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Render Props Pattern

Organization
PatternsDev
render-props-pattern

Teaches the render props pattern for flexible component composition. Use when you need to share rendering logic between components by passing a function that returns JSX as a prop.

Overview

PublisherPatternsDev
Repositoryskills
Skill namerender-props-pattern
Stars
250
Forks
27
Bundled files
Instructions only
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.

  • Self-contained

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

  • Open source

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

Installation

Install the Render Props Pattern 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/PatternsDev/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/react/render-props-pattern .claude/skills/render-props-pattern
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Render Props Pattern 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 Render Props Pattern 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 Render Props Pattern 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.

Render Props Pattern

Table of Contents

Another way of making components very reusable, is by using the render prop pattern. A render prop is a prop on a component, which value is a function that returns a JSX element. The component itself does not render anything besides the render prop. Instead, the component simply calls the render prop, instead of implementing its own rendering logic.

Imagine that we have a Title component. In this case, the Title component shouldn't do anything besides rendering the value that we pass. We can use a render prop for this! Let's pass the value that we want the Title component to render to the render prop.

When to Use

  • Use this when you need to share stateful logic between components with different rendering needs
  • This is helpful when the HOC pattern creates naming collision issues or overly deep nesting

When NOT to Use

  • When custom hooks can replace the pattern — hooks provide the same logic reuse without render prop nesting
  • When it creates deeply nested JSX that becomes hard to read and maintain
  • When the shared logic is simple enough for a plain utility function or hook

Instructions

  • Pass a function as a render prop (or children prop) that receives data and returns JSX
  • Prefer custom Hooks over render props in most modern React code
  • Use the children-as-a-function pattern as a cleaner alternative to explicit render props
  • Avoid deeply nesting multiple render prop components — refactor to Hooks instead

Details

js
<Title render={() => <h1>I am a render prop!</h1>} />

Within the Title component, we can render this data by returning the invoked render prop!

js
const Title = (props) => props.render();

Although they're called render props, a render prop doesn't have to be called render. Any prop that renders JSX is considered a render prop!

A component that takes a render prop usually does a lot more than simply invoking the render prop. Instead, we usually want to pass data from the component that takes the render prop, to the element that we pass as a render prop!

js
function Component(props) {
  const data = { ... }

  return props.render(data)
}

The render prop can now receive this value that we passed as its argument.

js
<Component render={data => <ChildComponent data={data} />}

Let's look at an example! We have a simple app, where a user can type a temperature in Celsius. The app shows the value of this temperature in Fahrenheit and Kelvin.

Currently there's a problem. The stateful Input component contains the value of the user's input, meaning that the Fahrenheit and Kelvin component don't have access to the user's input!

Lifting state

One way to make the users input available to both the Fahrenheit and Kelvin component is to lift the state.

In this case, we have a stateful Input component. However, the sibling components Fahrenheit and Kelvin also need access to this data. Instead of having a stateful Input component, we can lift the state up to the first common ancestor component that has a connection to Input, Fahrenheit and Kelvin: the App component in this case!

js
function Input({ value, handleChange }) {
  return <input value={value} onChange={(e) => handleChange(e.target.value)} />;
}

export default function App() {
  const [value, setValue] = useState("");

  return (
    <div className="App">
      <h1>☃️ Temperature Converter 🌞</h1>
      <Input value={value} handleChange={setValue} />
      <Kelvin value={value} />
      <Fahrenheit value={value} />
    </div>
  );
}

Although this is a valid solution, it can be tricky to lift state in larger applications with components that handle many children. Each state change could cause a re-render of all the children, even the ones that don't handle the data, which could negatively affect the performance of your app.

Render props

Instead, we can use render props! Let's change the Input component in a way that it can receive render props.

js
function Input(props) {
  const [value, setValue] = useState("");

  return (
    <>
      <input
        type="text"
        value={value}
        onChange={(e) => setValue(e.target.value)}
        placeholder="Temp in °C"
      />
      {props.render(value)}
    </>
  );
}

export default function App() {
  return (
    <div className="App">
      <h1>☃️ Temperature Converter 🌞</h1>
      <Input
        render={(value) => (
          <>
            <Kelvin value={value} />
            <Fahrenheit value={value} />
          </>
        )}
      />
    </div>
  );
}

Perfect, the Kelvin and Fahrenheit components now have access to the value of the user's input!

