code-to-diagram

name

code-to-diagram

description

Generate architecture diagrams, ER diagrams, sequence diagrams, flowcharts, and class diagrams from codebases using Mermaid.js. Use when users ask to visualize code structure, draw architecture diagrams, create ER diagrams from database models, generate sequence diagrams from API flows, or produce any diagram from source code. Triggers on: 'draw architecture', 'generate diagram', 'visualize code', 'ER diagram', 'sequence diagram', 'class diagram', 'flowchart from code', 'module dependency graph'.

Code to Diagram

Generate production-quality diagrams from source code via Mermaid.js, rendered to SVG/PNG with mmdc.

Environment

Executor required: This skill needs the diagram executor (Chromium + Node.js + mmdc pre-installed). If mmdc is not available, install first:

npm install -g @mermaid-js/mermaid-cli

Puppeteer config for headless environments — create at /tmp/puppeteer-config.json if missing:

{"args": ["--no-sandbox", "--disable-setuid-sandbox"]}

Workflow

1. Analyze — Read the codebase to understand structure (glob, grep, read)
2. Plan — Decide diagram type(s) based on user request and code patterns
3. Generate — Write .mmd file with Mermaid syntax
4. Render — Run mmdc to produce SVG and PNG
5. Verify — Read the output image and check correctness

Diagram Type Selection

User Intent	Diagram Type	Mermaid Keyword
System overview, module layout	Architecture	graph TD + subgraph
Database tables, ORM models	ER Diagram	erDiagram
API flow, request lifecycle	Sequence Diagram	sequenceDiagram
Inheritance, interfaces	Class Diagram	classDiagram
Business logic, conditionals	Flowchart	flowchart TD
Task states, lifecycle	State Diagram	stateDiagram-v2
Import/dependency tree	Dependency Graph	graph LR
Timeline, project phases	Gantt Chart	gantt

Analysis Strategy

Do NOT read every file. Use progressive analysis:

Step 1 — Directory scan: glob("**/*.py") or glob("**/*.ts") to understand module structure.

Step 2 — Entry points:

• Python: main.py, app.py, __init__.py, pyproject.toml
• Node.js: package.json, index.ts, app.ts
• Java: pom.xml, Application.java

Step 3 — Targeted reads by diagram type:

• ER → ORM models (models.py, schema.prisma, *.entity.ts)
• Architecture → Router registrations, dependency injection, config
• Sequence → Specific endpoint handler + service call chain
• Class → Class definitions via grep("class ")

Step 4 — GitHub repos:

git clone --depth 1 <url> /tmp/repo-name

Then apply the same progressive scan.

Rendering

# SVG (transparent background, good for docs)
mmdc -i diagram.mmd -o diagram.svg -b transparent -p /tmp/puppeteer-config.json

# PNG (white background, 2x scale for sharpness)
mmdc -i diagram.mmd -o diagram.png -b white -s 2 -p /tmp/puppeteer-config.json

Always generate both formats. Use -s 2 for PNG (sharp at any zoom level).

Mermaid Syntax Reference

For detailed patterns and examples per diagram type, see references/mermaid-patterns.md.

Key rules:

• Short IDs, descriptive labels: DB[("PostgreSQL 16")]
• Use subgraph for logical grouping in architecture diagrams
• Limit ER diagrams to ~10 entities — split by domain if larger
• participant aliases in sequence diagrams for short names
• Quote labels with special chars: A["Node (v1)"]
• Max ~20 nodes per diagram — split into multiple if larger

Output Conventions

• Write .mmd source + rendered files to workspace
• Descriptive names: architecture.mmd, er-diagram.png, api-sequence.svg
• Multiple diagrams → create diagrams/ folder with index

Quality Checklist

• All entities/modules from the code are represented
• Relationships and data flow directions are correct
• Labels readable, not truncated or overlapping
• No Mermaid syntax errors
• Output image visually verified