Borrowing it
Nothing to install: this file belongs to MisonL/Ling. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/MisonL/Ling/main/.agents/skills/nextjs-react-expert/SKILL.mdgit clone --depth 1 https://github.com/MisonL/LingWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/misonl/ling/nextjs-react-expert)<a href="https://agentmods.dev/skills/misonl/ling/nextjs-react-expert"><img src="https://agentmods.dev/badge/skills/misonl/ling/nextjs-react-expert/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/misonl/ling/nextjs-react-expert"><img src="https://agentmods.dev/badge/skills/misonl/ling/nextjs-react-expert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00057 | $0.03000 |
| Opus 5.5 | $0.00023 | $0.01200 |
| Sonnet 5.5 | $0.00011 | $0.00600 |
| Haiku 4.5 | $0.00006 | $0.00300 |
Grade A, and why
nextjs-react-expert scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 287 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Next.js 与 React 性能专家
来自 Vercel Engineering - 按影响优先级整理的 57 条优化规则
哲学： 先消除 waterfall，再优化 bundle，最后再做微优化。
选择性阅读规则（强制）
只阅读与当前任务相关的章节！ 先看下面内容地图，再按需加载。
[CRITICAL] 进行性能评审时：先看 CRITICAL（1-2），再看 HIGH/MEDIUM。
内容地图
| 文件 | 影响等级 | 规则数 | 阅读时机 |
|---|---|---|---|
1-async-eliminating-waterfalls.md |
[CRITICAL] CRITICAL | 5 条 | 页面加载慢、串行 API 调用、数据获取 waterfall（瀑布式请求） |
2-bundle-bundle-size-optimization.md |
[CRITICAL] CRITICAL | 5 条 | bundle 体积过大、TTI 慢、首屏加载问题 |
3-server-server-side-performance.md |
HIGH | 7 条 | SSR 缓慢、API Route 优化、服务端 waterfall（瀑布式请求） |
4-client-client-side-data-fetching.md |
[SUGGESTION] MEDIUM-HIGH | 4 条 | 客户端数据管理、SWR 模式、请求去重 |
5-rerender-re-render-optimization.md |
[SUGGESTION] MEDIUM | 12 条 | 过度重渲染、React 性能、memoization |
6-rendering-rendering-performance.md |
[SUGGESTION] MEDIUM | 9 条 | 渲染瓶颈、虚拟列表、图像优化 |
7-js-javascript-performance.md |
LOW-MEDIUM | 12 条 | 微优化、缓存、循环性能 |
8-advanced-advanced-patterns.md |
VARIABLE | 3 条 | 高级 React 模式、useLatest、init-once |
总计：8 大类，共 57 条规则
快速决策树
你的性能问题属于哪一类？
页面加载慢 / 可交互时间（Time to Interactive，TTI）长
-> 阅读第 1 节：消除瀑布式请求（Eliminating Waterfalls）
-> 阅读第 2 节：包体积优化（Bundle Size Optimization）
bundle 体积过大（> 200KB）
-> 阅读第 2 节：包体积优化（Bundle Size Optimization）
-> 检查：动态导入（dynamic imports）、桶文件导入（barrel imports）、tree-shaking
服务端渲染慢（SSR）
-> 阅读第 3 节：服务端性能（Server-Side Performance）
-> 检查：并行数据获取、streaming
[RUN] 重渲染过多 / UI 卡顿
-> 阅读第 5 节：重渲染优化（Re-render Optimization）
-> 检查：React.memo、useMemo、useCallback
渲染性能问题
-> 阅读第 6 节：渲染性能（Rendering Performance）
-> 检查：虚拟化、layout thrashing
客户端数据获取问题
-> 阅读第 4 节：客户端数据获取（Client-Side Data Fetching）
-> 检查：SWR 去重（deduplication）、localStorage
需要高级模式
-> 阅读第 8 节：高级模式（Advanced Patterns）
What ships with it
10 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- 1-async-eliminating-waterfalls.md 7.5 KB
- 2-bundle-bundle-size-optimization.md 6.4 KB
- 3-server-server-side-performance.md 12 KB
- 4-client-client-side-data-fetching.md 6.8 KB
- 5-rerender-re-render-optimization.md 15 KB
- 6-rendering-rendering-performance.md 10 KB
- 7-js-javascript-performance.md 17 KB
- 8-advanced-advanced-patterns.md 3.8 KB
- scripts/convert_rules.py 6.5 KB runs code
- scripts/react_performance_checker.py 9.8 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 287 lines · 57 tokens per session scan A a60cf6a51208
nextjs-react-expert is a skill published in the GitHub repository MisonL/Ling (8 stars, last pushed 7mo ago), licensed MIT. It adds 57 tokens to every session and 3,000 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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