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ssr-ssgSSR SSG 搜索

Agent Skill

ssr-ssg 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

4,194

周安装

173

GitHub Stars

公开资料未说明

下载量

1,370
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:ssr-ssg(SSR SSG 搜索)
来源仓库:https://github.com/codekungfu/ssr-ssg
安装命令:
openclaw skills install ssr-ssg
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install ssr-ssg

简介

深度解析 SSR、SSG、ISR 渲染模式差异。

  • 对比数据新鲜度、缓存策略与 SEO 表现权衡。
  • 适用于前端架构选型与技术方案设计参考。ssr-ssg 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 安装命令:openclaw skills install ssr-ssg。
  • 内容基于通用原则,需结合实际业务场景判断。

SKILL.md

name
ssr-ssg
description
Deep workflow for SSR, SSG, ISR, and hybrid rendering—choosing modes per route, data freshness, caching, streaming, hydration, SEO, and operational trade-offs (Next.js, Nuxt, Remix, etc.). Use when tuning web apps for performance, correctness, and crawlability.

SSR / SSG / Hybrid Rendering (Deep Workflow)

Rendering is an architecture decision, not a framework toggle. Guide users to map freshness, personalization, cost, and complexity per route—avoid “SSR everything” or “static everything” by default.

When to Offer This Workflow

Trigger conditions:

  • Choosing rendering strategy for marketing vs app shell vs dashboards
  • SEO + auth + dynamic data conflicts
  • Slow TTFB, stale content, or expensive server work per request
  • Hydration bugs, double data fetch, or client/server environment mismatch

Initial offer:

Use six stages: (1) route & data classification, (2) choose rendering mode(s), (3) data loading & cache layers, (4) streaming & partial SSR, (5) hydration & client boundaries, (6) validate (SEO, perf, ops). Confirm framework and hosting (Node server, serverless, edge).


Stage 1: Route & Data Classification

Goal: Each route has clear freshness, auth, and personalization needs.

Dimensions

  • Public vs authenticated: can HTML be shared or per-user?
  • Update frequency: static marketing, hourly blog, real-time inventory
  • Source of truth: CMS, DB, API with rate limits, edge KV

Output

A matrix: route pattern → public/private → max staleness acceptable → personalization level.

Exit condition: No ambiguous “dynamic page” without stating what changes and how often.


Stage 2: Choose Rendering Mode(s)

Goal: Pick SSG, SSR, ISR/ondemand revalidate, CSR with SSR shell, or edge—per route.

Heuristics

  • SSG / prerender: stable content, best TTFB/CDN cache, great SEO—watch rebuild/revalidate story
  • SSR: must reflect request-time data (A/B, geo, auth gating) or strict freshness
  • Client-heavy: acceptable for post-auth app surfaces if SEO not needed
  • Hybrid: static shell + client islands; or static generation with server components for parts (framework-specific)

Trade-offs

  • SSR cost and latency vs SSG staleness
  • Edge rendering: geography and limits (CPU, Node APIs)

Exit condition: Documented per-route strategy with rationale.


Stage 3: Data Loading & Cache Layers

Goal: One coherent story for where data is fetched and how it is cached (CDN, full-page, data cache, edge).

Practices

  • Cache-Control / surrogate keys / tag-based invalidation—align with framework primitives (e.g., revalidate, fetch cache)
  • Deduplicate requests between server and client where frameworks allow
  • Avoid accidental private data in shared cache—vary by cookie/auth correctly or disable cache

Stale-While-Revalidate

  • Great for mostly fresh—document user-visible staleness acceptance

Exit condition: Data flow diagram: origin → edge → browser; invalidation owner identified.


Stage 4: Streaming & Partial SSR

Goal: Improve perceived performance with suspense/streaming where supported.

Guidance

  • Defer slow fragments; show skeletons with accessible semantics
  • Ordering: ensure critical LCP resources not blocked by deferred junk
  • Headers: understand chunked response implications for intermediaries

Exit condition: Slow dependencies isolated; UX fallbacks defined.


Stage 5: Hydration & Client Boundaries

Goal: Correct interactive UI without double work or mismatches.

Checklist

  • Server/client component or module boundaries (framework-specific)
  • useEffect vs server fetch duplication—waterfalls
  • Environment: no window on server; no secret APIs in client bundles
  • Hydration mismatch: locale, random IDs, time—suppress or serialize state

Exit condition: Known interactive islands listed; mismatch risks mitigated.


Stage 6: Validate (SEO, Performance, Ops)

Goal: Rendering choices show up correctly in search, metrics, and logs.

SEO

  • View source / rendered HTML for critical content; meta and canonical per mode
  • Auth: soft paywalls—decide what crawlers see ethically and technically

Performance

  • TTFB vs FCP/LCP; server time vs edge cache hit
  • RUM segmented by route and cache hit

Ops

  • Cold starts on serverless SSR; concurrency limits; regional failover

Final Review Checklist

  • [ ] Per-route rendering choice documented with freshness/personalization
  • [ ] Caching and invalidation story is explicit and safe for auth
  • [ ] Streaming/skeletons don’t harm LCP or a11y
  • [ ] Hydration and env boundaries verified
  • [ ] SEO and RUM validation for top templates

Tips for Effective Guidance

  • Name staleness in seconds/minutes—“real-time” is rarely real-time.
  • When user uses Next.js, tie advice to App Router vs Pages semantics explicitly if known.
  • Warn: edge ≠ full Node—API surface differs.

Handling Deviations

  • SPA-only: focus on meta for landing routes and prerender for marketing if added later.
  • No server: SSG + client or external prerender service—be honest about limits.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

86.4%
按下载量换算1,184

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

操作浏览器

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安装前确认

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来源信息

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