Which programming languages does this skill support?

The skill is optimized for polyglot execution across Julia, Python, and Clojure, supporting data exchange between these different environments.

Can I generate standalone source files from the Org file?

Yes, this skill supports 'tangling,' a process that extracts code blocks from your Org-mode documentation into standalone source files for deployment.

How does this help with AI-assisted coding?

It allows Claude to generate, test, and document complex multi-language logic in a single structured context, ensuring that documentation never drifts from the actual code.

What is literate programming with Org-Babel?

It is a methodology where code and narrative documentation coexist in a single file, allowing you to execute logic directly from the text and generate output within the same document.

Is this skill suitable for data science?

Absolutely. It is designed for scientific computing workflows where tracking data transformations and documenting methodology is as important as the code itself.

Org-Babel Literate Execution

Name: Org-Babel Literate Execution
Author: plurigrid

byplurigrid

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Data Science & ML

Executes polyglot code blocks across multiple languages directly within Org-mode files to enable seamless literate programming workflows.

About

This skill transforms static documentation into an active execution engine by leveraging Org-babel to orchestrate code across Julia, Python, and Clojure. It allows developers to maintain executable research notebooks, automate documentation through live results, and pass data between disparate language environments within a single .org file, making it ideal for scientific computing and complex system orchestration where documentation and implementation must remain perfectly synchronized.

Key Features

Automated documentation generation with embedded execution results
Source code tangling to automatically generate production files from documentation
2 GitHub stars
Cross-language data passing for integrated multi-stack workflows
In-place code block execution for rapid prototyping and interactive development
Polyglot execution across Julia, Python, and Clojure environments

Use Cases

Scientific research notebooks where documentation and code must be tightly coupled
Building complex polyglot pipelines that require data sharing between Python and Julia
Creating 'living documentation' that updates its own examples and output automatically

About

Key Features

Automated documentation generation with embedded execution results
Source code tangling to automatically generate production files from documentation
2 GitHub stars
Cross-language data passing for integrated multi-stack workflows
In-place code block execution for rapid prototyping and interactive development
Polyglot execution across Julia, Python, and Clojure environments

Use Cases

Scientific research notebooks where documentation and code must be tightly coupled
Building complex polyglot pipelines that require data sharing between Python and Julia
Creating 'living documentation' that updates its own examples and output automatically