Does the Agent Detector run on every message?

Yes, it is designed with the highest priority to run automatically at the start of every interaction to ensure the correct specialized context is set for Claude.

How does it determine which technology I am using?

The skill uses a four-layer detection system that analyzes explicit mentions, intent-based keywords, project configuration files (like package.json), and specific file naming patterns.

What happens if a task involves both frontend and backend work?

The system supports multi-agent activation, where it may assign a primary agent for the core task and secondary agents to assist with supporting components or quality gates.

Can I manually override the selected agent?

Yes, users can force a specific agent by explicitly mentioning it in their request, which overrides the automatic scoring and makes that agent the primary lead.

Aura Frog Agent Detector

Name: Aura Frog Agent Detector
Author: nguyenthienthanh

bynguyenthienthanh

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生产力与工作流

Automatically identifies and activates the most suitable specialized AI agent for development tasks using multi-layer scoring and project context analysis.

关于

The Aura Frog Agent Detector is the central routing engine for the Aura Frog plugin suite, designed to ensure every Claude Code interaction is handled by a domain-specific expert. By analyzing technology mentions, user intent, project file structures, and specific file patterns, it intelligently assigns tasks to one of 24 specialized agents—from mobile development to security auditing. This eliminates the need for manual prompt engineering by providing a seamless, context-aware environment that automatically invokes the right tools and best practices for the task at hand.

主要功能

Dynamic visual status banners indicating active agents and current workflow phases
Multi-layer scoring system based on tech stack, intent, and project context
1 GitHub stars
Automatic high-priority invocation for every message to ensure expert routing
Collaborative multi-agent activation for full-stack and complex development features
Intelligent project context detection through file structure analysis (e.g., package.json, go.mod)

使用场景

Automatically routing bug fix requests to the appropriate backend or frontend framework specialist
Dynamically activating quality assurance and testing agents during code modification tasks
Identifying mobile frameworks like React Native or Flutter based on directory structure without manual input

关于

主要功能

Dynamic visual status banners indicating active agents and current workflow phases
Multi-layer scoring system based on tech stack, intent, and project context
1 GitHub stars
Automatic high-priority invocation for every message to ensure expert routing
Collaborative multi-agent activation for full-stack and complex development features
Intelligent project context detection through file structure analysis (e.g., package.json, go.mod)

使用场景

Automatically routing bug fix requests to the appropriate backend or frontend framework specialist
Dynamically activating quality assurance and testing agents during code modification tasks
Identifying mobile frameworks like React Native or Flutter based on directory structure without manual input