Customer Success Manager

Three Python scripts that score customer health, predict churn risk, and identify upsell opportunities using weighted models across usage, engagement, support, and relationship dimensions. Runs entirely on standard library with no external dependencies or API calls, so you get deterministic results you can audit. Built for SaaS customer success teams who need repeatable analysis without spinning up ML infrastructure. The health scoring uses configurable segment thresholds (Enterprise, Mid-Market, SMB) and outputs color-coded classifications. Churn analyzer assigns urgency multipliers based on time to renewal. Includes QBR templates and executive reporting formats. Honest take: this is scorecarding done right, though you'll need clean data going in or garbage out applies hard.

skills.sh installs: 153
GitHub stars: 1.1K
last updated: Aug 21, 2026

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Install

$ npx -y skills add borghei/claude-skills --skill customer-success-manager --agent claude-code

Installs into .claude/skills of the current project.

Files

Customer Success Manager

Production-grade customer success analytics with multi-dimensional health scoring, churn risk prediction, and expansion opportunity identification. Three Python CLI tools provide deterministic, repeatable analysis using standard library only -- no external dependencies, no API calls, no ML models.