signal-scan

Name: signal-scan
Availability: InStock
Author: scanbott

Analyze cross-domain sales, revenue, content, and deliverables for hidden correlations.

Updated Apr 21, 2026

Search Tags:#analytics #sales #supabase #pattern #cross-domain #revenue #signal

Ready to run

npx skills add https://github.com/scanbott/claude-skills --skill signal-scan-scanbott

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: signal-scan
Source: https://github.com/scanbott/claude-skills/tree/main/signal-scan
Command: npx skills add https://github.com/scanbott/claude-skills --skill signal-scan-scanbott

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Biweekly cross-domain pattern recognition engine that analyzes sales calls, revenue, content, and deliverables to find non-obvious correlations, trending shifts, and actionable insights. Stores patterns in Supabase with confidence scoring and compounding history, and reports findings to stakeholders.

Core Features & Use Cases

Cross-domain pattern detection across sales, revenue, content pipeline, and deliverables to surface hidden correlations.
Automated data pull, pattern scoring, and persistent storage with historical context for trend analysis.
Biweekly intelligence sweeps that produce a structured report and notify stakeholders.

Quick Start

Run the full end-to-end signal-scan workflow to pull data, analyze patterns, and store results.

Frequently Asked Questions about signal-scan

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I identify cross-domain patterns across sales, revenue, and content data?▼

Cross-domain pattern detection analyzes sales, revenue, content, and deliverables to surface hidden correlations. It applies biweekly intelligence sweeps to extract signals, score them, and store findings for reporting to stakeholders.

How do I automate biweekly intelligence sweeps for sales and revenue signals?▼

Automate biweekly intelligence sweeps by pulling data from multiple sources, performing cross-domain analysis, and upserting pattern records in Supabase. This generates an actionable report and notifications for stakeholders.

Does this pattern recognition workflow require Supabase to store historical context?▼

Yes, this pattern recognition workflow requires Supabase to store patterns with confidence scoring and compounding history. Persistent storage enables historical trend analysis and structured reporting for stakeholders.

Can I extract actionable insights by correlating sales calls with content pipeline deliverables?▼

Yes, you can extract actionable insights by correlating sales calls, revenue, content pipelines, and deliverables. The analysis surfaces non-obvious correlations and trending shifts to produce a structured report.

What is the best way to surface hidden revenue correlations from multiple data sources?▼

The best way to surface hidden revenue correlations is running an end-to-end workflow that pulls data from multiple sources, applies pattern scoring, and upserts findings into Supabase. This extracts signals and generates notifications.

When should I run cross-domain analysis to catch trending shifts in my sales data?▼

You should run cross-domain analysis on a biweekly schedule to catch trending shifts and non-obvious correlations in sales data. This intelligence sweep cadence ensures compounding history and timely stakeholder reporting.