performance

What This Skill Does

The performance skill for OpenClaw is an comprehensive toolkit designed to identify, analyze, and remediate bottlenecks in web applications and AI-driven API pipelines. It bridges the gap between traditional frontend web performance and modern LLM cost management. By auditing Core Web Vitals (LCP, CLS, FID) and evaluating resource weights, this skill provides actionable advice on how to improve loading speeds, implement effective code splitting, optimize critical rendering paths, and minimize bandwidth. Furthermore, it addresses the rising cost of LLM integration by helping developers implement smart model routing, budget tracking, and prompt caching strategies to ensure efficient resource consumption.

Installation

To integrate this skill into your OpenClaw environment, execute the following command in your terminal: clawhub install openclaw/skills/skills/huamu668/performance-ecc

Use Cases

• Auditing an existing React or Next.js application for excessive JS bundle sizes that impact page speed.
• Providing a structured performance budget for new projects to maintain high standards for mobile users.
• Optimizing LLM-based applications by routing low-complexity queries to cheaper, faster models while reserving high-end models for complex tasks.
• Reducing TTFB and render-blocking resources through precise HTML, CSS, and JS loading strategies.
• Implementing server-side caching and content compression policies to ensure optimal user experience under varying network conditions.

Example Prompts

1. "Analyze my current Lighthouse report data and suggest three specific code-level optimizations to improve my Largest Contentful Paint (LCP) for mobile users."
2. "We are spending too much on GPT-4 API tokens. Can you help me set up a model routing strategy that shifts 70% of our chat traffic to a more cost-effective model without sacrificing user satisfaction?"
3. "Review this component file and suggest how I can use code-splitting and tree-shaking to reduce its impact on our main bundle size."

Tips & Limitations

When using the performance skill, always prioritize the most impactful metrics first (LCP and TTFB). Keep in mind that aggressive tree-shaking might require manual testing to ensure dependencies are resolved correctly. While the LLM cost optimization strategies are highly effective, they require proper API key management and monitoring. Note that this skill provides recommendations based on your current configuration; consistent monitoring is required as your codebase scales. Always test performance changes in a staging environment to prevent regressions in user experience.