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-find-duplicatesgit 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-find-duplicates)<a href="https://agentmods.dev/skills/yuyy2004/excel-skills/excel-find-duplicates"><img src="https://agentmods.dev/badge/skills/yuyy2004/excel-skills/excel-find-duplicates/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-find-duplicates"><img src="https://agentmods.dev/badge/skills/yuyy2004/excel-skills/excel-find-duplicates.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 | $0.00136 | $0.01408 |
| Opus 5 | $0.00068 | $0.00704 |
| Sonnet 5 | $0.00027 | $0.00282 |
| Haiku 4.5 | $0.00014 | $0.00141 |
Grade A, and why
excel-find-duplicates 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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
This skill is read-only, no side effects. Follows [[excel-safe-workflow]] Scout→Analyze two-step approach. 本技能只读不写，安全无副作用。遵循 [[excel-safe-workflow]] 勘察→分析两步。
Excel Find Duplicates (Read-only) / Excel 查重（只读）
Function / 功能
- Scan for duplicate rows by specified column(s) (or multi-column combination) / 按指定列（或多列联合）扫描重复行
- Output duplicate statistics and row number list / 输出重复统计和行号列表
- Results can be directly passed to [[excel-delete]] for deletion / 结果可直接传给 [[excel-delete]] 执行删除
Step 0: Requirement Parsing / 第零步：需求解析
| Element / 要素 | Common Phrasing / 常见表述 | Default / 默认值 |
|---|---|---|
| Key Column(s) / 关键列 | "By patent number" / "Column E" / "按专利号查""E列" | Must be explicit / 必须明确 |
| Keep Strategy / 保留策略 | "Keep first" / "Keep latest" / "保留第一个""保留最新的" | Keep first occurrence / 保留首次出现 |
| Output Format / 输出格式 | Directly return row number list / 直接返回行号列表 | Excel row numbers / Excel 行号 |
Step 1: Scout (Read-only Scan) / 第一步：勘察（只读扫描）
import pandas as pd
FILE = 'target.xlsx' / FILE = '目标文件.xlsx'
KEY_COL = 'Column Name / 列名' # Key column name / 关键列名
KEEP = 'first' # 'first'=keep first occurrence / 保留首次 / 'last'=keep last / 保留末次
# pandas efficient read (C engine, seconds-level) / pandas 高效读取（C引擎，秒级）
df = pd.read_excel(FILE)
total = len(df)
mask = df[KEY_COL].duplicated(keep=KEEP)
dup_indices = df.index[mask].tolist()
dup_excel_rows = [i + 2 for i in dup_indices] # +2: pandas 0-index → Excel row number (row 1=header) / pandas 0-index → Excel行号（第1行=表头）
print(f'Total rows: {total} / 总行数: {total}')
print(f'Unique values: {total - len(dup_excel_rows)} / 唯一值: {total - len(dup_excel_rows)}')
print(f'Duplicate rows: {len(dup_excel_rows)} ({len(dup_excel_rows)/total*100:.1f}%) / 重复行: {len(dup_excel_rows)}')
print(f'Row range: {min(dup_excel_rows)} ~ {max(dup_excel_rows)}' if dup_excel_rows else 'No duplicates / 无重复')
Multi-Column Joint Dedup / 多列联合查重
KEY_COLS = ['Col1 / 列名1', 'Col2 / 列名2'] # Multi-column joint / 多列联合
mask = df.duplicated(subset=KEY_COLS, keep=KEEP)
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 · 99 lines · 136 tokens per session scan A d941b2e3fdda
excel-find-duplicates is a skill published in the GitHub repository YuYY2004/excel-skills (2 stars, last pushed 2mo ago), licensed MIT. It adds 136 tokens to every session and 1,408 once invoked, about $0.0007 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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