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Ink

OrganizationPopular
vercel-labs
ink

Ink terminal renderer for json-render that turns JSON specs into interactive terminal UIs. Use when working with @json-render/ink, building terminal UIs from JSON, creating terminal component catalogs, or rendering AI-generated specs in the terminal.

Overview

Publishervercel-labs
Repositoryjson-render
Skill nameink
Stars
16.5K
Forks
887
Bundled files
Instructions only
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.

  • Self-contained

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

  • Open source

    Published by vercel-labs on GitHub. Read the source before you install it.

Installation

Install the Ink 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/vercel-labs/json-render.git /tmp/json-render
mkdir -p .claude/skills
cp -r /tmp/json-render/skills/ink .claude/skills/ink
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ink 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 Ink 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 Ink 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.

@json-render/ink

Ink terminal renderer that converts JSON specs into interactive terminal component trees with standard components, data binding, visibility, actions, and dynamic props.

Quick Start

typescript
import { defineCatalog } from "@json-render/core";
import { schema } from "@json-render/ink/schema";
import {
  standardComponentDefinitions,
  standardActionDefinitions,
} from "@json-render/ink/catalog";
import { defineRegistry, Renderer, type Components } from "@json-render/ink";
import { z } from "zod";

// Create catalog with standard + custom components
const catalog = defineCatalog(schema, {
  components: {
    ...standardComponentDefinitions,
    CustomWidget: {
      props: z.object({ title: z.string() }),
      slots: [],
      description: "Custom widget",
    },
  },
  actions: standardActionDefinitions,
});

// Register only custom components (standard ones are built-in)
const { registry } = defineRegistry(catalog, {
  components: {
    CustomWidget: ({ props }) => <Text>{props.title}</Text>,
  } as Components<typeof catalog>,
});

// Render
function App({ spec }) {
  return (
    <JSONUIProvider initialState={{}}>
      <Renderer spec={spec} registry={registry} />
    </JSONUIProvider>
  );
}

Spec Structure (Flat Element Map)

The Ink schema uses a flat element map with a root key:

json
{
  "root": "main",
  "elements": {
    "main": {
      "type": "Box",
      "props": { "flexDirection": "column", "padding": 1 },
      "children": ["heading", "content"]
    },
    "heading": {
      "type": "Heading",
      "props": { "text": "Dashboard", "level": "h1" },
      "children": []
    },
    "content": {
      "type": "Text",
      "props": { "text": "Hello from the terminal!" },
      "children": []
    }
  }
}

Standard Components

Layout

  • Box - Flexbox layout container (like a terminal <div>). Use for grouping, spacing, borders, alignment. Default flexDirection is row.
  • Text - Text output with optional styling (color, bold, italic, etc.)
  • Newline - Inserts blank lines. Must be inside a Box with flexDirection column.
  • Spacer - Flexible empty space that expands along the main axis.

Content

  • Heading - Section heading (h1: bold+underlined, h2: bold, h3: bold+dimmed, h4: dimmed)
  • Divider - Horizontal separator with optional centered title
  • Badge - Colored inline label (variants: default, info, success, warning, error)
  • Spinner - Animated loading spinner with optional label
  • ProgressBar - Horizontal progress bar (0-1)
  • Sparkline - Inline chart using Unicode block characters
  • BarChart - Horizontal bar chart with labels and values
  • Table - Tabular data with headers and rows
  • List - Bulleted or numbered list
  • ListItem - Structured list row with title, subtitle, leading/trailing text
  • Card - Bordered container with optional title
  • KeyValue - Key-value pair display
  • Link - Clickable URL with optional label
  • StatusLine - Status message with colored icon (info, success, warning, error)
  • Markdown - Renders markdown text with terminal styling

Interactive

  • TextInput - Text input field (events: submit, change)
  • Select - Selection menu with arrow key navigation (events: change)
  • MultiSelect - Multi-selection with space to toggle (events: change, submit)
  • ConfirmInput - Yes/No confirmation prompt (events: confirm, deny)
  • Tabs - Tab bar navigation with left/right arrow keys (events: change)

Visibility Conditions

Use visible on elements to show/hide based on state. Syntax: { "$state": "/path" }, { "$state": "/path", "eq": value }, { "$state": "/path", "not": true }, { "$and": [cond1, cond2] } for AND, { "$or": [cond1, cond2] } for OR.

Dynamic Prop Expressions

Any prop value can be a data-driven expression resolved at render time:

  • { "$state": "/state/key" } - reads from state model (one-way read)
  • { "$bindState": "/path" } - two-way binding: use on the natural value prop of form components
  • { "$bindItem": "field" } - two-way binding to a repeat item field
  • { "$cond": <condition>, "$then": <value>, "$else": <value> } - conditional value
  • { "$template": "Hello, ${/name}!" } - interpolates state values into strings

Components do not use a statePath prop for two-way binding. Use { "$bindState": "/path" } on the natural value prop instead.

