Agent skill · data analytics · onewave-ai
renewal-predictor
Predicts client renewal likelihood based on health score signals. Analyzes engagement, support, adoption, satisfaction, billing, stakeholder, and usage data to calculate a weighted Health Score (0-100), classify renewal risk, and generate a prioritized action plan with early warning signals and recommended save plays.
Why this skill is useful
Adds a comprehensive predictive model and executable workflows for assessing client renewal likelihood that are not commonly found in public resources.
What it needs
Requires bash, glob, grep installed locally. About 3k tokens when loaded. Last updated 2026-07-15. 242 stars on the source repository.
What this skill does
Renewal Predictor Predict client renewal likelihood by computing a multi-dimensional Health Score and generating an actionable, evidence-backed risk assessment for every account. Core Mission For every account, answer three questions: 1. Will this client renew, and with what confidence? 2. What signals are driving that prediction? 3. What specific intervention should the team execute right now? Contents references/dimension-rubrics.md -- 0-100 scoring criteria, data sources, red/green flags for all 7 dimensions references/confidence-and-scoring.md -- composite formula, thresholds, confidence calibration, missing-data rules, edge cases references/signals.md -- compound churn and expansion signals with severity tiers references/save-plays.md -- intervention templates by priority references/output-template.md -- exact structure for renewal-forecast.md references/data-templates.md -- CSV templates to request when data is missing Health Score Model The Health Score is a composite metric from 0 to 100, built from seven weighted dimensions. Score each dimension independently on a 0-100 scale using references/dimension-rubrics.md, then combine with these weights: Dimension Weight --- --- Engagement Frequency 20% Support Ticket Volume and Sentiment 15% Feature Adoption 20% NPS/CSAT Scores 10% Billing History 10% Stakeholder Continuity 10% Usage Trends 15% Map the composite score to a prediction category (80-100 Likely to Renew, 60-79 Neutral/Monitor, 40-59 At Risk, 0-39 Likely to Churn). See references/confidence-and-scoring.md for the formula, thresholds, and confidence rules. Execution Protocol 1. Discover available data. Use Glob to find CSV, JSON, YAML, or XLSX files, CRM exports, meeting notes, or communication logs in the working directory. Use Grep for account names, metric patterns, and keywords like "churn," "cancel," "renew," "escalat," "competitor," "discount," "downgrade." If no data is found, request the templates in references/data-templates.md and stop. 2. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills onewave-ai/renewal-predictor