项目有162个star,说明受到一定关注
Delivers real lab measurements: LCP improved from 4.2s to 1.1s, Performance score from 61 to 100.
独立开发者
Developers using AI coding agents to generate landing pages
目标用户 · 非用户评价Target user · not a testimonial
INDIE WEB/独立站与出海·LANDING
aleksandr-alhoff/seo-landing
LCP 4.2→1.1,性能 61→100,这个 SEO skill 做到了LCP 4.2s→1.1s, Performance 61→100 — a senior Technical SEO engineer, now as an agent skill.
让AI编码代理自动生成满分PageSpeed的SEO着陆页。A ready-to-use skill that helps AI coding agents build landing pages with 100/100 PageSpeed and solid technical SEO.
怎么装:Install: git clone https://github.com/aleksandr-alhoff/seo-landing.git
02 / 现在的位置02 / Why now
首次发现FIRST SEEN
03 OCT 202603 OCT 2026
增长GROWTH
历史不足Not enough history
只有 1 个快照,还不足以计算增长Only 1 snapshots so far — not enough to compute growth
讨论DISCUSSION
暂无None
还没有采集到外部讨论No external discussion collected yet
状态STATUS
持续活跃Active
质量 A-Quality A-
项目有162个star,说明受到一定关注Delivers real lab measurements: LCP improved from 4.2s to 1.1s, Performance score from 61 to 100.
03 / 它能帮你做什么03 / What it helps you do
生成满分PageSpeed着陆页
自动优化图片加载
添加SEO结构化数据
确保无障碍访问
内置安全响应头
Generate a landing page that scores 100/100 on Google PageSpeed
Include JSON-LD schemas for WebSite, Organization, BreadcrumbList, and FAQPage
Optimize images with AVIF, WebP, and JPEG fallback across breakpoints
Meet WCAG 2.1 AA accessibility with keyboard navigation and reduced motion
Keep JavaScript under 15 KB on first load with deferred third-party widgets
04 / 谁在用04 / WHO IT’S FOR
项目有162个star,说明受到一定关注
Delivers real lab measurements: LCP improved from 4.2s to 1.1s, Performance score from 61 to 100.
独立开发者
Developers using AI coding agents to generate landing pages
目标用户 · 非用户评价Target user · not a testimonial
项目最近一次提交在2026-08-30,表明近期有更新
Enforces LCP < 2.5s, INP < 100ms, CLS < 0.1; uses AVIF/WebP/JPEG via <picture>, critical CSS inline, and system fonts only.
前端开发者
Technical SEO specialists who want to automate page creation
目标用户 · 非用户评价Target user · not a testimonial
项目包含完整的基准测试和验证流程,确保质量
Includes a negative fixture that must fail every validator gate, confirming the skill catches common mistakes.
内容创作者
Content teams that need fast, SEO-friendly static pages
目标用户 · 非用户评价Target user · not a testimonial
项目有162个star,说明受到一定关注
Delivers real lab measurements: LCP improved from 4.2s to 1.1s, Performance score from 61 to 100.
技术创业者
Developers using AI coding agents to generate landing pages
目标用户 · 非用户评价Target user · not a testimonial
不适合谁Not for同样来自文档,不是我们的判断Also from the docs, not our judgement
05 / 安装05 / Install
$ README 里给出的安装方式。The installation method given in the README.
$ README 里给出的安装方式。The installation method given in the README.
两种装法选一个即可 —— 上面那条给命令行用户,下面那条给写代码的用户。Pick one of the two — the first is for command-line users, the second for people writing code.
克隆仓库后,将seo-landing文件夹复制到你的AI编码助手的技能目录(如~/.claude/skills/)。Clone the repository and copy the seo-landing folder into your skill directory — for Claude Code, run: cp -R seo-landing ~/.claude/skills/ or .claude/skills/ for a project-local install.
06 / 限制与风险06 / Limits and risk
风险不是警告,是可信度的一部分。以下结论只基于文档静态扫描,我们不会执行项目里的任何代码。Risk here is evidence, not an alarm. These findings come from static scanning of the docs; we never execute a project’s code.
限制LIMITS
未知Unknown
静态扫描STATIC SCAN
在 README、SKILL.md 和依赖清单中没有匹配到已知风险模式。No known risk patterns matched in the README, SKILL.md or dependency list.这不等于安全that does not mean it is safe,只能说明文档里没写。 — only that the docs do not mention it.
静态扫描未发现明显风险,但不代表安全。The static scan did not detect any known risk patterns, but this does not guarantee the skill is safe. Review the code before using it.
这里只做静态扫描:读 README、SKILL.md 和依赖清单,不执行代码。没有命中不代表安全。This is static scanning only: we read the README, SKILL.md and dependency list, and never execute code. No findings does not mean safe.
{
"agents": [
{
"agent": "claude-code",
"evidence": "readme: …c): works in VS Code Copilot, Claude Code, OpenAI Codex, Google Antigra…"
},
{
"agent": "codex",
"evidence": "readme: …VS Code Copilot, Claude Code, OpenAI Codex, Google Antigravity, Cursor,…"
},
{
"agent": "gemini-cli",
"evidence": "readme: …, Google Antigravity, Cursor, Gemini CLI, OpenClaw, Hermes, and other…"
},
{
"agent": "vscode",
"evidence": "readme: …loped by Anthropic): works in VS Code Copilot, Claude Code, OpenAI…"
},
{
"agent": "opencode",
"evidence": "readme: …g ~/.gemini/config/skills/ # OpenCode mkdir -p ~/.config/opencode/s…"
}
],
"apiKey": null,
"docker": null,
"taxonomy": {
"scores": {
"design": 0,
"ai-tools": 0,
"dev-tools": 1,
"indie-web": 12,
"skill-agent": 10,
"productivity": 0
},
"primary": "indie-web",
"secondary": "landing"
},
"localRuntime": null,
"skillMdTotal": 1,
"skillMdErrors": [],
"treeTruncated": false,
"categoryScores": {
"data": 0,
"agent": 1,
"media": 1,
"design": 1,
"browser": 0,
"devtool": 1,
"security": 1,
"marketing": 3,
"productivity": 0
},
"classification": [
{
"signal": "1 SKILL.md with name + description",
"weight": 0.95
},
{
"signal": "README describes a Claude / Agent Skill",
"weight": 0.7
},
{
"signal": "description mentions AI",
"weight": 0.2
}
],
"scannedSources": [
"readme",
"SKILL.md"
],
"skillMdFetched": 1
}