Lead Scoring Framework (2026 Standard)
CommunityAI-powered real estate lead scoring framework.
Data & Analytics#lead scoring#real estate#prompt caching#ML predictions#dynamic weighting#FHA audit#Jorge framework
AuthorChunkyTortoise
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This skill unifies Jorge's proven seven-question lead qualification approach with ML-driven predictions and adaptive weights to deliver a single, actionable lead score and recommended next actions.
Core Features & Use Cases
- Multi-Method Scoring: Combines Jorge baseline, ML enhancement, and dynamic market-based adjustments for robust scoring.
- Auditability & Compliance: FHA audit trails ensure unbiased housing assessments.
- Cost Efficiency & Scalability: Prompt caching and graceful fallbacks optimize runtime cost and reliability.
- Use Case: Real estate teams score thousands of leads daily across multiple markets to prioritize follow-ups and CRM syncing.
Quick Start
Provide lead interaction data to the scoring service and request a scored output with classification and rationale.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: Lead Scoring Framework (2026 Standard) Download link: https://github.com/ChunkyTortoise/EnterpriseHub/archive/main.zip#lead-scoring-framework-2026-standard Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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