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Prototype Openclaw Tui

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openclaw
prototype-openclaw-tui

Build throwaway, fixture-driven OpenClaw Clack or Pi TUI prototypes and compare multiple interactive variants side by side in tmux without running the full application or touching live state.

Overview

Publisheropenclaw
Repositoryopenclaw
Skill nameprototype-openclaw-tui
Stars
391K
Forks
82.2K
Bundled files
2
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.

  • 2 bundled files

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

  • Open source

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

Installation

Install the Prototype Openclaw Tui 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/openclaw/openclaw/tree/main/.agents/skills/prototype-openclaw-tui
  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/openclaw/openclaw.git /tmp/openclaw
mkdir -p .claude/skills
cp -r /tmp/openclaw/.agents/skills/prototype-openclaw-tui .claude/skills/prototype-openclaw-tui
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Prototype Openclaw Tui 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 Prototype Openclaw Tui 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 Prototype Openclaw Tui 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.

Prototype OpenClaw TUI

Use this skill to isolate one OpenClaw terminal surface, render it with the real OpenClaw TUI stack, and compare two to six design variants in tmux.

Rules

  • Read the root and scoped AGENTS.md files before editing.
  • Keep the prototype beside the target and name it *.prototype.ts.
  • When iterating on an existing surface, include its current implementation as the first baseline variant with the same fixture data. Only omit the baseline when the user explicitly asks for a greenfield comparison.
  • Use the real OpenClaw renderer, theme, copy, and component where practical.
  • Replace scanning, models, network calls, installs, config writes, SQLite, and other durable effects with deterministic in-memory fixtures.
  • Do not run the full OpenClaw application when the isolated surface is enough.
  • Treat prototype code as throwaway. Do not promote it directly to production.
  • Preserve unrelated and pre-existing worktree changes.

Choose the renderer

  • Wizard, onboarding, configuration, doctor, selection, or progress surface: use createClackPrompter() from src/wizard/clack-prompter.ts.
  • Agent shell, chat, overlay, editor, selector, or src/tui/** component: use @earendil-works/pi-tui and the existing OpenClaw component.

Do not invent a shared Clack/Pi abstraction. They are separate prototype recipes joined only by the tmux comparison loop.

Workflow

  1. Read the target module, its renderer adapter, callers, and adjacent tests.
  2. Create the smallest executable harness that reaches the target surface.
  3. If the surface already exists, make the no-argument invocation render its current implementation unchanged as --variant=baseline.
  4. Add structurally different alternatives behind --variant=<id>, for two to six total variants including the baseline.
  5. Give every variant the same fixture data and terminal dimensions.
  6. Run each variant directly in its own tmux pane. Do not pipe interactive TUI output; tmux must provide the PTY.
  7. Iterate on the harness with the launcher's --refresh mode. Respawn the panes in the existing session; do not kill the session or reopen the user's terminal.
  8. After the user chooses a direction, carry the decision into production code with normal tests and validation. Remove or separately capture the prototype.

Launch the comparison grid

Run the bundled launcher with a session name, repository path, then title and command pairs:

bash
.agents/skills/prototype-openclaw-tui/scripts/launch-tmux-grid.sh \
  --open \
  app-recommendations-prototype "$PWD" \
  "A - Baseline" "node --import tsx src/wizard/setup.app-recommendations.prototype.ts --variant=baseline" \
  "B - Grouped" "node --import tsx src/wizard/setup.app-recommendations.prototype.ts --variant=grouped" \
  "C - Focused" "node --import tsx src/wizard/setup.app-recommendations.prototype.ts --variant=focused"

After editing the prototype, run the same command with --refresh instead of --open. This preserves the tmux session, attached external terminal, window, and first pane while restarting all pane commands and reapplying the grid:

bash
.agents/skills/prototype-openclaw-tui/scripts/launch-tmux-grid.sh \
  --refresh \
  app-recommendations-prototype "$PWD" \
  "A - Baseline" "node --import tsx src/wizard/setup.app-recommendations.prototype.ts --variant=baseline" \
  "B - Grouped" "node --import tsx src/wizard/setup.app-recommendations.prototype.ts --variant=grouped" \
  "C - Focused" "node --import tsx src/wizard/setup.app-recommendations.prototype.ts --variant=focused"

The launcher refuses to replace an existing session unless --refresh is explicitly provided. --open uses the user's .command-associated terminal app on macOS, Windows Terminal from WSL, or the first available Linux launcher from xdg-terminal-exec, $TERMINAL, and x-terminal-emulator. If no supported launcher is available, the tmux session remains ready at equal detached dimensions and the script exits successfully after printing the manual attach command. Attach, then run --refresh once to adopt the terminal's larger dimensions. The same guidance applies if an external terminal opens but does not attach within ten seconds. When invoked from a non-interactive TERM=dumb environment, the launcher removes its inherited NO_COLOR only from prototype pane processes so the external terminal can detect and render its normal colors. Prefer the external terminal over the Codex in-app terminal unless the user asks for the in-app surface. Leave the session running for user review unless asked to stop it.

Handoff

Report:

  • the prototype path and exact run command;
  • the tmux session name and attach command;
  • which effects were replaced with fixtures;
  • available variant ids;
  • whether the prototype changed production code (normally no).

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 Prototype Openclaw Tui AI skill do?

Build throwaway, fixture-driven OpenClaw Clack or Pi TUI prototypes and compare multiple interactive variants side by side in tmux without running the full application or touching live state.

Why use Prototype Openclaw Tui on TypingMind?

Because you install it once and use it with any model. Prototype Openclaw Tui 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 Prototype Openclaw Tui in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/openclaw/openclaw/tree/main/.agents/skills/prototype-openclaw-tui. 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 Prototype Openclaw Tui?

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 Prototype Openclaw Tui?

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

Is the Prototype Openclaw Tui AI skill free?

It is published on GitHub by openclaw. Check the repository for licensing terms. 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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