An AI-powered CLI tool that analyzes application routes to suggest and implement intelligent prefetching for instant page transitions.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install prefetch-suggester
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install prefetch-suggester using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Prefetch Suggester?
Prefetch Suggester is a developer-centric tool designed to eliminate navigation latency by predicting user intent. By analyzing your project's directory structure and routing logic, this utility within the Openclaw Skills ecosystem identifies high-probability navigation paths and provides ready-to-use implementation code. It transforms standard web applications into high-performance experiences by ensuring data is ready before the user even clicks.
Built as part of the LXGIC Dev Toolkit, this tool emphasizes a zero-config philosophy. It allows developers to optimize their user flows without manually mapping every possible interaction, making it an essential addition to any modern frontend performance workflow.
Prefetch Suggester Use Cases
- Optimizing critical user flows like checkout or registration paths.
- Improving perceived performance in slow-loading React, Next.js, or Vue applications.
- Identifying which routes benefit most from hover-based or intersection-based prefetching.
- Automating the generation of prefetch implementation code for complex route structures.
How Prefetch Suggester Works
- The tool scans your specified pages or routes directory to map out the application's structure.
- It utilizes AI to evaluate the logical flow between different views and identify common navigation patterns.
- A probability model determines which data and assets should be prefetched to maximize performance without wasting bandwidth.
- The skill generates specific implementation snippets (e.g., Prefetch on hover or Intersection Observer logic) for your codebase.
Prefetch Suggester Setup
Ensure you have Node.js 18+ installed and your OPENAI_API_KEY set in your environment variables. Run the tool directly using npx:
export OPENAI_API_KEY='your_key_here'
npx ai-prefetch ./src/pages/
To see all available options and help commands:
npx ai-prefetch --help
Prefetch Suggester Data Schema & Taxonomy
The Prefetch Suggester organizes its analysis by mapping the relationship between directory paths and suggested actions. It outputs recommendations based on the following taxonomy:
| Data Point | Description |
|---|---|
| Route Path | The specific file path analyzed within the pages or app directory. |
| Probability Score | AI-calculated likelihood of a user navigating to this route next. |
| Prefetch Strategy | Recommended method such as Hover, Viewport, or Intent-based prefetching. |
| Implementation Code | Executable logic provided to implement the suggested prefetching strategy. |
Prefetch Suggester Advanced Features
- Support for both classic pages directories and modern app router structures.
- Intelligent intent signals to prioritize common paths like checkout flows over generic links.
- Bandwidth-aware recommendations to prevent over-fetching and resource waste.
- Integration-ready for Openclaw Skills users looking to automate performance audits.
- Customizable analysis depth to handle deeply nested route hierarchies in enterprise applications.
SKILL.md
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