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Markstream Vue

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Simon-He95
markstream-vue

Integrate markstream-vue into a Vue 3 app. Use when Codex needs to add the Vue 3 renderer, import CSS in the right order, choose renderer and DOM modes, choose built-in, plain, or custom code-block paths, choose between `content` and `nodes`, coordinate long AI timelines with `MarkstreamVirtualTimeline`, `useMarkstreamVirtualAdapter`, or `vue-virtual-scroller`, enable optional peers such as stream-diffs, Mermaid, KaTeX, D2, or Infographic, or wire scoped custom components in a non-Nuxt Vue repository.

Overview

PublisherSimon-He95
Repositorymarkstream-vue
Skill namemarkstream-vue
Stars
3K
Forks
188
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

    Published by Simon-He95 on GitHub. Read the source before you install it.

Installation

Install the Markstream Vue 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/Simon-He95/markstream-vue/tree/main/.agents/skills/markstream-vue
  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/Simon-He95/markstream-vue.git /tmp/markstream-vue
mkdir -p .claude/skills
cp -r /tmp/markstream-vue/.agents/skills/markstream-vue .claude/skills/markstream-vue
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Markstream Vue 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 Markstream Vue 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 Markstream Vue 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.

Markstream Vue 3

Use this skill when the host app is plain Vue 3, typically Vite-based, and not Nuxt.

Workflow

  1. Confirm the repo is Vue 3 and not Nuxt.
  2. Install markstream-vue plus only the optional peers required by the requested features.
  3. Import markstream-vue/index.css after resets.
    • In Tailwind or UnoCSS projects, use @import 'markstream-vue/index.css' layer(components);.
    • The root JS import does not inject styles; use markstream-vue/index.css or markstream-vue/index.px.css explicitly.
  4. Start with content and choose the renderer mode by surface.
    • Use mode="chat" for AI chat or SSE output. It uses lightweight batches, fade=false, and max-live-nodes=0; smooth-streaming="auto" paces visible output.
    • Use mode="docs" for rich document surfaces. It is the default and enables larger batches, tooltips, and fade.
    • Use mode="minimal" when the surface is lightweight but not chat.
    • Regular fenced code uses the built-in CodeBlockNode, enhanced by stream-diffs when that optional peer is installed and otherwise falling back to <pre><code>. Set render-code-blocks-as-pre=true to force the plain path, or replace code_block through scoped setCustomComponents(...) when the app owns the renderer.
    • Use dom-mode="minimal" only when the surface can also disable wrapper-dependent features such as fade, batching, deferral, virtualization, typewriter, and custom components; otherwise it falls back to full DOM.
    • typewriter only controls the blinking cursor and defaults to false. Prefer typewriter="simple" for high-frequency chat and precise mode for complex inline cursor placement.
    • Set :smooth-streaming="false" to preserve raw chunk cadence; set :smooth-streaming="true" to force smooth pacing even on first-screen content (may cause hydration mismatch in SSR).
    • In Vue 3 (including Nuxt), smooth-streaming controls output pacing and fade controls opacity; they can be enabled together. mode="chat" keeps fade=false as a lightweight default. Add fade when gradual text reveal is desired; keep it off when animation cost matters more. Vue 3 append fades use stable batches (200 ms, 50 ms coalescing window, at most four batches per text node); later appends do not restart earlier batches.
    • Streaming vs recovering history: in chat UIs the same MarkdownRender starts streaming and later switches to history when final=true.
      • Streaming: start with mode="chat" and final; add fade for text reveal and typewriter only when a cursor is wanted.
      • Recovering/completed chat history: keep mode="chat" on the same chat row to avoid switching layout strategy when final=true; use :smooth-streaming="false", typewriter=false, and choose fade independently for the desired entry/reveal effect. Do not bind it to the inverse of streaming state unless that visual policy is intentional.
      • Use mode="minimal" for lightweight non-chat recovered content, and use mode="docs" only for rich document surfaces, not for finalizing an existing chat message.
    • Switch to nodes plus final only when the app needs custom AST control, worker preparsing, or structural updates beyond pacing.
    • Remember that html-policy now defaults to safe, and Mermaid strict mode is on by default through mermaid-props.
  5. For long AI transcripts or existing message virtualizers, choose the virtual-scroll path.
    • Prefer MarkstreamVirtualTimeline when the app does not already own timeline virtualization.
    • If the app already uses vue-virtual-scroller DynamicScroller, use useMarkstreamVirtualAdapter() and bind adapter.markdownProps(item, index) to Markdown items.
    • Put adapter.measureItem(item, index, el) on the outer timeline row so row chrome is included in item height.
    • Use Markstream's reported logical height (metrics.totalHeight through the adapter/virtualizer), not the renderer element's current offsetHeight, because Markdown node virtualization may only mount the live window.
    • On thread switches, save adapter.captureThreadState() together with the scroller cache; restore the scroller cache before restoring the Markstream anchor.
  6. Use custom-id plus scoped setCustomComponents(...) for local overrides, or import { VueRendererMarkdown } from markstream-vue and install it when the repo already has an app-level plugin entry.
  7. Validate with the smallest useful dev, build, or typecheck command.