Children as a function

Besides regular JSX components, we can pass functions as children to React components. This function is available to us through the children prop, which is technically also a render prop.

Let's change the Input component. Instead of explicitly passing the render prop, we'll just pass a function as a child for the Input component.

js
export default function App() {
  return (
    <div className="App">
      <h1>☃️ Temperature Converter 🌞</h1>
      <Input>
        {(value) => (
          <>
            <Kelvin value={value} />
            <Fahrenheit value={value} />
          </>
        )}
      </Input>
    </div>
  );
}

We have access to this function, through the props.children prop that's available on the Input component. Instead of calling props.render with the value of the user input, we'll call props.children with the value of the user input.

js
function Input(props) {
  const [value, setValue] = useState("");

  return (
    <>
      <input
        type="text"
        value={value}
        onChange={(e) => setValue(e.target.value)}
        placeholder="Temp in °C"
      />
      {props.children(value)}
    </>
  );
}

Great, this way the Kelvin and Fahrenheit component have access to the value, without having to worry about the name of the render prop.

Hooks

In some cases, we can replace render props with Hooks. A good example of this is Apollo Client.

One way to use Apollo Client is through the Mutation and Query components. In order to pass data down from the Mutation component to the elements that need the data, we pass a function as a child. The function receives the value of the data through its arguments.

js
<Mutation mutation={...} variables={...}>
  {addMessage => <div className="input-row">...</div>}
</Mutation>

Although we can still use the render prop pattern and is often preferred compared to the higher order component pattern, it has its downsides.

One of the downsides is deep component nesting. We can nest multiple Mutation or Query components, if a component needs access to multiple mutations or queries.

js
<Mutation mutation={FIRST_MUTATION}>
  {(firstMutation) => (
    <Mutation mutation={SECOND_MUTATION}>
      {(secondMutation) => (
        <Mutation mutation={THIRD_MUTATION}>
          {(thirdMutation) => (
            <Element
              firstMutation={firstMutation}
              secondMutation={secondMutation}
              thirdMutation={thirdMutation}
            />
          )}
        </Mutation>
      )}
    </Mutation>
  )}
</Mutation>

After the release of Hooks, Apollo added Hooks support to the Apollo Client library. Instead of using the Mutation and Query render props, developers can now directly access the data through the hooks that the library provides.

By using the useQuery hook, we reduced the amount of code that was needed in order to provide the data to the component.

Pros

Sharing logic and data among several components is easy with the render props pattern. Components can be made very reusable, by using a render or children prop. Although the Higher Order Component pattern mainly solves the same issues, namely reusability and sharing data, the render props pattern solves some of the issues we could encounter by using the HOC pattern.

The issue of naming collisions that we can run into by using the HOC pattern no longer applies by using the render props pattern, since we don't automatically merge props. We explicitly pass the props down to the child components, with the value provided by the parent component.

Since we explicitly pass props, we solve the HOC's implicit props issue. The props that should get passed down to the element, are all visible in the render prop's arguments list. This way, we know exactly where certain props come from.

We can separate our app's logic from rendering components through render props. The stateful component that receives a render prop can pass the data onto stateless components, which merely render the data.

Cons

The issues that we tried to solve with render props, have largely been replaced by React Hooks. As Hooks changed the way we can add reusability and data sharing to components, they can replace the render props pattern in many cases.

Since we can't add lifecycle methods to a render prop, we can only use it on components that don't need to alter the data they receive.

Source

References

Frequently asked questions

What does the Render Props Pattern AI skill do?

Teaches the render props pattern for flexible component composition. Use when you need to share rendering logic between components by passing a function that returns JSX as a prop.

Why use Render Props Pattern on TypingMind?

Because you install it once and use it with any model. Render Props Pattern 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 Render Props Pattern in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/PatternsDev/skills/tree/main/react/render-props-pattern. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Render Props Pattern?

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 Render Props Pattern?

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

Is the Render Props Pattern AI skill free?

Yes. It is published on GitHub by PatternsDev 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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