Cxc Dev Visualizer logo

Cxc Dev Visualizer

Community
lidge-jun
cxc-dev-visualizer

Use for visual explanations and documents. Triggers: diagrams, charts, interactive models, HTML reports, infographics, 시각화, 그려줘, 문서 만들어줘, 보고서, PDF 생성.

Overview

Publisherlidge-jun
Repositorycodexclaw
Skill namecxc-dev-visualizer
Stars
51
Forks
10
Bundled files
42
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.

  • 42 bundled files

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

  • Open source

    Published by lidge-jun on GitHub. Read the source before you install it.

Installation

Install the Cxc Dev Visualizer 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/lidge-jun/codexclaw/tree/main/plugins/codexclaw/skills/dev-visualizer
  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/lidge-jun/codexclaw.git /tmp/codexclaw
mkdir -p .claude/skills
cp -r /tmp/codexclaw/plugins/codexclaw/skills/dev-visualizer .claude/skills/cxc-dev-visualizer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cxc Dev Visualizer 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 Cxc Dev Visualizer 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 Cxc Dev Visualizer 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.

Visual documents — compose, render, deliver

Turn the reader's question and supplied facts into a useful visual artifact. Use dev for scope, work class and verification; a document request does not automatically require a development loop. This skill owns artifact composition and delivery. dev-uiux-design owns broader design judgment, dev-frontend owns frontend implementation, and available format-specific skills own document mechanics.

Select a route; read only what it needs

ConditionReference
Every artifact: caller scope and requested outcomeScope, authoring routes
Choosing HTML, SVG, inline output, PDF, document format or scientific plottingAuthoring routes
Before composing/styling/building any visualArtifact composition
Human-readable reports and documentsReader documents, report writing
Research reports, analytical exhibits or English/bilingual outputResearch/language/exhibit routes
Computed/exported tiers, or any artifact in doubtComputed verification
PDF/print/paged report assurance profileReport pipeline
Delivery, borrowing sources or refreshing the skillDelivery and provenance

Verify in proportion to what can break

VIZ-VERIFY-SCALE-01 — the proof matches the failure it would catch. Rendering an artifact and reading the result costs a round trip, and much of what this skill produces cannot fail out of sight: the reader sees an inline visual before a screenshot could reach you, and a static page in normal flow shows its own text. Spend the round trip where the visible result is computed rather than written.

DeliveringBefore delivery
An inline visual in this conversation, or a fenced diagram the host rendersReread the source once and send it. The reader's screen is the render.
A small static HTML/SVG page in ordinary flow — prose, tables, hand-placed shapes, no runtime data, no library, no exportReread the source, save it, return the link.
Anything whose visible result is computed — marks drawn from data, connector geometry derived from rendered bounds, a runtime library or webfont, an input that changes the outputDIAGRAM-RENDER-VERIFY-01 in full.
PDF, print output, or a multi-page paged reportDIAGRAM-RENDER-VERIFY-01 with a stated assurance profile. Merely saving or sharing a simple static HTML/SVG file does not promote it to this tier.

Two rules hold in every tier. An unrun check is never written up as a passed one: "not rendered — static HTML in normal flow" is honest, "verified" is not. And a defect promotes the artifact: once the reader reports something wrong, or a first render shows it, render each further fix before sending it. Nothing here is enforced by a hook, and the calling task's own verification gate still governs its work.

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 Cxc Dev Visualizer AI skill do?

Use for visual explanations and documents. Triggers: diagrams, charts, interactive models, HTML reports, infographics, 시각화, 그려줘, 문서 만들어줘, 보고서, PDF 생성.

Why use Cxc Dev Visualizer on TypingMind?

Because you install it once and use it with any model. Cxc Dev Visualizer 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 Cxc Dev Visualizer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/lidge-jun/codexclaw/tree/main/plugins/codexclaw/skills/dev-visualizer. 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 Cxc Dev Visualizer?

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 Cxc Dev Visualizer?

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

Is the Cxc Dev Visualizer AI skill free?

Yes. It is published on GitHub by lidge-jun 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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