Use when optimising multi-page navigation performance, reducing INP on page transitions, or implementing progressive enhancement for fast page loads.
复制下面这句话,粘贴给 Claude Code、Codex、Cursor 等 AI 编程工具,它会读取安装说明并在你确认后完成安装。
请阅读 https://ai.atlankj.com/install/asset/gh-speculation-rules-d4123a30c1f1 ,按照其中的说明把「speculation-rules」安装到你(当前 AI 工具)中。执行前先告诉我将运行的命令和写入的位置,等我确认。
查看 AI 将读取的安装说明正在读取 GitHub 原文…
内容来自 GitHub 原始文件,由原作者维护。在 GitHub 查看
Navigation latency is one of the biggest contributors to poor Interaction to Next Paint (INP) and overall perceived performance. Prerendering the most likely next page eliminates all network and rendering latency — the user sees the new page in under 100 ms regardless of server response time. Google Search has used this API to deliver its "instant" results page experience.
Check whether the site uses the Speculation Rules API or equivalent prefetch/prerender techniques for likely navigation targets.
Add a Speculation Rules JSON block targeting the most likely next-page links, starting with prefetch and graduating to prerender.
Explain how the Speculation Rules API differs from rel=prefetch and rel=prerender, and how prerendering achieves near-zero navigation latency.
Review speculation rule selectors for over-eagerness — flag patterns that would prerender unrelated pages, third-party URLs, or pages with personalised/authenticated content that should not be pre-fetched.
For full implementation details, code examples, and framework-specific guidance,
see references/rule.md.
Rule page: https://frontendchecklist.io/en/rules/performance/speculation-rules