Mini Analysis Column

v0.1.1

统计分析csv文件中某一列的表现

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Install the skill "Mini Analysis Column" (fdmseven/mini-analysis-column) from ClawHub.
Skill page: https://clawhub.ai/fdmseven/mini-analysis-column
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

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openclaw skills install mini-analysis-column

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npx clawhub@latest install mini-analysis-column

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high confidence

✓

Purpose & Capability

Name/description say it analyzes a single CSV column; SKILL.md and scripts/compute.py only request a CSV file path and column name and perform max/min/mean. There are no unrelated credentials, binaries, or services required.

✓

Instruction Scope

Instructions only ask to install pandas and run the script with --file and --rowkey. The script reads only the given CSV, prints basic stats and (optionally) debugging output. It does not read other system files, environment variables, or send data to external endpoints.

✓

Install Mechanism

No install spec in the skill bundle; SKILL.md recommends 'pip install pandas', which is appropriate and proportionate for the task. (Installing packages from PyPI is standard; users should perform installs in a trusted environment.)

✓

Credentials

The skill requires no environment variables, credentials, or config paths. The only input is a user-supplied CSV file path and column name, which aligns with the stated functionality.

✓

Persistence & Privilege

Skill is not always-enabled and uses the normal model-invocation default. It does not attempt to modify agent configuration or request persistent privileges.

Assessment

This skill appears to do exactly what it says: compute simple statistics on a numeric CSV column. If you install it: (1) run it locally or in a trusted environment; (2) install pandas via your normal package manager (prefer a virtualenv); (3) only pass CSV files you trust (the script reads the file you point it to); and (4) use --debug to inspect input shape/head if you want more confidence. There are no network calls or credential requests in the code.

Like a lobster shell, security has layers — review code before you run it.

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78downloads

0stars

2versions

Updated 1w ago

v0.1.1

MIT-0

analysis_column

统计分析 CSV 文件中某一列的表现，支持数值列的统计计算。

功能

数值列：计算最大值、最小值、平均值

依赖

需要先安装依赖：

pip install pandas

使用方法

python scripts/compute.py --file <CSV文件路径> --rowkey <列名> [--debug]

参数说明

参数	必填	说明
--file	是	CSV 文件路径
--rowkey	是	要分析的列名（必须是数值列）
--debug	否	开启调试模式，显示更多信息

示例

python scripts/compute.py --file data.csv --rowkey score

输出：

程序调用成功
最大值: 1000
最小值: 1
平均值: 505.77

注意事项

CSV 文件需要包含表头
目前仅支持数值列的统计计算
字符串列暂不支持

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