InputOTP logo

InputOTP

Organization
lynx-family
InputOTP

Build headless, configurable-length OTP, PIN, and verification-code inputs with lynx-ui InputOTP.

Overview

Publisherlynx-family
Repositorylynx-ui
Skill nameInputOTP
Stars
119
Forks
13
Bundled files
15
LicenseApache-2.0
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.

  • 15 bundled files

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

  • Open source

    Published by lynx-family on GitHub. Read the source before you install it.

Installation

Install the InputOTP 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/lynx-family/lynx-ui.git /tmp/lynx-ui
mkdir -p .claude/skills
cp -r /tmp/lynx-ui/packages/lynx-ui-input-otp .claude/skills/InputOTP
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable InputOTP 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 InputOTP 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 InputOTP 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.

lynx-ui InputOTP

Requirements

InputOTP requires Lynx SDK 4.0 or newer.

Core capabilities

InputOTP owns value and keyboard behavior through one hidden native input. Consumers compose the visible interface with InputOTPSlot. It supports:

  • A configurable positive number of numeric, alphabetic, or alphanumeric ASCII characters.
  • Controlled and uncontrolled values.
  • Completion, focus, and blur callbacks.
  • Imperative focus, blur, set, clear, and read methods.
  • Consumer-defined slot layout, separators, masking, caret, themes, and RTL.
  • Typed ui-* state variants and render props without visible package CSS.

Minimal example

tsx
import { useState } from '@lynx-js/react'
import { InputOTP, InputOTPSlot } from '@lynx-js/lynx-ui'

function VerificationCode() {
  const [code, setCode] = useState('')

  return (
    <InputOTP
      autoFocus
      length={6}
      value={code}
      onChange={setCode}
      onComplete={(completeCode) => {
        console.log('verify', completeCode)
      }}
    >
      {Array.from(
        { length: 6 },
        (_, index) => (
          <InputOTPSlot
            key={index}
            index={index}
            className='otp-slot'
          />
        ),
      )}
    </InputOTP>
  )
}

Usage guidance

  • Render one InputOTPSlot for every configured index.
  • Pass a positive integer to length; invalid values fall back to six slots.
  • Use inputType="numeric", "alphabetic", or "alphanumeric" to choose both the native keyboard and accepted ASCII characters.
  • Prefer controlled mode when a parent submits, validates, or resets the value.
  • Use InputOTPRef.clear() to reset an uncontrolled field. In controlled mode, update the value prop from onChange.
  • Treat onComplete as a readiness signal and keep network submission in the parent.
  • Implement masking with the InputOTPSlot render function. The original value remains available to InputOTP callbacks.
  • Insert separator nodes directly between InputOTPSlot children.
  • Use className and style for base slot styling. On the root, target ui-focused, ui-complete, ui-disabled, and ui-invalid. On slots, target ui-focused, ui-filled, ui-complete, ui-disabled, and ui-invalid. Use the slot render function when custom character or caret nodes need their own presentation.
  • Apply direction: rtl to the outer container and let descendants inherit it.

Masked slot example

tsx
<InputOTPSlot index={0}>
  {({ filled }) =>
    filled ? <text></text> : null}
</InputOTPSlot>

Component roles

  • InputOTP: owns the native input, normalized value, callbacks, and context.
  • InputOTPSlot: consumes a zero-based character index and renders either the default character/caret nodes or custom render-prop content.

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 InputOTP AI skill do?

Build headless, configurable-length OTP, PIN, and verification-code inputs with lynx-ui InputOTP.

Why use InputOTP on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/lynx-family/lynx-ui/tree/main/packages/lynx-ui-input-otp. 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 InputOTP?

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 InputOTP?

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

Is the InputOTP AI skill free?

Yes. It is published on GitHub by lynx-family under the Apache-2.0 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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