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Beta Lead Scoring
by
1477009639zw-blip
· GitHub ↗
· v1.0.0
· MIT-0
97
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Install in OpenClaw
/install betaleadscore
Description
AI-powered B2B lead scoring model. Predicts conversion probability for potential customers using machine learning (LightGBM + SHAP). CSV upload or API integr...
README (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
Usage Guidance
This package is not malicious, but it's misleading: it advertises a LightGBM+SHAP model while the included score.py is a simple rule-based scorer. Before installing or using it: (1) review the Python script yourself — it only requires pandas/numpy and does not call external services or handle secrets; (2) if you expect a trained LightGBM model or SHAP explanations, ask the author for the model artifact and the real code that computes SHAP values; (3) avoid installing heavy ML packages unless you actually need them; and (4) run the script on non-sensitive sample data first to confirm behavior. If you need a true ML-backed lead scorer, obtain the trained model and verify how feature importances/SHAP are computed and stored.
Capability Assessment
Purpose & Capability
The description and SKILL.md advertise LightGBM + SHAP and interpretability, but score.py contains a simple rule-based implementation that never imports or uses lightgbm or shap. Declaring heavyweight ML libraries in 'Notes' is disproportionate to the actual code and could mislead users about capabilities or required setup.
Instruction Scope
Runtime instructions are narrow and clear (run python3 score.py --input ...). They do not instruct the agent to read unrelated files, access secrets, or make network calls. However, the SKILL.md claims features (SHAP explanations, model pipeline) that are not implemented by the provided script, so the instructions and claimed scope are inconsistent.
Install Mechanism
There is no install spec (lowest risk). The SKILL.md lists dependencies (lightgbm, shap, pandas) but the package does not include installation steps and the script only uses pandas/numpy. This is not an install risk but is inconsistent and could lead users to install unnecessary/large ML packages.
Credentials
The skill requests no environment variables, credentials, or config paths. The code reads only the supplied CSV and writes an output CSV — no secrets or unrelated system access are requested.
Persistence & Privilege
always:false and no installation or background persistence. The skill does not modify other skills or system settings and does not request persistent presence.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install betaleadscore - After installation, invoke the skill by name or use
/betaleadscore - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
init
Metadata
Frequently Asked Questions
What is Beta Lead Scoring?
AI-powered B2B lead scoring model. Predicts conversion probability for potential customers using machine learning (LightGBM + SHAP). CSV upload or API integr... It is an AI Agent Skill for Claude Code / OpenClaw, with 97 downloads so far.
How do I install Beta Lead Scoring?
Run "/install betaleadscore" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Beta Lead Scoring free?
Yes, Beta Lead Scoring is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Beta Lead Scoring support?
Beta Lead Scoring is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Beta Lead Scoring?
It is built and maintained by 1477009639zw-blip (@1477009639zw-blip); the current version is v1.0.0.
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