Cache Components logo

Cache Components

Organization
Asymmetric-al
cache-components

Build correct cached/dynamic boundaries in the Next.js App Router when Cache Components or PPR are enabled. Use when working with cacheComponents, Partial Prerendering (PPR), 'use cache', cacheLife, cacheTag, updateTag, or revalidateTag, to avoid request-context leaks and enforce proper cache invalidation. Not for the Pages Router or when Cache Components/PPR are off.

Overview

PublisherAsymmetric-al
Repositorycore
Skill namecache-components
Stars
383
Forks
7
Bundled files
Instructions only
LicenseAGPL-3.0
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Asymmetric-al on GitHub. Read the source before you install it.

Installation

Install the Cache Components 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.
  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/Asymmetric-al/core.git /tmp/core
mkdir -p .claude/skills
cp -r /tmp/core/docs/ai/skills/cache-components .claude/skills/cache-components
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cache Components 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 Cache Components 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 Cache Components 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.

Cache Components (Next.js) — Skill

Name: cache-components Purpose: Build correct cached/dynamic boundaries in Next.js App Router when Cache Components or PPR are in use. Use this skill to avoid request-context leaks and to enforce proper cache invalidation.

Applies when: cacheComponents: true, Partial Prerendering (PPR), 'use cache', cacheLife, cacheTag, updateTag, revalidateTag. Do not use when: Working in the Pages Router or when Cache Components/PPR are not enabled.

Rules

  • Cached vs dynamic: Shared data should be cached; request/user-specific data must be dynamic and streamed behind <Suspense>.
  • No request context inside cache: Never call cookies(), headers(), or auth/session inside a 'use cache' scope.
  • Cached functions must be async: Any 'use cache' function/component must be async.
  • Prefer code-local caching: Favor 'use cache', cacheLife, cacheTag over route-segment config (revalidate, dynamic).
  • Mutations must invalidate tags: Use updateTag for immediate consistency or revalidateTag for background refresh.
  • PPR + generateStaticParams: Do not return empty arrays; keep request-specific logic out of the shell.
  • Instant Navigation (16.3): with partialPrefetching: true, Next.js prefetches one reusable shell per route. Every server await is a Stream (<Suspense>) / Cache ('use cache') / Block (export const instant = false + reason comment) decision; Instant Insights errors link the canonical fix at nextjs.org/docs/messages/... — apply that pattern, don't improvise.
  • Prefetch escalation: <Link prefetch={true}> extends prefetching to build-time-known cached content on that link; export const prefetch = 'allow-runtime' extends it to request-time cached content and requires PR justification.

Workflow

  1. Classify each data dependency as shared or request-specific.
  2. For shared data, add 'use cache' + cacheTag (and cacheLife if needed).
  3. For request/user-specific data, keep it dynamic and render behind <Suspense>.
  4. Split cached logic from request logic if needed.
  5. Invalidate tags after mutations.

Checklists

Implementation checklist

  • Shared data uses 'use cache'
  • Cached scopes have cacheTag
  • No request data inside cached scopes
  • Dynamic UI is isolated behind <Suspense>
  • Cached functions are async
  • Route stays instant (Stream/Cache), or Blocks explicitly via export const instant = false with a reason
  • Mutations invalidate correct tags

Review checklist

  • Route segment config avoided unless required
  • PPR shells do not include request-specific logic

Minimal examples

Cached function

ts
"use cache";

import { cacheLife, cacheTag } from "next/cache";

export async function getProducts(category: string) {
  cacheLife("minutes");
  cacheTag("products");
  cacheTag(`products:${category}`);
}

Dynamic Suspense boundary

tsx
import { Suspense } from "react";

export default function Page() {
  return (
    <>
      <MainCached />
      <Suspense fallback={null}>
        <UserPanel />
      </Suspense>
    </>
  );
}

Mutation invalidation

ts
"use server";

import { updateTag } from "next/cache";

export async function updateProduct(id: string) {
  updateTag(`product:${id}`);
  updateTag("products");
}

Common mistakes / pitfalls

  • Reading cookies/headers/session inside 'use cache'
  • Missing cache tags on cached functions
  • Rendering request-specific data outside <Suspense>
  • Forgetting to invalidate tags after mutations
  • Returning an empty array from generateStaticParams

Frequently asked questions

What does the Cache Components AI skill do?

Build correct cached/dynamic boundaries in the Next.js App Router when Cache Components or PPR are enabled. Use when working with cacheComponents, Partial Prerendering (PPR), 'use cache', cacheLife, cacheTag, updateTag, or revalidateTag, to avoid request-context leaks and enforce proper cache invalidation. Not for the Pages Router or when Cache Components/PPR are off.

Why use Cache Components on TypingMind?

Because you install it once and use it with any model. Cache Components 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 Cache Components in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Asymmetric-al/core/tree/develop/docs/ai/skills/cache-components. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Cache Components?

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 Cache Components?

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

Is the Cache Components AI skill free?

Yes. It is published on GitHub by Asymmetric-al under the AGPL-3.0 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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