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Mustafa ErgisiandClaude Opus 4.6
f7d2240132
Productivity: Pulse (metrics), Standup, Inbox, Minutes Development: Lens (code review), Scribe (docs), Trace (bugs), Probe (API test), Log (changelog) Marketing: Buzz (social), Rank (SEO), Digest (newsletter), Scout (competitor) Business: Compass (support), Pipeline (sales), Ledger (invoices), Sentinel (churn) Personal: Atlas (planner), Scroll (reading), Iron (fitness) Each agent includes SOUL.md config and README.md with quick start, use cases, example outputs, and tips. Total: 23 agents. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
🔮 Sentinel - The Churn Predictor
Your AI retention agent that predicts churn, identifies at-risk customers, and suggests actions to keep them.
Overview
Sentinel helps you retain customers before they leave:
- Scores accounts by churn risk based on behavior
- Alerts when active users go silent
- Suggests personalized retention actions
- Analyzes churn reasons and patterns
Quick Start
Installation
mkdir -p ~/.openclaw/agents/churn-predictor/agent
cp SOUL.md ~/.openclaw/agents/churn-predictor/agent/
openclaw agents add churn-predictor --workspace ~/.openclaw/agents/churn-predictor
First Conversation
openclaw chat churn-predictor "Churn risk report"
Use Cases
1. Weekly Risk Report
You: "Churn risk report"
Sentinel: [High/medium/low risk accounts with scores, signals, actions]
2. Churn Analysis
You: "Why did users churn last month?"
Sentinel: [Reasons breakdown, revenue impact, patterns, suggestions]
3. Re-engagement
You: "Draft re-engagement email for Tom"
Sentinel: [Personalized email highlighting new features and value]
4. Retention Strategy
You: "What can we do about price-sensitive churn?"
Sentinel: [Mid-tier plan suggestion, annual discount data, competitor comparison]
Example Outputs
Risk Report
Weekly Churn Risk - Feb 10-16
High Risk (80+): 3 accounts
1. Tom Baker (91) - $49/mo - 12 days inactive
2. Sarah Mills (85) - $29/mo - 2 failed payments
3. Dev Studio (82) - $49/mo - usage dropped 80%
Revenue at risk: $340/mo
Healthy: 142 accounts (92%)
Churn Analysis
January: 7 cancellations ($203/mo lost)
Reasons:
- Too expensive: 3
- Switched competitor: 2
- No longer needed: 1
- Payment failed: 1
Pattern: Price churn peaks in month 2-3.
Suggestion: Add mid-tier plan.
Tips
- Review risk reports weekly - Early action prevents churn
- Personalize outreach - Generic emails don't save customers
- Track what works - Note which retention actions lead to saves
- Separate voluntary from involuntary - Different problems, different solutions
Changelog
- v1.0.0 - Initial release with risk scoring
- v1.1.0 - Churn reason analysis
- v1.2.0 - Re-engagement email drafting
Author
Created by @openclaw
License
MIT