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Visualize

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code-yeongyu
visualize

Builds a self-contained HTML page (chart, table, diagram, dashboard) to show inline in a thread. Use before calling show_html_page, html_preview or html_render, or whenever an answer reads better as a page than as prose.

Overview

Publishercode-yeongyu
Repositoryoh-my-openagent
Skill namevisualize
Stars
70K
Forks
5.7K
Bundled files
Instructions only
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 code-yeongyu on GitHub. Read the source before you install it.

Installation

Install the Visualize 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/code-yeongyu/oh-my-openagent/tree/dev/packages/omo-senpi/skills/visualize
  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/code-yeongyu/oh-my-openagent.git /tmp/oh-my-openagent
mkdir -p .claude/skills
cp -r /tmp/oh-my-openagent/packages/omo-senpi/skills/visualize .claude/skills/visualize
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Visualize 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 Visualize 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 Visualize 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.

Visualize

A page shown inline sits beside a reply, in the reader's theme, and is read in a few seconds. It earns its place only by being clearer than the paragraph it replaces. This skill owns what is particular to such a page. The data work belongs to data-scientist and the design work to frontend: load those skills for their parts instead of improvising them here.

The loop

Do these in order. Never show a page you have not looked at.

  1. Data: load data-scientist. Compute every figure with its engines (DuckDB or Polars), at the grain the reader needs, and follow its references/visualization.md for which chart answers which question. Keep the query: every number on the page must trace back to it.
  2. Design: load frontend. Use it for hierarchy, type, spacing and states. This page's constraints replace its design-system gate: the page brings no palette or fonts of its own and uses the theme the host injects (below).
  3. Build one self-contained page under the constraints below.
  4. Preview and look. Render with html_preview in dark and in light, at the reply's width and at 390 px. Read the screenshot and the console, fix what you see, and preview again. Where html_preview is not offered, open the page file in a browser through the browser skill and capture the same four views.
  5. Show it with show_html_page (OmO) or html_render (other hosts), with the height the preview measured. Then write only what the page does not already say.

Constraints of an inline page

  • No network. Inline every script, style, font and image (data: URIs); the sandbox blocks every request, so a CDN library leaves a blank chart. Draw with hand-written SVG when a library cannot be inlined.
  • Theme from the host. Color only through the injected custom properties: --background, --foreground, --muted, --muted-foreground, --card, --border, --primary, --accent, --destructive, --warning, --success, the series colors --chart-1 to --chart-6, and --font-sans, --font-mono, --radius. They hold in both themes and change live; a literal color does neither. A page opened outside the app gets only a few of them, so give each a fallback for both themes: var(--chart-2, light-dark(#0d9488, #2dd4bf)).
  • Part of the reply, not a card. Fluid width, no outer padding, border or banner. Give charts fixed pixel heights, not heights that scale with the width. A fluid SVG stretched with preserveAspectRatio="none" stretches its text too, so put axis labels in HTML beside it, positioned by percentage.
  • Readable without scripts. On the web a page first renders with scripts off, until the reader presses Run page. Put the figure itself in markup or SVG, and use scripts only for interaction.
  • Traceable. Show how the numbers were computed in a small, muted "How this was computed" block (the query or aggregation), and state caveats near the figure when they change how a number reads: dropped rows, a partial window, a small sample.
  • Designed empty and error states. No data, or a failed query, is stated in the same visual language, never as a blank frame.
  • Links. A link opens only after the reader confirms it in the app, which shows its full address. Keep data out of link addresses.

Before you show it

  • The title states the finding, not the dataset name.
  • Axis labels carry units, numbers use tabular figures and a sensible precision, and nothing clips at 390 px.
  • The series colors separate in both themes, and the console is clean.

Frequently asked questions

What does the Visualize AI skill do?

Builds a self-contained HTML page (chart, table, diagram, dashboard) to show inline in a thread. Use before calling show_html_page, html_preview or html_render, or whenever an answer reads better as a page than as prose.

Why use Visualize on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/code-yeongyu/oh-my-openagent/tree/dev/packages/omo-senpi/skills/visualize. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Visualize?

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 Visualize?

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

Is the Visualize AI skill free?

It is published on GitHub by code-yeongyu. 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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