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Real Estate Price Prediction and Classification Pipeline

100 / 100 · Low risk

Fine to try.

By ECNU-ICALK/AutoSkill (GitHub) · coding · 613 stars · scanned at commit 94c47ca

Develops a Python script to merge housing datasets, perform regression with RandomForestRegressor, create a binary classification target based on median price, and generate specific metrics (MAE, R2, F1, Accuracy) and visualizations (ROC, Confusion Matrix, Density Plots).

Works with any agent that supports SKILL.md skills.

What this skill can do

We found nothing in the files we read that matches our rules. That does not prove the skill is safe: see the limits of static scanning.

Install

Paste this into your terminal. It downloads exactly the version we scanned, not whatever is newest.

if [ -e ~/.agents/skills/'real-estate-price-prediction-and-classification-pipeline' ] || [ -L ~/.agents/skills/'real-estate-price-prediction-and-classification-pipeline' ]; then echo 'A skill folder named real-estate-price-prediction-and-classification-pipeline already exists — not replacing it' >&2; false; else d=$(mktemp -d) && git clone --quiet --filter=blob:none --no-checkout 'https://github.com/ECNU-ICALK/AutoSkill' "$d" && git -C "$d" checkout --quiet '94c47ca488d4ba4117d20272e66d49b9877e68cf' -- 'SkillBank/ConvSkill/english_gpt4_8_GLM4.7/real-estate-price-prediction-and-classification-pipeline' && mkdir -p ~/.agents/skills && cp -R "$d"/'SkillBank/ConvSkill/english_gpt4_8_GLM4.7/real-estate-price-prediction-and-classification-pipeline' ~/.agents/skills/'real-estate-price-prediction-and-classification-pipeline' && rm -rf "$d"; fi

Codex reads ~/.agents/skills directly. For Claude Code, Cursor, Copilot, Gemini CLI, Antigravity or OpenCode, also link it. For Claude Code: ln -s ~/.agents/skills/'real-estate-price-prediction-and-classification-pipeline' ~/.claude/skills/'real-estate-price-prediction-and-classification-pipeline' (other agents: ~/.cursor/skills, ~/.copilot/skills, ~/.gemini/skills, ~/.gemini/config/skills, ~/.config/opencode/skills). Or install through the finder skill, which does both.

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