skills/tools/diagram/kroki-diagram-api/SKILL.md
Generate diagrams from text via Kroki's multi-format rendering API
npx skillsauth add wentorai/research-plugins kroki-diagram-apiInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Kroki provides a unified HTTP API to render 20+ text-based diagram formats into images (SVG, PNG, PDF). It supports Mermaid, PlantUML, Graphviz, D2, BPMN, and more — all through a single endpoint. Self-hostable or use the free public instance. No authentication required. Ideal for generating research figures, architecture diagrams, and flowcharts programmatically.
# Graphviz DOT diagram
curl "https://kroki.io/graphviz/svg/digraph{A->B->C}" -o diagram.svg
# Mermaid diagram (base64-encoded)
echo "graph TD; A-->B; B-->C;" | base64 | \
curl "https://kroki.io/mermaid/svg/$(cat -)" -o diagram.svg
# PlantUML sequence diagram
curl -X POST "https://kroki.io/plantuml/svg" \
-H "Content-Type: text/plain" \
-d '@startuml
Alice -> Bob: Hello
Bob --> Alice: Hi!
@enduml' -o sequence.svg
# Mermaid flowchart
curl -X POST "https://kroki.io/mermaid/svg" \
-H "Content-Type: text/plain" \
-d 'graph TD
A[Data Collection] --> B[Preprocessing]
B --> C[Model Training]
C --> D[Evaluation]
D -->|Good| E[Deploy]
D -->|Bad| B' -o flowchart.svg
# Graphviz
curl -X POST "https://kroki.io/graphviz/svg" \
-H "Content-Type: text/plain" \
-d 'digraph {
rankdir=LR
"Raw Data" -> "Feature Extraction" -> "Model" -> "Prediction"
}' -o pipeline.svg
# D2 diagram
curl -X POST "https://kroki.io/d2/svg" \
-H "Content-Type: text/plain" \
-d 'Client -> API: Request
API -> Database: Query
Database -> API: Results
API -> Client: Response' -o d2.svg
https://kroki.io/{diagram_type}/{output_format}/{encoded_source}
# Or POST to:
https://kroki.io/{diagram_type}/{output_format}
| Type | Keyword | Best for |
|------|---------|----------|
| Mermaid | mermaid | Flowcharts, sequences, Gantt |
| PlantUML | plantuml | UML, sequences, class diagrams |
| Graphviz | graphviz | Network graphs, DAGs |
| D2 | d2 | Modern text-to-diagram |
| Ditaa | ditaa | ASCII art diagrams |
| BlockDiag | blockdiag | Block diagrams |
| Nomnoml | nomnoml | UML-like diagrams |
| WaveDrom | wavedrom | Digital timing diagrams |
| Vega | vega | Data visualizations |
| Vega-Lite | vegalite | Simplified data viz |
| C4 PlantUML | c4plantuml | C4 architecture |
| BPMN | bpmn | Business processes |
| Bytefield | bytefield | Protocol/byte diagrams |
| Excalidraw | excalidraw | Hand-drawn style |
| Format | Extension | Use case |
|--------|-----------|----------|
| SVG | /svg | Web, scalable |
| PNG | /png | Documents, slides |
| PDF | /pdf | Papers, print |
| JPEG | /jpeg | Compatibility |
import requests
import base64
import zlib
KROKI_URL = "https://kroki.io"
def render_diagram(source: str, diagram_type: str = "mermaid",
output_format: str = "svg") -> bytes:
"""Render a text diagram to image via Kroki."""
resp = requests.post(
f"{KROKI_URL}/{diagram_type}/{output_format}",
headers={"Content-Type": "text/plain"},
data=source,
)
resp.raise_for_status()
return resp.content
def save_diagram(source: str, output_path: str,
diagram_type: str = "mermaid",
output_format: str = "svg"):
"""Render and save a diagram to file."""
content = render_diagram(source, diagram_type, output_format)
with open(output_path, "wb") as f:
f.write(content)
def render_research_pipeline(steps: list) -> bytes:
"""Create a research pipeline flowchart."""
nodes = []
for i, step in enumerate(steps):
node_id = chr(65 + i)
nodes.append(f" {node_id}[{step}]")
if i > 0:
prev_id = chr(65 + i - 1)
nodes.append(f" {prev_id} --> {node_id}")
mermaid = "graph TD\n" + "\n".join(nodes)
return render_diagram(mermaid, "mermaid", "svg")
# Example: create a research workflow diagram
workflow = """graph TD
A[Literature Review] --> B[Hypothesis]
B --> C[Data Collection]
C --> D[Statistical Analysis]
D --> E{Significant?}
E -->|Yes| F[Write Paper]
E -->|No| G[Revise Hypothesis]
G --> B
F --> H[Peer Review]"""
save_diagram(workflow, "research_workflow.svg", "mermaid")
# Example: Graphviz citation network
citation_graph = """digraph {
rankdir=BT
node [shape=box, style=rounded]
"Vaswani 2017" -> "BERT 2018"
"Vaswani 2017" -> "GPT 2018"
"BERT 2018" -> "RoBERTa 2019"
"GPT 2018" -> "GPT-2 2019"
"GPT-2 2019" -> "GPT-3 2020"
}"""
save_diagram(citation_graph, "citations.svg", "graphviz")
# Example: research pipeline helper
pipeline_svg = render_research_pipeline([
"Raw Data", "Cleaning", "Feature Engineering",
"Model Training", "Evaluation", "Deployment"
])
# Run Kroki locally via Docker
docker run -d -p 8000:8000 yuzutech/kroki
# Then use http://localhost:8000 instead of https://kroki.io
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