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 fuzhengwei/xfg-skills-template --skill data-analysisgit clone --depth 1 https://github.com/fuzhengwei/xfg-skills-templateWrote 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/fuzhengwei/xfg-skills-template/data-analysis)<a href="https://agentmods.dev/skills/fuzhengwei/xfg-skills-template/data-analysis"><img src="https://agentmods.dev/badge/skills/fuzhengwei/xfg-skills-template/data-analysis/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/fuzhengwei/xfg-skills-template/data-analysis"><img src="https://agentmods.dev/badge/skills/fuzhengwei/xfg-skills-template/data-analysis.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 | $0.00058 | $0.00541 |
| Opus 5 | $0.00029 | $0.00270 |
| Sonnet 5 | $0.00012 | $0.00108 |
| Haiku 4.5 | $0.00006 | $0.00054 |
Grade A, and why
data-analysis 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.
What it actually says
数据分析技能
对表格数据文件进行探索、分析和可视化。
支持的文件格式
- CSV / TSV
- Excel (.xlsx, .xls)
核心功能
1. 探索性分析
import pandas as pd
df = pd.read_csv("data.csv")
print(df.shape) # 行数和列数
print(df.dtypes) # 列类型
print(df.describe()) # 统计摘要
print(df.isnull().sum()) # 缺失值统计
2. 数据清洗
- 处理缺失值：填充或删除
- 去除重复行
- 类型转换
- 异常值检测
3. 数据可视化
使用 matplotlib 生成图表：
- 柱状图：分类数据对比
- 折线图：趋势分析
- 散点图：相关性分析
- 直方图：分布分析
4. 统计分析
- 描述统计（均值、中位数、标准差）
- 分组聚合
- 相关性分析
工作流
- 读取数据文件，检查格式和编码
- 输出基本统计摘要
- 根据用户需求进行特定分析
- 生成图表时保存到文件并报告路径
输出规范
- 统计结果使用 Markdown 表格
- 图表保存为 PNG 文件
- 清洗后的数据保存为新文件，不覆盖原始数据
Gotchas
- 读取文件时始终指定
encoding='utf-8'，中文数据可能需要encoding='gbk' - Excel 文件使用
openpyxl引擎：pd.read_excel(file, engine='openpyxl') - 生成图表后必须调用
plt.tight_layout()避免标签截断 - 中文字体设置：
plt.rcParams['font.sans-serif'] = ['Arial Unicode MS']
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 · 71 lines · 58 tokens per session scan A b9020f0a4557
data-analysis is a skill published in the GitHub repository fuzhengwei/xfg-skills-template (11 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 58 tokens to every session and 541 once invoked, about $0.0003 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 2026-08-30.
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