skills/tools/diagram/plantuml-guide/SKILL.md
Create UML diagrams and architecture visualizations with PlantUML
npx skillsauth add wentorai/research-plugins plantuml-guideInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Create UML diagrams, architecture visualizations, flowcharts, and other technical diagrams using PlantUML's text-based notation for reproducible, version-controllable diagrams.
PlantUML generates diagrams from plain text descriptions. Diagrams are defined in .puml files and rendered to PNG, SVG, or PDF.
| Method | Command / URL | Best For |
|--------|--------------|----------|
| VS Code extension | Install "PlantUML" by jebbs | IDE integration |
| CLI (Java JAR) | java -jar plantuml.jar diagram.puml | Batch processing |
| Online server | plantuml.com/plantuml | Quick prototyping |
| Docker | docker run plantuml/plantuml-server | Self-hosted server |
| Python | pip install plantuml | Python integration |
| Jupyter | pip install iplantuml | Notebook integration |
@startuml
title My First Diagram
Alice -> Bob: Hello
Bob --> Alice: Hi there!
@enduml
Model interactions between components over time:
@startuml
title Research Paper Submission Workflow
actor Author
participant "Submission\nSystem" as SS
participant "Editor" as Ed
participant "Reviewer 1" as R1
participant "Reviewer 2" as R2
Author -> SS: Submit manuscript
activate SS
SS -> Ed: Notify new submission
activate Ed
Ed -> SS: Assign reviewers
SS -> R1: Review request
SS -> R2: Review request
activate R1
activate R2
R1 -> SS: Submit review (Accept)
deactivate R1
R2 -> SS: Submit review (Minor revision)
deactivate R2
Ed -> SS: Decision: Minor revision
SS -> Author: Revision request
deactivate Ed
deactivate SS
Author -> SS: Submit revised manuscript
activate SS
SS -> Ed: Notify revision
Ed -> SS: Accept
SS -> Author: Acceptance notification
deactivate SS
@enduml
Model system structure and relationships:
@startuml
title Research Data Model
class Paper {
+id: UUID
+title: String
+abstract: String
+doi: String
+year: Integer
+venue: String
--
+getCitations(): List<Paper>
+getAuthors(): List<Author>
+getBibTeX(): String
}
class Author {
+id: UUID
+name: String
+orcid: String
+affiliation: String
+h_index: Integer
--
+getPapers(): List<Paper>
+getCoauthors(): List<Author>
}
class Dataset {
+id: UUID
+name: String
+doi: String
+license: String
+size_bytes: Long
--
+download(): File
+getCitation(): String
}
class Experiment {
+id: UUID
+description: String
+date: Date
+config: JSON
--
+run(): Results
+getMetrics(): Map
}
Paper "1" -- "*" Author : authored by >
Paper "1" -- "*" Dataset : uses >
Paper "1" -- "*" Experiment : contains >
Dataset "1" -- "*" Experiment : used in >
Paper "1" -- "*" Paper : cites >
@enduml
Model workflows and decision processes:
@startuml
title Systematic Review Screening Process
start
:Import records from databases;
:Remove duplicates;
:Screen title and abstract;
if (Meets inclusion criteria?) then (yes)
:Retrieve full text;
if (Full text available?) then (yes)
:Screen full text;
if (Meets all criteria?) then (yes)
:Include in review;
:Extract data;
if (Suitable for meta-analysis?) then (yes)
:Include in meta-analysis;
else (no)
:Include in narrative synthesis;
endif
else (no)
:Exclude with reason;
endif
else (no)
:Mark as unavailable;
endif
else (no)
:Exclude;
endif
:Compile PRISMA flow diagram;
stop
@enduml
Model system architecture:
@startuml
title Research Platform Architecture
package "Web Frontend" {