Default Decisions

  • Vue 3 apps default to content; choose mode before fine-tuning lower-level render props.
  • Omit mode only when the surface should use rich docs defaults.
  • Smooth streaming (smooth-streaming="auto") is on by default when typewriter or max-live-nodes <= 0. It only paces the content path; nodes mode is never affected.
  • For manual pacing with nodes, use useSmoothMarkdownStream directly: enqueue() chunks, finish() when done, render from visible, and wait for caughtUp before final parsing.
  • For a non-virtual chat scroller that should follow streaming output, import useStickToBottom from markstream-vue/utils and call scheduleScrollToBottom() after Vue commits new content. It coalesces writes and preserves manual scrollback; do not run scrollIntoView({ behavior: 'smooth' }) for every token. For long mixed timelines, use MarkstreamVirtualTimeline with stick-to-bottom="auto" instead.
  • Streaming vs recovering history: keep the same renderer mode for a given chat row; completed history can disable pacing/cursor; fade is an independent visual choice and may remain enabled throughout streaming and completion. Switch to mode="docs" only when moving content into a separate rich document surface. See docs/guide/ai-chat-streaming.md for full examples.
  • Prefer local component registration unless the repo already uses a shared plugin entry.
  • If a Vue 3 app already virtualizes messages, keep that outer virtualizer in charge and enable virtual-scroll only on large Markdown messages.
  • For vue-virtual-scroller, keep sessionKey tied to content identity (thread:item:revision) and measurementKey tied to layout identity such as width, theme, font, and density.
  • When enhanced code blocks need app-level preloading, use preloadCodeBlockRuntime. For intentional low-level controller use, import the advanced API directly from stream-diffs; do not depend on a raw-runtime getter from markstream-vue.
  • The Vue 3 enhanced code surface uses stream-diffs only; do not install stream-monaco.
  • For large code blocks (tens of thousands of lines) in Vue 3, offload Shiki tokenization to Web Workers by injecting an upstream @pierre/diffs WorkerPoolManager via setStreamDiffsWorkerPool(...) from markstream-vue. The host builds the pool with its own bundler (@pierre/diffs/worker/worker.js?worker) and adds @pierre/diffs as a direct dependency; markstream-vue forwards it as the workerManager runtime option and syncs the active isDark/theme/themes theme to the pool on every change. Without injection, or when the pool reports itself unavailable, highlighting stays on the main thread (unchanged behavior). Do not bundle or spawn the worker inside the library.
  • Configure the built-in surface through top-level code-block-options or direct CodeBlockNode.codeBlockOptions. Keep header/toolbar props in code-block-props; Markstream retains ownership of theme, code/language, streaming lifecycle, header, mount/reveal timing, and disposal.
  • Keep html-policy="safe" and Mermaid strict mode unless the task is explicitly preserving trusted legacy behavior.
  • If a trusted surface needs pre-hardening behavior, opt out locally with html-policy="trusted" and :mermaid-props="{ isStrict: false }", and call out the trust boundary in the final handoff.
  • If the host is actually Nuxt, leave SSR-specific setup to markstream-nuxt.

Useful Doc Targets

  • docs/guide/quick-start.md
  • docs/guide/installation.md
  • docs/guide/usage.md
  • docs/guide/ai-chat-streaming.md
  • docs/guide/performance.md
  • docs/guide/component-overrides.md
  • docs/guide/code-block-runtime.md

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 Markstream Vue AI skill do?

Integrate markstream-vue into a Vue 3 app. Use when Codex needs to add the Vue 3 renderer, import CSS in the right order, choose renderer and DOM modes, choose built-in, plain, or custom code-block paths, choose between `content` and `nodes`, coordinate long AI timelines with `MarkstreamVirtualTimeline`, `useMarkstreamVirtualAdapter`, or `vue-virtual-scroller`, enable optional peers such as stream-diffs, Mermaid, KaTeX, D2, or Infographic, or wire scoped custom components in a non-Nuxt Vue repository.

Why use Markstream Vue on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Simon-He95/markstream-vue/tree/main/.agents/skills/markstream-vue. 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 Markstream Vue?

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 Markstream Vue?

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

Is the Markstream Vue AI skill free?

Yes. It is published on GitHub by Simon-He95 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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