Python Roulette Color Probability Prediction

What the source does

• FilesystemNone observedNo reads or writes in the source
• NetworkNone observedNo outbound calls in the source
• ShellNone observedNo commands run in the source
• DependenciesPinnedNothing floats
• SecretsNone foundNo keys in source

Five audit layers

Gates applied: no behavioural pass.

Audit 0.4.1 · source sha 04e912cff54b · 14 Oct 2026Report an issue or request a re-scan

• PublisherECNU-ICALK GitHub organizationOwner of the repository this skill is read from
• Source folderECNU-ICALK/AutoSkill/SkillBank/ConvSkill/english_gpt4_8_GLM4.7/python-roulette-color-probability-predictionThe exact folder we audited
• LicenceNot declaredAs the repository states it
• Commit pinned for this verdict04e912cff54bA new audit runs when the source changes
• Repository statusNot archivedLast push 157 days ago
• Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

Its description: Generate Python code using machine learning to predict the probability of specific colors (red, purple, yellow) in a roulette game based on historical data, and calculate the model's accuracy.

---
id: "a417112a-edd7-4ed8-905b-e0f971ce27b9"
name: "Python Roulette Color Probability Prediction"
description: "Generate Python code using machine learning to predict the probability of specific colors (red, purple, yellow) in a roulette game based on historical data, and calculate the model's accuracy."
version: "0.1.0"
tags:
  - "python"
  - "machine learning"
  - "roulette"
  - "prediction"
  - "probability"
triggers:
  - "predict roulette colors"
  - "roulette probability python"
  - "predict red purple yellow"
  - "roulette ml code"
---

# Python Roulette Color Probability Prediction

Generate Python code using machine learning to predict the probability of specific colors (red, purple, yellow) in a roulette game based on historical data, and calculate the model's accuracy.

## Prompt

# Role & Objective
Act as a Python Machine Learning Engineer. Write code to predict the outcome probabilities of a roulette game with specific colors (red, purple, yellow) based on a list of historical results.

# Operational Rules & Constraints
- Use a machine learning classifier (e.g., Naive Bayes, SVM) from scikit-learn.
- Input data is a list of strings representing past game colors.
- Encode the categorical data using LabelEncoder.
- Predict and print the probability (%) for each color.
- Calculate and print the model's accuracy in percentage using cross-validation.
- The specific colors to handle are red, purple, and yellow.

# Anti-Patterns
- Do not use random guessing or simple frequency counting without a classifier.
- Do not omit the accuracy calculation.

## Triggers

- predict roulette colors
- roulette probability python
- predict red purple yellow
- roulette ml code

Excerpt, first 1,696 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

git clone https://github.com/ECNU-ICALK/AutoSkill
git -C AutoSkill checkout 04e912cff54b

Works in

1. 2026-10-14
   ✓SAFE B 89 / 100

   first audit · source 04e912cff54b

Questions about Python Roulette Color Probability Prediction

• github.com/ECNU-ICALK/AutoSkill/tree/main/SkillBank/ConvSkill/en — the audited source at commit 04e912cff54b and every finding aboveObserved · 14 Oct 2026

Spotted something wrong? Report a correction · Methodology