[React SPA] as SPA
[Dashboard] as Dash
[Skills Browser] as Skills
}
package "API Gateway" {
[FastAPI Server] as API
[Auth Service] as Auth
[Rate Limiter] as RL
}
package "Backend Services" {
[Paper Search] as PS
[Citation Graph] as CG
[Skill Registry] as SR
}
package "Data Layer" {
database "PostgreSQL" as PG
database "Redis Cache" as Redis
database "Elasticsearch" as ES
}
package "External APIs" {
[Unpaywall] as UP
[CrossRef] as CR
[OpenAlex] as OA
}
SPA --> API : HTTPS
Dash --> API : HTTPS
Skills --> API : HTTPS
API --> Auth : validate token
API --> RL : check rate limit
API --> PS : search request
API --> CG : graph query
API --> SR : skill lookup
PS --> ES : full-text search
PS --> S2 : paper metadata
PS --> CR : DOI resolution
CG --> PG : citation data
CG --> OA : citation graph
SR --> PG : skill metadata
SR --> Redis : cache
@enduml
Model system states and transitions:
@startuml
title Paper Lifecycle States
[*] --> Draft
Draft --> Submitted : Author submits
Submitted --> UnderReview : Editor assigns reviewers
Submitted --> DeskRejected : Editor rejects
UnderReview --> RevisionRequired : Minor/Major revision
UnderReview --> Accepted : Accept as is
UnderReview --> Rejected : Reject
RevisionRequired --> UnderReview : Author resubmits
RevisionRequired --> Withdrawn : Author withdraws
Accepted --> InProduction : Copy editing
InProduction --> Published : Online first
Published --> [*]
DeskRejected --> [*]
Rejected --> [*]
Withdrawn --> [*]
@enduml
Plan research timelines:
@startuml
title Research Project Timeline
Project starts 2025-01-01
[Literature Review] starts 2025-01-01 and lasts 8 weeks
[Research Design] starts at [Literature Review]'s end and lasts 4 weeks
[IRB Approval] starts at [Research Design]'s end and lasts 6 weeks
[Data Collection] starts at [IRB Approval]'s end and lasts 12 weeks
[Data Analysis] starts at [Data Collection]'s end and lasts 8 weeks
[Paper Writing] starts at [Data Analysis]'s end and lasts 10 weeks
[Peer Review] starts at [Paper Writing]'s end and lasts 12 weeks
[Revision] starts at [Peer Review]'s end and lasts 6 weeks
-- Milestones --
[Proposal Defense] happens at [Research Design]'s end
[Conference Presentation] happens at [Data Analysis]'s end
[Submission] happens at [Paper Writing]'s end
@enduml
Organize research topics:
@startmindmap
title Machine Learning Research Landscape
* Machine Learning
** Supervised Learning
*** Classification
**** SVM
**** Decision Trees
**** Neural Networks
*** Regression
**** Linear Regression
**** Gradient Boosting
** Unsupervised Learning
*** Clustering
**** K-Means
**** DBSCAN
*** Dimensionality Reduction
**** PCA
**** t-SNE
**** UMAP
** Reinforcement Learning
*** Model-Free
**** DQN
**** PPO
*** Model-Based
**** Dreamer
**** MuZero
** Deep Learning
*** CNNs
*** Transformers
*** GANs
*** Diffusion Models
@endmindmap
\usepackage{plantuml}
\begin{plantuml}
@startuml
Alice -> Bob: Hello
Bob --> Alice: Hi
@enduml
\end{plantuml}
% Compile with: pdflatex -shell-escape paper.tex
Many Markdown renderers (GitHub, GitLab, Notion) support Mermaid natively. PlantUML can be used via plugins or pre-rendering:
# Pre-render PlantUML to SVG for Markdown embedding
import plantuml
server = plantuml.PlantUML(url="http://www.plantuml.com/plantuml/svg/")
svg_content = server.processes("""
@startuml
Alice -> Bob: Hello
@enduml
""")
with open("diagram.svg", "wb") as f:
f.write(svg_content)
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