What kind of output does the skill generate?

It generates a structured XML file (defaulting to nuget-context.xml) that includes the compressed API surface and, optionally, full package documentation.

Does this skill require Repomix?

Yes, it utilizes Repomix under the hood to handle the extraction, compression, and formatting of the NuGet package content.

What is the primary purpose of sc-repomix-nuget?

It creates a compressed, AI-optimized representation of a NuGet package's API and structure to help Claude understand and interact with the library more effectively.

How does the compression work?

It uses Tree-sitter to perform intelligent code compression, ensuring that the API surface remains readable for AI models while staying within token limits.

Can I use this with private NuGet registries?

Yes, the skill allows you to specify an optional registry_url parameter to resolve packages and dependencies from private or custom registries.

NuGet AI Context Generator

Name: NuGet AI Context Generator
Author: randlee

byrandlee

Aprendizaje y Documentación

Generates AI-optimized context and API references for NuGet packages using Repomix for enhanced coding assistance.

Acerca de

This skill streamlines the process of providing Claude with high-density context about NuGet packages by leveraging Repomix to compress API surfaces and resolve complex dependency graphs. It automatically handles framework metadata injection, namespace mapping, and repository URL resolution to create a two-tier output optimized for information retrieval. By converting package structures into compressed XML context, it allows developers to perform deep dependency analysis and generate accurate AI-ready documentation directly within their Claude Code workflow.

Características Principales

0 GitHub stars
Injection of framework metadata, namespaces, and repository URLs
Integration with Agent Runner for automated validation and analysis
Multi-tier output options for both API surfaces and optional documentation
Automated package graph resolution for dependencies and dependents
Compressed API surface generation using Tree-sitter technology

Casos de Uso

Performing deep dependency analysis and package graph visualization
Preparing AI-ready documentation for internal or proprietary NuGet libraries
Generating context-rich API references for LLM-assisted C# development

Acerca de

Características Principales

0 GitHub stars
Injection of framework metadata, namespaces, and repository URLs
Integration with Agent Runner for automated validation and analysis
Multi-tier output options for both API surfaces and optional documentation
Automated package graph resolution for dependencies and dependents
Compressed API surface generation using Tree-sitter technology

Casos de Uso

Performing deep dependency analysis and package graph visualization
Preparing AI-ready documentation for internal or proprietary NuGet libraries
Generating context-rich API references for LLM-assisted C# development