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Mermaid Visualizer

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axtonliu
mermaid-visualizer

Transform text content into professional Mermaid diagrams for presentations and documentation. Use when users ask to visualize concepts, create flowcharts, or make diagrams from text. Supports process flows, system architectures, comparisons, mindmaps, and more with built-in syntax error prevention.

Overview

Publisheraxtonliu
Repositoryaxton-obsidian-visual-skills
Skill namemermaid-visualizer
Stars
3.6K
Forks
321
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 axtonliu on GitHub. Read the source before you install it.

Installation

Install the Mermaid 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.
  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/axtonliu/axton-obsidian-visual-skills.git /tmp/axton-obsidian-visual-skills
mkdir -p .claude/skills
cp -r /tmp/axton-obsidian-visual-skills/mermaid-visualizer .claude/skills/mermaid-visualizer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mermaid 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 Mermaid 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 Mermaid 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.

Mermaid Visualizer

Overview

Convert text content into clean, professional Mermaid diagrams optimized for presentations and documentation. Automatically handles common syntax pitfalls (list syntax conflicts, subgraph naming, spacing issues) to ensure diagrams render correctly in Obsidian, GitHub, and other Mermaid-compatible platforms.

Quick Start

When creating a Mermaid diagram:

  1. Analyze the content - Identify key concepts, relationships, and flow
  2. Choose diagram type - Select the most appropriate visualization (see Diagram Types below)
  3. Select configuration - Determine layout, detail level, and styling
  4. Generate diagram - Create syntactically correct Mermaid code
  5. Output in markdown - Wrap in proper code fence with optional explanation

Default assumptions:

  • Vertical layout (TB) unless horizontal requested
  • Medium detail level (balanced between simplicity and information)
  • Professional color scheme with semantic colors
  • Obsidian/GitHub compatible syntax

Diagram Types

1. Process Flow (graph TB/LR)

Best for: Workflows, decision trees, sequential processes, AI agent architectures

Use when: Content describes steps, stages, or a sequence of actions

Key features:

  • Swimlanes via subgraph for grouping related steps
  • Arrow labels for transitions
  • Feedback loops and branches
  • Color-coded stages

Configuration options:

  • layout: "vertical" (TB), "horizontal" (LR)
  • detail: "simple" (core steps only), "standard" (with descriptions), "detailed" (with annotations)
  • style: "minimal", "professional", "colorful"

2. Circular Flow (graph TD with circular layout)

Best for: Cyclic processes, continuous improvement loops, agent feedback systems

Use when: Content emphasizes iteration, feedback, or circular relationships

Key features:

  • Central hub with radiating elements
  • Curved feedback arrows
  • Clear cycle indicators

3. Comparison Diagram (graph TB with parallel paths)

Best for: Before/after comparisons, A vs B analysis, traditional vs modern systems

Use when: Content contrasts two or more approaches or systems

Key features:

  • Side-by-side layout
  • Central comparison node
  • Clear differentiation via color/style

4. Mindmap

Best for: Hierarchical concepts, knowledge organization, topic breakdowns

Use when: Content is hierarchical with clear parent-child relationships

Key features:

  • Radial tree structure
  • Multiple levels of nesting
  • Clean visual hierarchy

5. Sequence Diagram

Best for: Interactions between components, API calls, message flows

Use when: Content involves communication between actors/systems over time

Key features:

  • Timeline-based layout
  • Clear actor separation
  • Activation boxes for processes

6. State Diagram

Best for: System states, status transitions, lifecycle stages

Use when: Content describes states and transitions between them

Key features:

  • Clear state nodes
  • Labeled transitions
  • Start and end states

Critical Syntax Rules

Always follow these rules to prevent parsing errors:

Rule 1: Avoid List Syntax Conflicts

❌ WRONG: [1. Perception]       → Triggers "Unsupported markdown: list"
✅ RIGHT: [1.Perception]         → Remove space after period
✅ RIGHT: [① Perception]         → Use circled numbers (①②③④⑤⑥⑦⑧⑨⑩)
✅ RIGHT: [(1) Perception]       → Use parentheses
✅ RIGHT: [Step 1: Perception]   → Use "Step" prefix

Rule 2: Subgraph Naming

❌ WRONG: subgraph AI Agent Core  → Space in name without quotes
✅ RIGHT: subgraph agent["AI Agent Core"]  → Use ID with display name
✅ RIGHT: subgraph agent          → Use simple ID only

Rule 3: Node References

❌ WRONG: Title --> AI Agent Core  → Reference display name directly
✅ RIGHT: Title --> agent          → Reference subgraph ID

Rule 4: Special Characters in Node Text

✅ Use quotes for text with spaces: ["Text with spaces"]
✅ Escape or avoid: quotation marks → use 『』instead
✅ Escape or avoid: parentheses → use 「」instead
✅ Line breaks in circle nodes only: ((Text<br/>Break))

