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.

3,891 stars

Best use case

mermaid-visualizer is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

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.

Teams using mermaid-visualizer should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/mermaid-visualizer/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/axtonliu/mermaid-visualizer/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/mermaid-visualizer/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How mermaid-visualizer Compares

Feature / Agentmermaid-visualizerStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this 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.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# 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](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:
- [references/syntax-rules.md](references/syntax-rules.md) - Complete syntax reference and error prevention

Related Skills

mermaid-architect

3891
from openclaw/skills

Generate beautiful, hand-drawn Mermaid diagrams with robust syntax (quoted labels, ELK layout). Use this skill when the user asks for "diagram", "flowchart", "sequence diagram", or "visualize this process".

General Utilities

3d-wordcloud-visualizer

3891
from openclaw/skills

3D 词云可视化工具 - 将对话历史或其他文本数据自动转换为炫酷的 3D 地球词云,支持多格式文件导入(JSON/MD/TXT),自动中文分词和词频统计,生成 TOP30 高频词的 3D 可视化效果

Data Visualization

karpathy-jobs-bls-visualizer

3819
from openclaw/skills

Research tool for visually exploring BLS Occupational Outlook Handbook data with an interactive treemap, LLM-powered scoring pipeline, and data scraping/parsing utilities.

---

3891
from openclaw/skills

name: article-factory-wechat

Content & Documentation

humanizer

3891
from openclaw/skills

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

Content & Documentation

find-skills

3891
from openclaw/skills

Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.

General Utilities

tavily-search

3891
from openclaw/skills

Use Tavily API for real-time web search and content extraction. Use when: user needs real-time web search results, research, or current information from the web. Requires Tavily API key.

Data & Research

baidu-search

3891
from openclaw/skills

Search the web using Baidu AI Search Engine (BDSE). Use for live information, documentation, or research topics.

Data & Research

agent-autonomy-kit

3891
from openclaw/skills

Stop waiting for prompts. Keep working.

Workflow & Productivity

Meeting Prep

3891
from openclaw/skills

Never walk into a meeting unprepared again. Your agent researches all attendees before calendar events—pulling LinkedIn profiles, recent company news, mutual connections, and conversation starters. Generates a briefing doc with talking points, icebreakers, and context so you show up informed and confident. Triggered automatically before meetings or on-demand. Configure research depth, advance timing, and output format. Walking into meetings blind is amateur hour—missed connections, generic small talk, zero leverage. Use when setting up meeting intelligence, researching specific attendees, generating pre-meeting briefs, or automating your prep workflow.

Workflow & Productivity

self-improvement

3891
from openclaw/skills

Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Claude ('No, that's wrong...', 'Actually...'), (3) User requests a capability that doesn't exist, (4) An external API or tool fails, (5) Claude realizes its knowledge is outdated or incorrect, (6) A better approach is discovered for a recurring task. Also review learnings before major tasks.

Agent Intelligence & Learning

botlearn-healthcheck

3891
from openclaw/skills

botlearn-healthcheck — BotLearn autonomous health inspector for OpenClaw instances across 5 domains (hardware, config, security, skills, autonomy); triggers on system check, health report, diagnostics, or scheduled heartbeat inspection.

DevOps & Infrastructure