Skills lead-scoring

Name: lead-scoring
Author: openclaw

AI-powered B2B lead scoring model. Predicts conversion probability for potential customers using machine learning (LightGBM + SHAP). CSV upload or API integration.

install

source · Clone the upstream repo

git clone https://github.com/openclaw/skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/1477009639zw-blip/betaleadscore" ~/.claude/skills/openclaw-skills-lead-scoring && rm -rf "$T"

OpenClaw · Install into ~/.openclaw/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/1477009639zw-blip/betaleadscore" ~/.openclaw/skills/openclaw-skills-lead-scoring && rm -rf "$T"

manifest: skills/1477009639zw-blip/betaleadscore/SKILL.md

Lead Scoring Model

AI-powered B2B lead scoring using LightGBM + SHAP for interpretability.

Usage

python3 score.py --input leads.csv --output scores.csv

Features

CSV upload → scored leads with conversion probability
Top features driving each score (SHAP)
Ranked priority list
Pipeline: LightGBM → SHAP → actionable insights

Input CSV Format

company_size,industry,page_views,email_opens,form_fills,job_title_score
50,tech,120,5,2,8
200,finance,45,2,0,5

Output

lead_id,score,probability,top_factor,risk_level
1,0.85,85%,page_views,hot
2,0.32,32%,low_engagement,cold

Notes

MIT-0 License | Requires: python3, lightgbm, shap, pandas