Event System

Components use emit to fire named events. The element's on field maps events to action bindings:

tsx
CustomButton: ({ props, emit }) => (
  <Box>
    <Text>{props.label}</Text>
    {/* emit("press") triggers the action bound in the spec's on.press */}
  </Box>
),
json
{
  "type": "CustomButton",
  "props": { "label": "Submit" },
  "on": { "press": { "action": "submit" } },
  "children": []
}

Built-in Actions

setState, pushState, and removeState are built-in and handled automatically:

json
{ "action": "setState", "params": { "statePath": "/activeTab", "value": "home" } }
{ "action": "pushState", "params": { "statePath": "/items", "value": { "text": "New" } } }
{ "action": "removeState", "params": { "statePath": "/items", "index": 0 } }

Repeat (Dynamic Lists)

Use the repeat field on a container element to render items from a state array:

json
{
  "type": "Box",
  "props": { "flexDirection": "column" },
  "repeat": { "statePath": "/items", "key": "id" },
  "children": ["item-row"]
}

Inside repeated children, use { "$item": "field" } to read from the current item and { "$index": true } for the current index.

For nested lists, an inner repeat can use { "statePath": { "$item": "children" } } to iterate an array on the enclosing item.

Streaming

Use useUIStream to progressively render specs from JSONL patch streams:

tsx
import { useUIStream } from "@json-render/ink";

const { spec, send, isStreaming } = useUIStream({ api: "/api/generate" });

Server-Side Prompt Generation

Use the ./server export to generate AI system prompts from your catalog:

typescript
import { catalog } from "./catalog";

const systemPrompt = catalog.prompt({ system: "You are a terminal assistant." });

Providers

ProviderPurpose
StateProviderShare state across components (JSON Pointer paths). Accepts optional store prop for controlled mode.
ActionProviderHandle actions dispatched via the event system
VisibilityProviderEnable conditional rendering based on state
ValidationProviderForm field validation
FocusProviderManage focus across interactive components
JSONUIProviderCombined provider for all contexts

External Store (Controlled Mode)

Pass a StateStore to StateProvider (or JSONUIProvider) to use external state management:

tsx
import { createStateStore, type StateStore } from "@json-render/ink";

const store = createStateStore({ count: 0 });

<StateProvider store={store}>{children}</StateProvider>

store.set("/count", 1); // React re-renders automatically

When store is provided, initialState and onStateChange are ignored.

createRenderer (Higher-Level API)

tsx
import { createRenderer } from "@json-render/ink";
import { standardComponents } from "@json-render/ink";
import { catalog } from "./catalog";

const InkRenderer = createRenderer(catalog, {
  ...standardComponents,
  // custom component overrides here
});

// InkRenderer includes all providers (state, visibility, actions, focus)
render(
  <InkRenderer spec={spec} state={{ activeTab: "overview" }} />
);

Key Exports

ExportPurpose
defineRegistryCreate a type-safe component registry from a catalog
RendererRender a spec using a registry
createRendererHigher-level: creates a component with built-in providers
JSONUIProviderCombined provider for all contexts
schemaInk flat element map schema (includes built-in state actions)
standardComponentDefinitionsCatalog definitions for all standard components
standardActionDefinitionsCatalog definitions for standard actions
standardComponentsPre-built component implementations
useStateStoreAccess state context
useStateValueGet single value from state
useBoundPropTwo-way binding for $bindState/$bindItem expressions
useActionsAccess actions context
useActionGet a single action dispatch function
useOptionalValidationNon-throwing variant of useValidation
useUIStreamStream specs from an API endpoint
createStateStoreCreate a framework-agnostic in-memory StateStore
StateStoreInterface for plugging in external state management
ComponentsTyped component map (catalog-aware)
ActionsTyped action map (catalog-aware)
ComponentContextTyped component context (catalog-aware)
flatToTreeConvert flat element map to tree structure

Terminal UI Design Guidelines

  • Use Box for layout (flexDirection, padding, gap). Default flexDirection is row.
  • Terminal width is ~80-120 columns. Prefer vertical layouts (flexDirection: column) for main structure.
  • Use borderStyle on Box for visual grouping (single, double, round, bold).
  • Use named terminal colors: red, green, yellow, blue, magenta, cyan, white, gray.
  • Use Heading for section titles, Divider to separate sections, Badge for status, KeyValue for labeled data, Card for bordered groups.
  • Use Tabs for multi-view UIs with visible conditions on child content.
  • Use Sparkline for inline trends and BarChart for comparing values.

Frequently asked questions

What does the Ink AI skill do?

Ink terminal renderer for json-render that turns JSON specs into interactive terminal UIs. Use when working with @json-render/ink, building terminal UIs from JSON, creating terminal component catalogs, or rendering AI-generated specs in the terminal.

Why use Ink on TypingMind?

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

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

Which AI models can use Ink?

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 Ink?

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

Is the Ink AI skill free?

Yes. It is published on GitHub by vercel-labs 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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