook.md 19 KB
- resources/worksheet.md 22 KB
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.
- 9d ago First seen · 174 lines · 97 tokens per session scan A bf7c664b178d
pywin32-excel-docs is a skill published in the GitHub repository pyxll/pyxll-agent-skills (2 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 97 tokens to every session and 2,053 once invoked, about $0.0005 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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