Skills

Anomaly Scan

Scan connected platforms for anomalies against stored baselines, with likely causes.

Install

npx skills add indranilbanerjee/digital-marketing-pro --skill anomaly-scan -g -a claude-code -y
Category
Engineering
Updated
6d ago
License
MIT
Context cost
Mediumabout 1,830 tokens
Runs scripts
No, instructions only

What it does

Scan connected platforms for anomalies against stored baselines, with likely causes. \"why did our CPA spike\

/digital-marketing-pro:anomaly-scan

Script location. If your host does not set ${CLAUDE_PLUGIN_ROOT}, the scripts are in this plugin's scripts/ folder, next to skills/. Run them with Python 3.10 or newer: python, or python3 where python is not found (macOS, many Linux systems).

Purpose

Scan all connected marketing platforms for anomalies, statistically significant deviations from established baselines that could indicate problems (traffic drops, CPA spikes, deliverability collapse, budget overruns) or opportunities (viral content, conversion rate improvements, unexpected channel growth). Designed to catch issues early, before they compound into costly problems, and to surface wins worth amplifying.

Input Required

The user must provide (or will be prompted for):

  • Sensitivity level: Strict (flags deviations >1.5 standard deviations from baseline), normal (>2 std dev), or relaxed (>3 std dev). Defaults to normal
  • Time period: The window to scan for anomalies, today, last 3 days, last 7 days, last 30 days, or custom range. Defaults to last 7 days
  • Platforms (optional): Specific platforms to focus the scan on (e.g., "Google Ads and Meta only"). If omitted, all connected platforms are scanned
  • Metrics focus (optional): Specific metrics to prioritize (e.g., "CPA and conversion rate only"). If omitted, all available metrics are evaluated
  • Baseline period (optional): Custom baseline for comparison instead of the default. Defaults to the rolling 30-day average maintained by performance-monitor.py
  • Exclude known events (optional): List of known events to filter out (e.g., "Black Friday sale", "site migration on Jan 15") so expected deviations are not flagged as anomalies

Process

Read the whole SKILL.md on GitHub

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