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React Server Components Framework

Community
yonatangross
react-server-components-framework

Use when building Next.js 16+ apps with React Server Components. Covers App Router, Cache Components (replacing experimental_ppr), streaming SSR, Server Actions, and React 19 patterns for server-first architecture.

Overview

Publisheryonatangross
Repositoryorchestkit
Skill namereact-server-components-framework
Stars
298
Forks
35
Bundled files
16
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 16 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by yonatangross on GitHub. Read the source before you install it.

Installation

Install the React Server Components Framework AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/yonatangross/orchestkit/tree/main/plugins/ork/skills/react-server-components-framework
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/yonatangross/orchestkit.git /tmp/orchestkit
mkdir -p .claude/skills
cp -r /tmp/orchestkit/plugins/ork/skills/react-server-components-framework .claude/skills/react-server-components-framework
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable React Server Components Framework in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads React Server Components Framework on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so React Server Components Framework is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

React Server Components Framework

Overview

React Server Components (RSC) enable server-first rendering with client-side interactivity. This skill covers Next.js 16.2 LTS App Router patterns, Server Components, Server Actions, and streaming.

Next.js 16.2.6 / React 19.2.6 (security release, May 2026) — Turbopack is the default bundler (no --turbo flag needed), Server Fast Refresh is on by default, and the new cacheComponents config flag replaces the legacy experimental_ppr escape hatch. For AI-agent debugging Next.js ships Next DevTools MCP — wire npx -y next-devtools-mcp@latest into .mcp.json (it connects via the dev server's /_next/mcp endpoint) to inspect render trees and cache boundaries mid-session.

When to use this skill:

  • Building Next.js 16+ applications with the App Router
  • Designing component boundaries (Server vs Client Components)
  • Implementing data fetching with caching and revalidation
  • Creating mutations with Server Actions
  • Optimizing performance with streaming and Suspense

Quick Reference

Server vs Client Components

FeatureServer ComponentClient Component
DirectiveNone (default)'use client'
Async/awaitYesNo
HooksNoYes
Browser APIsNoYes
Database accessYesNo
Client JS bundleZeroShips to client

Key Rule: Server Components can render Client Components, but Client Components cannot directly import Server Components (use children prop instead).

Data Fetching Quick Reference

Next.js 16 Cache Components (Recommended):

tsx
import { cacheLife, cacheTag } from 'next/cache'

// Default — shared across all users (public CDN-cached)
async function CachedProducts() {
  'use cache'
  cacheLife('hours')
  cacheTag('products')
  return await db.product.findMany()
}

// Remote variant (16.2+) — always served from the edge/CDN, never rendered
// inline on the origin. Best for static product listings, marketing content.
async function MarketingHero() {
  'use cache: remote'
  cacheLife('days')
  return <Hero />
}

// Private variant (16.2+) — cached per-user session. Never shared across
// users. Use for personalized dashboards with expensive computation.
async function UserDashboard({ userId }: { userId: string }) {
  'use cache: private'
  cacheLife('minutes')
  cacheTag(`user:${userId}`)
  return await loadDashboard(userId)
}

// Invalidate cache — v16 requires a cacheLife profile as the 2nd arg
import { revalidateTag } from 'next/cache'
revalidateTag('products', 'max') // or updateTag('products') for read-your-writes

Enable via next.config.ts:

ts
import type { NextConfig } from 'next'
const config: NextConfig = {
  cacheComponents: true,  // 16.2+ — replaces experimental_ppr flag
}
export default config

Legacy Fetch Options (Next.js 15):

tsx
// Static (cached indefinitely)
await fetch(url, { cache: 'force-cache' })

// Revalidate every 60 seconds
await fetch(url, { next: { revalidate: 60 } })

// Always fresh
await fetch(url, { cache: 'no-store' })

// Tag-based revalidation
await fetch(url, { next: { tags: ['posts'] } })

Server Actions Quick Reference

tsx
'use server'

export async function createPost(formData: FormData) {
  const title = formData.get('title') as string
  const post = await db.post.create({ data: { title } })
  revalidatePath('/posts')
  redirect("/posts/" + post.id)
}

Async Params/SearchParams (Next.js 16)

Route parameters and search parameters are now Promises that must be awaited:

tsx
// app/posts/[slug]/page.tsx
export default async function PostPage({
  params,
  searchParams,
}: {
  params: Promise<{ slug: string }>
  searchParams: Promise<{ page?: string }>
}) {
  const { slug } = await params
  const { page } = await searchParams
  return <Post slug={slug} page={page} />
}

Note: Also applies to layout.tsx, generateMetadata(), and route handlers. Complete migration guide: first-party next-upgrade / vercel:next-upgrade skill. House scars: Read("references/ork-delta.md").

Dev Server (Next.js 16.2 LTS)

  • Turbopack default — next dev and next build run Turbopack without any flag. Pass --webpack only when forced (legacy plugin).
  • Server Fast Refresh — Server Components hot-reload on save without losing client state. No extra config; it's on by default in 16.2.
  • Next DevTools MCP — register npx -y next-devtools-mcp@latest in .mcp.json; it attaches to the running dev server over the /_next/mcp endpoint and exposes RSC payloads and cache boundaries to an MCP client. Designed for AI agents that need to inspect render trees mid-session without screenshotting. (There is no next-browser binary.)

