Skip to content
Back to skills

Time Anomaly Marker

ASecurity

时序/数值异常标记工具。对指定或全部数值列进行 Z-Score 异常和差分突变检测, 输出 anomaly_flag 与 anomaly_reasons,不删除数据,适用于时序稳态/突变异常识别。

  • 539 stars
  • 0 votes
  • 0 copies
  • 2 views
  • Added September 11, 2026
toolspythonbash

Security analysis

A100/100

Pro scans all 4 files and shows the line behind each finding

Scanned September 11, 2026

npx -y skills add cas-bigdatalab/piflow --skill time_anomaly_marker --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Time Anomaly Marker?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Time Anomaly Marker
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/cas-bigdatalab-time-anomaly-marker/badge)](https://www.skillsdirectory.com/skills/cas-bigdatalab-time-anomaly-marker)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: time_anomaly_marker
description: |
  时序/数值异常标记工具。对指定或全部数值列进行 Z-Score 异常和差分突变检测,
  输出 anomaly_flag 与 anomaly_reasons,不删除数据,适用于时序稳态/突变异常识别。
name_zh: time_anomaly_marker_时序异常标记算子
input_params:
  - name: input_path
    type: string
    required: true
    description: 输入文件路径(支持CSV/TSV/Excel等)
  - name: output_path
    type: string
    required: true
    description: 输出文件路径(标记后的文件)
  - name: numeric_columns
    type: string
    required: false
    description: 需检测的数值列,逗号分隔;不填默认所有数值列
  - name: z_threshold
    type: string
    required: false
    description: Z-Score 阈值,默认 3.0
  - name: diff_threshold
    type: string
    required: false
    description: 差分突变阈值(倍数标准差),默认 3.0
output_params:
  - name: output_path
    type: csv_file
    description: 包含 anomaly_flag 与 anomaly_reasons 的标记后文件
tag: 数据清洗
publisher: COMMUNITY
---

# time_anomaly_marker 时序/数值异常标记

## 功能概述
- 基于 Z-Score 检测全局异常值。
- 基于差分标准差检测尖峰/突变。
- 输出 anomaly_flag(布尔)与 anomaly_reasons(多条原因分号分隔)。
- 不删除数据,仅标记,便于后续复核/过滤。

## 触发条件
- 时序数据需识别稳态异常或突变异常。
- 需要为后续过滤/校验提供异常标记。

## 参数说明

| 参数 | 必填 | 默认值 | 说明 |
|------|------|--------|------|
| `--input_path` | 是 |  | 输入文件路径(支持CSV/TSV/Excel等) |
| `--output_path` | 是 |  | 输出文件路径(标记后的文件) |
| `--numeric_columns` | 否 |  | 需检测的数值列,逗号分隔;不填默认所有数值列 |
| `--z_threshold` | 否 |  | Z-Score 阈值,默认 3.0 |
| `--diff_threshold` | 否 |  | 差分突变阈值(倍数标准差),默认 3.0 |

## 使用方法
```bash
python scripts/time_anomaly_marker.py \
  --input_path <输入文件> \
  --output_path <输出文件> \
  [--numeric_columns col1,col2] \
  [--z_threshold 3.0] \
  [--diff_threshold 3.0]
```

## 输出说明
- 新增列:
  - anomaly_flag: 是否命中异常
  - anomaly_reasons: 命中原因列表(分号分隔)
- 输出格式与输入一致,其余列保持不变。

## 注意事项
- 默认检测所有数值列,可通过 numeric_columns 指定。
- Z-Score 与差分阈值可按噪声水平调节。
- 对全空列/全 NaN 列自动跳过。

Files in this skill

  • SKILL.md2.6 KB
  • scripts/data_io.py3.5 KB
  • scripts/time_anomaly_marker.py4 KB
  • skill.json1.9 KB

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

View all in tools →

Comments

Loading comments…

Newsletter

Get the weekly list of safe new skills, and the ones we pulled.