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 YuYY2004/excel-skills --skill excel-safe-workflowgit clone --depth 1 https://github.com/YuYY2004/excel-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/yuyy2004/excel-skills/excel-safe-workflow)<a href="https://agentmods.dev/skills/yuyy2004/excel-skills/excel-safe-workflow"><img src="https://agentmods.dev/badge/skills/yuyy2004/excel-skills/excel-safe-workflow/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/yuyy2004/excel-skills/excel-safe-workflow"><img src="https://agentmods.dev/badge/skills/yuyy2004/excel-skills/excel-safe-workflow.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 | $0.00185 | $0.02433 |
| Opus 5 | $0.00093 | $0.01216 |
| Sonnet 5 | $0.00037 | $0.00487 |
| Haiku 4.5 | $0.00018 | $0.00243 |
Grade A, and why
excel-safe-workflow 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 10d 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 — 235 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Excel Safe Editing Five-Step Method / Excel 安全编辑五步法
概述
编辑现有 Excel 文件(尤其是大文件或包含公式的文件)时,跳过勘察直接操作极易出错——不知道单元格里存的是值还是公式、insert 操作后公式引用错乱、处理完才发现数据对应不上。
此技能定义五步标准流程,所有 Excel 结构性编辑任务均应遵循。
第零步:备份(操作前必做) / Step Zero: Backup (Mandatory)
任何写操作都有不可逆风险。备份是第一道防线。
import shutil
from datetime import datetime
FILE = '目标文件.xlsx'
BAK = FILE.replace('.xlsx', f'_backup_{datetime.now().strftime("%Y%m%d_%H%M%S")}.xlsx')
shutil.copy2(FILE, BAK)
print(f'已备份: {os.path.basename(BAK)}')
规则:
- 操作前必备份,备份名含时间戳,同目录存放
- 操作成功后,同文件历史备份仅保留最新 3 份
- 操作失误后:立即删除损坏文件 → 从备份恢复 → 重试
第一步:勘察 / Step 1: Scout
目标:彻底了解文件结构,不遗漏任何关键信息。
1.1 文件体量
import os
size_mb = os.path.getsize('file.xlsx') / 1024 / 1024
print(f'文件大小: {size_mb:.1f} MB')
- 估算加载时间:~1s/MB(openpyxl 全量模式)
- 设定合理 timeout:至少
文件大小_MB × 2 + 60秒
1.2 结构扫描
from openpyxl import load_workbook
# 全量模式获取准确行列数
wb = load_workbook('file.xlsx')
ws = wb.active
print(f'工作表: {ws.title}, 行: {ws.max_row}, 列: {ws.max_column}')
# 读取所有表头(可能有合并单元格/多行表头)
for row_idx in range(1, 4): # 前3行,覆盖多行表头
for col_idx in range(1, ws.max_column + 1):
v = ws.cell(row=row_idx, column=col_idx).value
if v is not None:
print(f' 行{row_idx} 列{col_idx}: {repr(v)[:60]}')
1.3 数据类型双重扫描(关键!) / Dual Data Type Scan (Critical!)
这是最常见的翻车点。 必须同时用两种模式读取,对比确认是值还是公式:
# 模式A:默认模式 → 读到公式字符串
wb_raw = load_workbook('file.xlsx', read_only=True)
ws_raw = wb_raw.active
# 模式B:data_only → 读到计算结果
wb_data = load_workbook('file.xlsx', read_only=True, data_only=True)
ws_data = wb_data.active
# 对比目标列的2-6行
for col in target_columns:
for row in range(2, 7):
v_raw = ws_raw.cell(row=row, column=col).value
v_data = ws_data.cell(row=row, column=col).value
match = type(v_raw) == type(v_data)
print(f' 列{col}行{row}: raw={type(v_raw).__name__}={repr(v_raw)[:30]}')
print(f' data_only={type(v_data).__name__}={repr(v_data)[:30]} {"✓" if match else "⚠️公式!"}')
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.
- 10d ago First seen · 235 lines · 185 tokens per session scan A bbdc5a8f55c2
excel-safe-workflow is a skill published in the GitHub repository YuYY2004/excel-skills (2 stars, last pushed 1mo ago), licensed MIT. It adds 185 tokens to every session and 2,433 once invoked, about $0.0009 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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