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Solid

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openclaw
solid

Write, port, review, or test Solid 2 UI in OpenClaw (Control UI, plugin views, Canvas hosts), including state ownership, Lit interop during the migration, native overlays, testing, performance, and lessons learned.

Overview

Publisheropenclaw
Repositoryopenclaw
Skill namesolid
Stars
391.7K
Forks
82.4K
Bundled files
9
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.

  • 9 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 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.
    https://github.com/openclaw/openclaw/tree/main/.agents/skills/solid
  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/solid .claude/skills/solid
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable 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 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 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.

Solid 2 in OpenClaw

The Control UI, plugin views (extensions/x, extensions/workboard), and the Canvas A2UI hosts render with Solid 2 (solid-js, @solidjs/web, @solidjs/signals, compiled by @solidjs/vite-plugin/@solidjs/compiler). Lit 3 and Web Awesome are being removed. Until the last Lit file is gone, ported Solid code runs next to unported Lit at every commit.

Read ui/AGENTS.md first; its state-ownership rules apply to Solid unchanged. Use the exact installed Solid pins from the owning package.json. Dependencies follow the repository's seven-day release-age gate.

Rules that keep the UI correct

  1. Domain owners stay plain TypeScript. The Gateway store, capabilities, lib/sessions/*, caches, persistence, and mutation authority keep synchronous mutate-then-read semantics. Solid 2 writes become visible only after a microtask flush, so authoritative state never lives in a signal. → state and ownership
  2. Components consume projections from ui/src/lib/reactive/ (one per owner and scope, never a second store) and useApplication() for the application context.
  3. Host tags and classes survive. A component renders its existing openclaw-* tag as a plain host element in light DOM; CSS and E2E select it. Never rename a tag or a class. → components
  4. One implementation per registered tag. A Solid component must never render a tag that a Lit class still registers. When you port a custom element, delete its Lit class; remaining Lit callers reach the Solid version through defineSolidBridge. → Lit interop
  5. One renderer per DOM region, and one lifecycle owner per overlay surface. → overlays
  6. Derive, don't synchronize. createMemo before createSignal; no copies of owner state; no defensive guards for states the owner already excludes. Prefer smaller code than the Lit you replace.

Component skeleton

An illustrative component (the tag is an example): it renders its host tag, reads an owner through a projection, and derives instead of copying state.

tsx
import { createMemo, Show } from "solid-js";
import { useApplication } from "../lib/reactive/context.ts";
import { projectAgents } from "../lib/reactive/domain-capabilities.ts";

export function AgentCount(props: { compact?: boolean }) {
  const app = useApplication();
  // Reads through to the synchronous owner; disposed with this component's owner.
  const agents = projectAgents(app.agents);
  // Never destructure props: reads must stay reactive.
  const count = createMemo(() => agents.read().agentsList?.agents.length ?? 0);
  return (
    <openclaw-agent-count class={["agent-count", { "agent-count--compact": props.compact }]}>
      <Show when={count() > 0} fallback={<span class="muted">—</span>}>
        <span>{count()}</span>
      </Show>
    </openclaw-agent-count>
  );
}

Use jsxImportSource: "@solidjs/web" and its JSX types, not Solid 1's solid-js/web.

Traps that compile but break

  • on:x, attr:x, bool:x, classList, and use: are gone in Solid 2; they compile to literal attributes or no-ops (lint flags them). prop: is the only namespace left.
  • Events are camelCase (onClick). onWaSelect listens to waselect; dashed custom events need onWa-select or a listen(...) ref factory.
  • A read right after a write sees the old value until flush(). Don't write-then-read in handlers; derive.
  • Reactive reads after the first await in an async memo are untracked, and async memos get no AbortSignal.
  • Ref callbacks run unowned: onCleanup inside them does nothing.
  • ARIA enumerations are typed strings: aria-pressed={pressed() ? "true" : "false"}, never a boolean.
  • Solid 1 APIs (createResource, onMount, mergeProps, Context.Provider) don't carry over: use async computations, onSettled, merge, and the context component itself.

More, each with its root cause: lessons learned.

Testing

mountSolid, waitForSolid/flush, renderSolidRef, and the Solid application-context provider live in ui/src/test-helpers/. .test.tsx files are discovered. Keep assertions when you replace a harness. Visual changes need pnpm ui:parity or inspected before/after screenshots. → testing

References

TopicRead when
componentsporting or writing components: Lit → Solid table, JSX bindings, events, refs, styles
state and ownershiptouching owners, projections, async reads, lifetimes, parking, chat render lifecycle
Lit interopa Lit caller uses your component, or your component hosts unported Lit
overlaysmenus, popovers, tooltips, dialogs, focus, positioning, the platform floor
testingunit, browser, E2E, WebKit, parity, retention suites
performancestartup bundle, lazy loading, render budgets
pluginsbuilding a plugin's Control UI view in Solid
migrationporting the remaining Lit, the final sweep, the inventory
lessons learnedbefore a new kind of change; most entries cost a failed CI run to learn

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 Solid AI skill do?

Write, port, review, or test Solid 2 UI in OpenClaw (Control UI, plugin views, Canvas hosts), including state ownership, Lit interop during the migration, native overlays, testing, performance, and lessons learned.

Why use Solid on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/openclaw/openclaw/tree/main/.agents/skills/solid. 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 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 Solid?

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

Is the Solid AI skill free?

Yes. It is published on GitHub by openclaw 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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