Rule 5: Arrow Types

  • --> solid arrow
  • -.-> dashed arrow (for supporting systems, optional paths)
  • ==> thick arrow (for emphasis)
  • ~~~ invisible link (for layout only)

For complete syntax reference and edge cases, see references/syntax-rules.md

Configuration Options

All diagrams accept these parameters:

Layout:

  • direction: "vertical" (TB), "horizontal" (LR), "right-to-left" (RL), "bottom-to-top" (BT)
  • aspect: "portrait" (default), "landscape" (wide), "square"

Detail Level:

  • simple: Core elements only, minimal labels
  • standard: Balanced detail with key descriptions (default)
  • detailed: Full annotations, explanations, and metadata
  • presentation: Optimized for slides (larger text, fewer details)

Style:

  • minimal: Monochrome, clean lines
  • professional: Semantic colors, clear hierarchy (default)
  • colorful: Vibrant colors, high contrast
  • academic: Formal styling for papers/documentation

Additional Options:

  • show_legend: true/false - Include color/symbol legend
  • numbered: true/false - Add sequence numbers to steps
  • title: string - Add diagram title

Example Usage Patterns

Pattern 1: Basic request

User: "Visualize the software development lifecycle"
Response: [Analyze → Choose graph TB → Generate with standard detail]

Pattern 2: With configuration

User: "Create a horizontal flowchart of our sales process with lots of detail"
Response: [Analyze → Choose graph LR → Generate with detailed level]

Pattern 3: Comparison

User: "Compare traditional AI vs AI agents"
Response: [Analyze → Choose comparison layout → Generate with contrasting styles]

Workflow

  1. Understand the content

    • Identify main concepts, entities, and relationships
    • Determine hierarchy or sequence
    • Note any comparisons or contrasts
  2. Select diagram type

    • Match content structure to diagram type
    • Consider user's presentation context
    • Default to process flow if ambiguous
  3. Choose configuration

    • Apply user-specified options
    • Use sensible defaults for unspecified options
    • Optimize for readability
  4. Generate Mermaid code

    • Follow all syntax rules strictly
    • Use semantic naming (descriptive IDs)
    • Apply consistent styling
    • Test for common errors:
      • No "number. space" patterns in node text
      • All subgraphs use ID["display name"] format
      • All node references use IDs not display names
  5. Output with context

    • Wrap in ```mermaid code fence
    • Add brief explanation of diagram structure
    • Mention rendering compatibility (Obsidian, GitHub, etc.)
    • Offer to adjust or create variations

Color Scheme Defaults

Standard professional palette:

  • Green (#d3f9d8/#2f9e44): Input, perception, start states
  • Red (#ffe3e3/#c92a2a): Planning, decision points
  • Purple (#e5dbff/#5f3dc4): Processing, reasoning
  • Orange (#ffe8cc/#d9480f): Actions, tool usage
  • Cyan (#c5f6fa/#0c8599): Output, execution, results
  • Yellow (#fff4e6/#e67700): Storage, memory, data
  • Pink (#f3d9fa/#862e9c): Learning, optimization
  • Blue (#e7f5ff/#1971c2): Metadata, definitions, titles
  • Gray (#f8f9fa/#868e96): Neutral elements, traditional systems

Common Patterns

Swimlane Pattern (Grouping)

mermaid
graph TB
    subgraph core["Core Process"]
        A --> B --> C
    end
    subgraph support["Supporting Systems"]
        D
        E
    end
    core -.-> support

Feedback Loop Pattern

mermaid
graph TB
    A[Start] --> B[Process]
    B --> C[End]
    C -.->|Feedback| A

Hub and Spoke Pattern

mermaid
graph TB
    Central[Hub]
    A[Spoke 1] --> Central
    B[Spoke 2] --> Central
    C[Spoke 3] --> Central

Quality Checklist

Before outputting, verify:

  • No "number. space" patterns in any node text
  • All subgraphs use proper ID syntax
  • All arrows use correct syntax (-->, -.->)
  • Colors applied consistently
  • Layout direction specified
  • Style declarations present
  • No ambiguous node references
  • Compatible with Obsidian/GitHub renderers
  • No Emoji in any node text - use text labels or color coding instead

References

For detailed syntax rules and troubleshooting, see:

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 Mermaid Visualizer AI skill do?

Transform text content into professional Mermaid diagrams for presentations and documentation. Use when users ask to visualize concepts, create flowcharts, or make diagrams from text. Supports process flows, system architectures, comparisons, mindmaps, and more with built-in syntax error prevention.

Why use Mermaid Visualizer on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/axtonliu/axton-obsidian-visual-skills/tree/main/mermaid-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 Mermaid 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 Mermaid Visualizer?

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

Is the Mermaid Visualizer AI skill free?

Yes. It is published on GitHub by axtonliu 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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