Skip to main content
Back to Prompt Library
implementation

Build Polars + XGBoost Scoring Engine

Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.

Linked challenge: Student Cooperative Micro-Credit Scoring & Fraud Alert System

Format
Text-first
Lines
1
Sections
1
Linked challenge
Student Cooperative Micro-Credit Scoring & Fraud Alert System

Prompt source

Original prompt text with formatting preserved for inspection.

1 lines
1 sections
No variables
0 checklist items
Write a Python script using `polars` for feature engineering and `xgboost` for inference that ingests cooperative applicant profiles and outputs loan decisions.

Adaptation plan

Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.

Keep stable

Hold the task contract and output shape stable so generated implementations remain comparable.

Tune next

Update libraries, interfaces, and environment assumptions to match the stack you actually run.

Verify after

Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.