References

Load on demand with Read("references/<file>"):

FileContent
ork-delta.mdHouse rules and scars: fabricated-API corrections from PR #2143, React 19 house conventions (2026-07-31 distillation)
tanstack-router-patterns.mdReact 19 features without Next.js, route-based data fetching, client-rendered app patterns
capability-details.mdKeyword and problem-mapping metadata for all 12 RSC capabilities

Upstream coverage (do not restate)

Vendor tutorials for these topics live in first-party skills and docs. This skill keeps only floors, scars, and house decisions (references/ork-delta.md).

TopicFirst-party source
Server Components fundamentals (async components, data fetching, route segment config, generateStaticParams, error handling)next-best-practices / vercel:nextjs skill; nextjs.org/docs
Client Components, 'use client', hydration, client-only renderingnext-best-practices / vercel:nextjs skill
Server/Client boundary and composition patterns, serializable propsnext-best-practices / vercel:nextjs skill; vercel-composition-patterns
Data fetching and caching (fetch cache options, revalidate, tags)next-best-practices / vercel:nextjs skill
Streaming SSR, Suspense boundaries, loading.tsx, skeleton statesvercel:nextjs skill (streaming)
Server Actions, progressive enhancement, useActionState forms, Zod validationvercel:nextjs skill (Server Actions)
Advanced routing (parallel, intercepting, route groups, dynamic and catch-all)vercel:nextjs skill (routing)
Pages Router to App Router migrationnext-upgrade / vercel:next-upgrade skill
Next.js 16 upgrade, breaking changes, codemodsnext-upgrade / vercel:next-upgrade skill
Cache Components: use cache, cacheLife, cacheTag, updateTag, PPRnext-cache-components / vercel:next-cache-components skill
React 19 core APIs (useActionState, useFormStatus, useOptimistic, use(), ref as prop)context7: /vercel/next.js + react.dev (query-docs)
RSC implementation and deployment checklistnext-best-practices skill

Best Practices Summary

Component Boundaries

  • Keep Client Components at the edges (leaves) of the component tree
  • Use Server Components by default
  • Extract minimal interactive parts to Client Components
  • Pass Server Components as children to Client Components

Data Fetching

  • Fetch data in Server Components close to where it's used
  • Use parallel fetching (Promise.all) for independent data
  • Set appropriate cache and revalidate options
  • Use generateStaticParams for static routes

Performance

  • Use Suspense boundaries for streaming
  • Implement loading.tsx for instant loading states
  • Enable PPR for static/dynamic mix
  • Use route segment config to control rendering mode

Templates

  • scripts/server-component-template.tsx - Basic async Server Component with data fetching
  • scripts/client-component-template.tsx - Interactive Client Component with hooks
  • scripts/server-action-template.ts - Server Action with validation and revalidation
  • scripts/create-server-component.md - Command-style scaffold; kept as the script-invocation contract exercised by tests/skills/scripts/

Troubleshooting

ErrorFix
"You're importing a component that needs useState"Add 'use client' directive
"async/await is not valid in non-async Server Components"Add async to function declaration
"Cannot use Server Component inside Client Component"Pass Server Component as children prop
"Hydration mismatch"Use 'use client' for Date.now(), Math.random(), browser APIs
"params is not defined" or params returning PromiseAdd await before params (Next.js 16 breaking change)
"experimental_ppr is not a valid export"Use Cache Components with "use cache" directive instead
"cookies/headers is not a function"Add await before cookies() or headers() (Next.js 16)

Resources


Related Skills

After mastering React Server Components:

  1. Streaming API Patterns - Real-time data patterns
  2. Type Safety & Validation - tRPC integration
  3. Edge Computing Patterns - Global deployment
  4. Performance Optimization - Core Web Vitals

Capability Details

Keyword and problem-mapping metadata for each RSC capability (react-19-patterns, use-hook-suspense, optimistic-updates-async, rsc-patterns, server-actions, data-fetching, streaming-ssr, caching, cache-components, tanstack-router-patterns, async-params, nextjs-16-upgrade).

Load full capability details: Read("references/capability-details.md")

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the React Server Components Framework AI skill do?

Use when building Next.js 16+ apps with React Server Components. Covers App Router, Cache Components (replacing experimental_ppr), streaming SSR, Server Actions, and React 19 patterns for server-first architecture.

Why use React Server Components Framework on TypingMind?

Because you install it once and use it with any model. React Server Components Framework is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install React Server Components Framework in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/yonatangross/orchestkit/tree/main/plugins/ork/skills/react-server-components-framework. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use React Server Components Framework?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with React Server Components Framework?

As many as you like. As long as a model supports skills, you can use React Server Components Framework with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the React Server Components Framework AI skill free?

Yes. It is published on GitHub by yonatangross under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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