Devtools Solid logo

Devtools Solid

OrganizationPopular
vercel-labs
devtools-solid

SolidJS adapter for the json-render devtools inspector. Use whenever the user wants to add, configure, or troubleshoot @json-render/devtools-solid in a SolidJS json-render app, including spec inspection, state editing, action and stream timelines, catalog browsing, or DOM picking.

Overview

Publishervercel-labs
Repositoryjson-render
Skill namedevtools-solid
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 Devtools Solid 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/devtools-solid .claude/skills/devtools-solid
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Devtools Solid 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 Devtools Solid 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 Devtools Solid 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/devtools-solid

SolidJS adapter for the json-render devtools panel. Read skills/devtools/SKILL.md for the shared panel capabilities, props, docking behavior, and server-side stream taps.

Install

bash
npm install @json-render/devtools @json-render/devtools-solid

Mount the panel

Mount JsonRenderDevtools inside the existing SolidJS json-render provider:

tsx
import { JsonRenderDevtools } from "@json-render/devtools-solid";

<JSONUIProvider registry={registry}>
  <Renderer spec={spec()} registry={registry} />
  <JsonRenderDevtools
    spec={spec()}
    catalog={catalog}
    messages={messages()}
  />
</JSONUIProvider>;

The component renders nothing in production builds. The panel provides the shared devtools controls, including the Ctrl/Cmd + Shift + J shortcut. Keep server-side stream instrumentation in @json-render/devtools.

Frequently asked questions

What does the Devtools Solid AI skill do?

SolidJS adapter for the json-render devtools inspector. Use whenever the user wants to add, configure, or troubleshoot @json-render/devtools-solid in a SolidJS json-render app, including spec inspection, state editing, action and stream timelines, catalog browsing, or DOM picking.

Why use Devtools Solid on TypingMind?

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

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

Which AI models can use Devtools Solid?

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 Devtools Solid?

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

Is the Devtools Solid 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