Does it only look at configuration files like package.json?

No, it uses a multi-layered approach: it checks explicit settings first, followed by the current file extension, project configuration files, and finally common directory structure patterns.

How does Context Detection handle fullstack projects?

It uses a multi-stack detection algorithm that scans for multiple configuration files, such as package.json and go.mod, simultaneously to identify both frontend and backend components.

Which frameworks are currently supported for detection?

The skill currently supports React, Vue, Go, Dingo, Rust, Python, and Bun, including their respective testing and state-management ecosystems.

Can I manually override the automated detection?

Yes, you can define explicit stack preferences in your .claude/settings.json file, which takes the highest priority over automated scans.

Context Detection & Stack Analysis

Name: Context Detection & Stack Analysis
Author: MadAppGang

byMadAppGang

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211

Productivity & Workflow

Automatically identifies project technology stacks and directory structures to configure optimal development environments and framework-specific skills.

About

The Context Detection skill streamlines your development workflow by intelligently analyzing your project's codebase to determine its specific technology stack. By scanning configuration files like package.json, go.mod, and pyproject.toml, as well as directory patterns and file extensions, it automatically loads relevant framework-specific skills and quality checks. It is particularly powerful for managing complex fullstack architectures—such as React paired with Go—ensuring that the right coding patterns and testing strategies are applied precisely where they are needed without manual configuration.

Key Features

Multi-stack detection for complex fullstack and polyglot projects
Real-time context-aware analysis based on active file extensions
Seamless integration with transpiled languages like Dingo
Hierarchical detection priority from explicit settings to inferred directory structures
211 GitHub stars
Automatic framework-specific skill loading for React, Vue, Go, Rust, Python, and Bun

Use Cases

Standardizing quality checks and linting across various technology stacks within the same project
Automatically configuring a workspace when opening a new multi-repository or fullstack project
Dynamically switching development contexts between frontend and backend files in a monorepo

About

Key Features

Multi-stack detection for complex fullstack and polyglot projects
Real-time context-aware analysis based on active file extensions
Seamless integration with transpiled languages like Dingo
Hierarchical detection priority from explicit settings to inferred directory structures
211 GitHub stars
Automatic framework-specific skill loading for React, Vue, Go, Rust, Python, and Bun

Use Cases

Standardizing quality checks and linting across various technology stacks within the same project
Automatically configuring a workspace when opening a new multi-repository or fullstack project
Dynamically switching development contexts between frontend and backend files in a monorepo