Does this skill affect the quality of the AI's coding advice?

No. When the system detects you need a specific expert (like a React Native specialist), it loads the full, high-quality definition automatically.

How does the system decide which agent to load?

It uses a keyword-based scoring system from an internal index. If a request hits a score of 80 or higher, the full agent profile is loaded.

How much does Lazy Agent Loader reduce token usage?

It can reduce initial load token counts by over 97%, dropping usage from approximately 48,000 tokens to just 1,200 for the agent index.

Can I manually force an agent to load?

Yes, you can use the 'reload agent [id]' command to bypass the lazy loading logic and inject a full agent definition immediately.

Lazy Agent Loader

Name: Lazy Agent Loader
Author: nguyenthienthanh

bynguyenthienthanh

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Productivity & Workflow

Optimizes Claude Code token usage by dynamically loading specialized agent definitions only when high-confidence triggers are detected.

About

The Lazy Agent Loader is a core performance optimization skill for the Aura Frog plugin that drastically reduces token consumption in Claude Code sessions. By initially loading only lightweight agent summaries (~50 tokens) and deferring the injection of full domain-specific expertise until a match is confirmed, it allows users to access a library of 24 specialized agents without exceeding context limits. The skill uses an intelligent scoring system and session-based caching to ensure the AI remains responsive, cost-effective, and highly focused on the specific task at hand.

Key Features

Categorized routing for dev, quality, ops, and infra specialists
Session-based caching to prevent redundant definition reloading
On-demand loading of full agent definitions (up to 97% token savings)
1 GitHub stars
Smart scoring system (≥80 score) for precise agent activation
Lightweight index-based discovery for 24+ specialized agents

Use Cases

Switching between specialized roles like DevOps and Frontend without context bloat
Reducing API costs by preventing the loading of unnecessary system prompts
Minimizing context window usage in complex, multi-stack software projects

About

Key Features

Categorized routing for dev, quality, ops, and infra specialists
Session-based caching to prevent redundant definition reloading
On-demand loading of full agent definitions (up to 97% token savings)
1 GitHub stars
Smart scoring system (≥80 score) for precise agent activation
Lightweight index-based discovery for 24+ specialized agents

Use Cases

Switching between specialized roles like DevOps and Frontend without context bloat
Reducing API costs by preventing the loading of unnecessary system prompts
Minimizing context window usage in complex, multi-stack software projects