explanatory-output-style
Adds educational insights about implementation choices and codebase patterns (mimics the deprecated Explanatory output style)
Summary
This skill enriches Claude Code's responses with educational insights about implementation choices and codebase patterns.
- It helps developers understand why certain decisions were made, how code fits into the broader architecture, and what trade-offs are involved, making it ideal for learning and code review.
Install & Usage
/plugin marketplace add <org/repo>Add the configuration to /plugin install explanatory-output-style@<marketplace>
/pluginUse Cases
Usage Examples
/explanatory-output-style Explain why we use a factory pattern for creating database connections in this project.
/explanatory-output-style What are the trade-offs of using Redux vs Context API in this React app?
/explanatory-output-style Add comments to this function explaining the reasoning behind each step.
Security Audits
Frequently Asked Questions
What is explanatory-output-style?
This skill enriches Claude Code's responses with educational insights about implementation choices and codebase patterns. It helps developers understand why certain decisions were made, how code fits into the broader architecture, and what trade-offs are involved, making it ideal for learning and code review.
How to install explanatory-output-style?
To install explanatory-output-style: add a marketplace (/plugin marketplace add <org/repo>), then add the config to /plugin install explanatory-output-style@<marketplace>. Finally, /plugin in Claude Code.
What is explanatory-output-style best for?
explanatory-output-style is a plugin categorized under General. Created by Anthropic.
What can I use explanatory-output-style for?
explanatory-output-style is useful for: When onboarding to a new project, understand why specific design patterns or libraries were chosen.; During code review, get explanations of the rationale behind non-obvious implementation decisions.; When refactoring, learn about alternative approaches and their trade-offs for the current code.; To document a codebase, generate inline comments that explain the 'why' behind complex logic.; When debugging, uncover the intended behavior and assumptions behind a piece of code.; To improve team knowledge sharing, automatically annotate pull requests with architectural insights..