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name: automl-analyst description: Automatically analyzes datasets to perform classification, regression, or clustering. Generates Python training scripts and HTML reports.

AutoML Analyst Skill

This skill turns the agent into a data scientist that autonomously trains models and reports results.

Workflow

1. Data Analysis:

   • Read the input file (CSV/JSON).
   • Determine the problem type:
     • Regression: Predicting a number (e.g., predicted_ltv).
     • Classification: Predicting a category (e.g., churn/no_churn).
     • Clustering: grouping data (e.g., customer_segments) if no target is specified.

2. Code Generation:

   • Write a python script (e.g., train_model.py) using pandas and scikit-learn.
   • The script MUST output metrics and generate plots (saved as images).

3. Reporting:

   • Read resources/report_template.html.
   • Inject the results (metrics, plot images, summary) into the template.
   • Save the final report as report.html.

Code Guidelines

• Handle missing values (impute or drop).
• Encode categorical variables.
• Use matplotlib or seaborn for plots.

Example

User: "Analyze this customer_churn.csv." Agent:

1. Detects 'churn' column -> Classification problem.
2. Writes train_churn.py -> Trains Random Forest -> Accuracy 85%.
3. Generates churn_report.html with feature importance plot.