What does this skill do?

The Data Science Expert skill gives an agent expert guidance across data science — exploratory analysis, machine learning, and data visualization.

It covers data analysis (EDA, cleaning, feature development, statistical inference, experimentation), machine learning (classification, regression, clustering, evaluation, tuning, ensembles), and visualization with matplotlib, seaborn, and plotly.

It provides reusable components for cleaning, EDA, feature engineering, time-series analysis, and A/B testing, and follows a disciplined end-to-end workflow.

  • Cleans data and handles missing values and outliers

  • Engineers features and runs EDA

  • Builds and evaluates machine-learning models

  • Analyzes time series and runs A/B tests

How it works

1

Load and inspect

The agent loads the dataset, inspects its structure, and addresses data-quality issues.

2

Engineer features

It creates domain-relevant features — interactions, binning, encoding, and scaling — avoiding information leakage.

3

Model and evaluate

It validates assumptions, builds supervised or unsupervised models, and evaluates them with appropriate metrics.

4

Visualize and document

It visualizes relationships and distributions and documents the findings and methodology.

Best use cases for this skill

  • Exploratory analysis: Clean, explore, and summarize a dataset.

  • Machine learning: Build and evaluate classification or regression models.

  • Time series: Decompose, test stationarity, and forecast with ARIMA.

  • Experimentation: Run A/B tests comparing control and treatment.

Frequently asked questions

What does the Data Science Expert skill do?

It provides expert-level data science guidance — exploratory analysis, data cleaning, feature engineering, machine learning, time-series analysis, A/B testing, and visualization.

When should an agent use it?

Use it for data science work — from cleaning and exploring data through feature engineering, model building, and visualization.

What components does it include?

Reusable modules for data cleaning, EDA, feature engineering, time-series analysis, and A/B testing.

What anti-patterns does it avoid?

Skipping exploration, ignoring data quality, information leakage during transformation, over-complex features, and misleading graphics.

Use from source

Ask your Buda agent to install this community skill.

Copy this prompt into your own Buda agent. It includes the source repository and install command so the agent can complete the setup in natural language.

Prompt to send to your Buda agent
Please install the "Data Science Expert Skill" skill into this Buda agent.

Source repository: https://github.com/personamanagmentlayer/pcl
Install command: npx skills add personamanagmentlayer/pcl --skill data-science-expert -y -a universal

Please run the install command, verify the skill is available, and tell me any setup notes or follow-up steps from the source repository.
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Install workflow

  1. 1Copy the prompt
  2. 2Send it to your Buda agent
  3. 3Done