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Agent Skill

Outlier Detection And Quality Assessment skill

outlier-detection-and-quality-assessmentOpenSenseNova/SenseNova-Skillsskills/sn-da-excel-workflow/capability/excel-data-cleaning/outlier-detection/SKILL.md

执行全面的异常值检测与数据质量评估，利用 IQR 方法识别异常值并结合偏度、峰度分析数据分布特征，适用于非正态分布数据的预处理阶段。

5.8kMIT

always on

58 tokname + description

once used

1,383 tokSKILL.md body

bundled files

0

repo stars

5.8kGitHub

Install the Outlier Detection And Quality Assessment skill

Skills CLI (Claude Code, Codex, Cursor and others)

npx skills add https://github.com/OpenSenseNova/SenseNova-Skills --skill outlier-detection-and-quality-assessment

Claude Code, by hand (all projects)

git clone --depth 1 https://github.com/OpenSenseNova/SenseNova-Skills.git /tmp/SenseNova-Skills
mkdir -p ~/.claude/skills
cp -R /tmp/SenseNova-Skills/skills/sn-da-excel-workflow/capability/excel-data-cleaning/outlier-detection ~/.claude/skills/outlier-detection-and-quality-assessment

For one project only, copy the folder into .claude/skills/ in that project instead. The agent picks it up when a task matches its description.

What it costs your context

Agent Skills load in three steps. Tokens counted with the o200k tokenizer; your model's count will differ a little.

WhenWhat loadsCost
Every sessionName and description58 tok
When the agent uses itThe SKILL.md instructions1,383 tok
Only if openedNo bundled files—

Until it is used, outlier-detection-and-quality-assessment costs about 23× less than the median MCP server we measured (1,362 tokens on every turn). Installing all 83 skills from OpenSenseNova/SenseNova-Skills would load 5,827 tokens of descriptions. Skills vs MCP study

Checks

  • The name doesn't match its folder name, as the specification requires.

Checked 2026-10-22 · method

What's inside

The headings of its SKILL.md. Read the full file on GitHub.

  • Step 1 加载数据并配置环境
  • Step 2 基于 IQR 方法识别异常值
  • Step 3 生成多维度可视化箱线图
  • Step 4 偏度与峰度分析及质量评估
  • Step 5 异常值处理建议（骨架）

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