plantuml-ascii

github/awesome-copilot · updated Apr 17, 2026

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$npx skills add https://github.com/github/awesome-copilot --skill plantuml-ascii
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summary

Generate ASCII art diagrams from PlantUML text syntax for terminal and documentation use.

  • Supports six diagram types: sequence, class, activity, state, component, use case, and deployment diagrams
  • Two output formats: pure ASCII ( -txt ) and Unicode-enhanced ASCII ( -utxt ) with box-drawing characters for improved readability
  • Works with PlantUML installation or standalone JAR; outputs to .atxt or .utxt files ready for terminals, READMEs, and version control
  • Command-line options inc
skill.md

PlantUML ASCII Art Diagram Generator

Overview

Create text-based ASCII art diagrams using PlantUML. Perfect for documentation in terminal environments, README files, emails, or any scenario where graphical diagrams aren't suitable.

What is PlantUML ASCII Art?

PlantUML can generate diagrams as plain text (ASCII art) instead of images. This is useful for:

  • Terminal-based workflows
  • Git commits/PRs without image support
  • Documentation that needs to be version-controlled
  • Environments where graphical tools aren't available

Installation

# macOS
brew install plantuml

# Linux (varies by distro)
sudo apt-get install plantuml  # Ubuntu/Debian
sudo yum install plantuml      # RHEL/CentOS

# Or download JAR directly
wget https://github.com/plantuml/plantuml/releases/download/v1.2024.0/plantuml-1.2024.0.jar

Output Formats

Flag Format Description
-txt ASCII Pure ASCII characters
-utxt Unicode ASCII Enhanced with box-drawing characters

Basic Workflow

1. Create PlantUML Diagram File

@startuml
participant Bob
actor Alice

Bob -> Alice : hello
Alice -> Bob : Is it ok?
@enduml

2. Generate ASCII Art

# Standard ASCII output
plantuml -txt diagram.puml

# Unicode-enhanced output (better looking)
plantuml -utxt diagram.puml

# Using JAR directly
java -jar plantuml.jar -txt diagram.puml
java -jar plantuml.jar -utxt diagram.puml

3. View Output

Output is saved as diagram.atxt (ASCII) or diagram.utxt (Unicode).

Diagram Types Supported

Sequence Diagram

@startuml
actor User
participant "Web App" as App
database "Database" as DB

User -> App : Login Request
App -> DB : Validate Credentials
DB --> App : User Data
App --> User : Auth Token
@enduml

Class Diagram

@startuml
class User {
  +id: int
  +name: string
  +email: string
  +login(): bool
}

class Order {
  +id: int
  +total: float
  +items: List
  +calculateTotal(): float
}

User "1" -- "*" Order : places
@enduml

Activity Diagram

@startuml
start
:Initialize;
if (Is Valid?) then (yes)
  :Process Data;
  :Save Result;
else (no)
  :Log Error;
  stop
endif
:Complete;
stop
@enduml

State Diagram

@startuml
[*] --> Idle
Idle --> Processing : start
Processing --> Success : complete
Processing --> Error : fail
Success --> [*]
Error --> Idle : retry
@enduml

Component Diagram

@startuml
[Client] as client
[API Gateway] as gateway
[Service A] as svcA
[Service B] as svcB
[Database] as db

client --> gateway
gateway --> svcA
gateway --> svcB
svcA --> db
svcB --> db
@enduml

Use Case Diagram

@startuml
actor "User" as user
actor "Admin" as admin

rectangle "System" {
  user -- (Login)
  user -- (View Profile)
  user -- (Update Settings)
  admin -- (Manage Users)
  admin -- (Configure System)
}
@enduml

Deployment Diagram

@startuml
actor "User" as user
node "Load Balancer" as lb
node "Web Server 1" as ws1
node "Web Server 2" as ws2
database "Primary DB" as db1
database "Replica DB" as db2

user --> lb
lb --> ws1
lb --> ws2
ws1 --> db1
ws2 --> db1
db1 --> db2 : replicate
@enduml

Command-Line Options

# Specify output directory
plantuml -txt -o ./output diagram.puml

# Process all files in directory
plantuml -txt ./diagrams/

# Include dot files (hidden files)
plantuml -txt -includeDot diagrams/

# Verbose output
plantuml -txt -v diagram.puml

# Specify charset
plantuml -txt -charset UTF-8 diagram.puml

Ant Task Integration

<target name="generate-ascii">
  <plantuml dir="./src" format="txt" />
</target>

<target name="generate-unicode-ascii">
  <plantuml dir="./src" format="utxt" />
</target>

Tips for Better ASCII Diagrams

  1. Keep it simple: Complex diagrams don't render well in ASCII
  2. Short labels: Long text breaks ASCII alignment
  3. Use Unicode (-utxt): Better visual quality with box-drawing chars
  4. Test before sharing: Verify in terminal with fixed-width font
  5. Consider alternatives: For complex diagrams, use Mermaid.js or graphviz

Example Output Comparison

Standard ASCII (-txt):

     ,---.          ,---.
     |Bob|          |Alice|
     `---'          `---'
      |   hello      |
      |------------->|
      |              |
      |  Is it ok?   |
      |<-------------|
      |              |

Unicode ASCII (-utxt):

┌─────┐        ┌─────┐
│ Bob │        │Alice│
└─────┘        └─────┘
  │   hello      │
  │─────────────>│
  │              │
  │  Is it ok?   │
  │<─────────────│
  │              │

Quick Reference

# Create sequence diagram in ASCII
cat > seq.puml << 'EOF'
@startuml
Alice -> Bob: Request
Bob --> Alice: Response
@enduml
EOF

plantuml -txt seq.puml
cat seq.atxt

# Create with Unicode
plantuml -utxt seq.puml
cat seq.utxt

Troubleshooting

Problem: Garbled Unicode characters

  • Solution: Ensure terminal supports UTF-8 and has proper font

Problem: Diagram looks misaligned

  • Solution: Use fixed-width font (Courier, Monaco, Consolas)

Problem: Command not found

  • Solution: Install PlantUML or use Java JAR directly

Problem: Output file not created

  • Solution: Check file permissions, ensure PlantUML has write access
how to use plantuml-ascii

How to use plantuml-ascii on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add plantuml-ascii
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/github/awesome-copilot --skill plantuml-ascii

The skills CLI fetches plantuml-ascii from GitHub repository github/awesome-copilot and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/plantuml-ascii

Reload or restart Cursor to activate plantuml-ascii. Access the skill through slash commands (e.g., /plantuml-ascii) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.835 reviews
  • Dhruvi Jain· Dec 28, 2024

    Keeps context tight: plantuml-ascii is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Benjamin Anderson· Dec 24, 2024

    We added plantuml-ascii from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Daniel Verma· Dec 12, 2024

    Keeps context tight: plantuml-ascii is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Isabella Smith· Dec 4, 2024

    I recommend plantuml-ascii for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Oshnikdeep· Nov 19, 2024

    plantuml-ascii has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Amelia White· Nov 15, 2024

    plantuml-ascii reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Hassan Sanchez· Nov 3, 2024

    plantuml-ascii has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Advait Tandon· Oct 22, 2024

    Solid pick for teams standardizing on skills: plantuml-ascii is focused, and the summary matches what you get after install.

  • Ganesh Mohane· Oct 10, 2024

    Solid pick for teams standardizing on skills: plantuml-ascii is focused, and the summary matches what you get after install.

  • Amelia Srinivasan· Oct 6, 2024

    Registry listing for plantuml-ascii matched our evaluation — installs cleanly and behaves as described in the markdown.

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