Drawio Diagram Forge
by aktsmm
Generate draw.io editable diagrams (.drawio, .drawio.svg) from text, images, or Excel. Orchestrates 3-agent workflow (Analysis → Manifest → SVG generation) with quality gates. Use when creating architecture diagrams, flowcharts, sequence diagrams, or converting existing images to editable format. Supports Azure/AWS cloud icons.
Skill Details
Repository Files
6 files in this skill directory
name: drawio-diagram-forge description: Generate draw.io editable diagrams (.drawio, .drawio.svg) from text, images, or Excel. Orchestrates 3-agent workflow (Analysis → Manifest → SVG generation) with quality gates. Use when creating architecture diagrams, flowcharts, sequence diagrams, or converting existing images to editable format. Supports Azure/AWS cloud icons. license: CC BY-NC-SA 4.0 metadata: author: yamapan (https://github.com/aktsmm)
Draw.io Diagram Forge
Generate draw.io editable diagrams using AI-powered workflow.
When to Use
- Creating architecture diagrams (Azure, AWS)
- Converting flowcharts from text descriptions
- Transforming images/screenshots into editable format
- Generating swimlane, sequence diagrams
Prerequisites
| Tool | Required |
|---|---|
| VS Code | Yes |
| Draw.io Integration | Yes |
| GitHub Copilot | Yes |
Quick Start
Create a login flow diagram
Generate an Azure Hub-Spoke architecture diagram
From inputs/requirements.md, create a system diagram
Output Formats
| Extension | Description | When to Use |
|---|---|---|
*.drawio |
Native format | Recommended |
*.drawio.svg |
SVG + metadata | Markdown/Web |
*.drawio.png |
PNG + metadata | Image with edit |
Output: outputs/
Workflow
USER INPUT → ORCHESTRATOR → MANIFEST GATEWAY → SVG FORGE → COMPLETED
Quality Gates
| Score | Action |
|---|---|
| 90-100 | Proceed |
| 70-84 | Fix and retry |
| 50-69 | Simplify |
| 0-29 | Ask user |
Limits
| Limit | Value |
|---|---|
| Manifest revision | 2 |
| SVG revision | 2 |
| Total timeout | 45min |
Cloud Icons
Enable in VS Code
- Open
.drawiofile - Click "+ More Shapes" (bottom-left)
- Enable: Azure, AWS
- Apply
Azure Format (Critical)
<!-- WRONG -->
<mxCell style="shape=mxgraph.azure.front_door;..." />
<!-- CORRECT -->
<mxCell style="aspect=fixed;image=img/lib/azure2/networking/Front_Doors.svg;..." />
References
| File | Description |
|---|---|
| mxcell-structure.md | mxCell XML structure |
| cloud-icons.md | Azure/AWS icon guide |
| style-guide.md | Node colors, edge styles |
Scripts
| Script | Description |
|---|---|
scripts/validate_drawio.py |
Validate mxCell structure |
Troubleshooting
| Issue | Solution |
|---|---|
| Blank in draw.io | Check content attribute |
| Edges not visible | Verify node IDs |
| Icons missing | Enable Azure/AWS shapes |
Done Criteria
-
.drawioor.drawio.svgfile generated - Diagram opens correctly in VS Code Draw.io extension
- All nodes and edges visible
- Quality gate score ≥ 85
Related Skills
Team Composition Analysis
This skill should be used when the user asks to "plan team structure", "determine hiring needs", "design org chart", "calculate compensation", "plan equity allocation", or requests organizational design and headcount planning for a startup.
Startup Financial Modeling
This skill should be used when the user asks to "create financial projections", "build a financial model", "forecast revenue", "calculate burn rate", "estimate runway", "model cash flow", or requests 3-5 year financial planning for a startup.
Startup Metrics Framework
This skill should be used when the user asks about "key startup metrics", "SaaS metrics", "CAC and LTV", "unit economics", "burn multiple", "rule of 40", "marketplace metrics", or requests guidance on tracking and optimizing business performance metrics.
Market Sizing Analysis
This skill should be used when the user asks to "calculate TAM", "determine SAM", "estimate SOM", "size the market", "calculate market opportunity", "what's the total addressable market", or requests market sizing analysis for a startup or business opportunity.
Anndata
This skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata, or handling large-scale biological datasets. Use when tasks involve AnnData objects, h5ad files, single-cell RNA-seq data, or integration with scanpy/scverse tools.
Geopandas
Python library for working with geospatial vector data including shapefiles, GeoJSON, and GeoPackage files. Use when working with geographic data for spatial analysis, geometric operations, coordinate transformations, spatial joins, overlay operations, choropleth mapping, or any task involving reading/writing/analyzing vector geographic data. Supports PostGIS databases, interactive maps, and integration with matplotlib/folium/cartopy. Use for tasks like buffer analysis, spatial joins between dat
Market Research Reports
Generate comprehensive market research reports (50+ pages) in the style of top consulting firms (McKinsey, BCG, Gartner). Features professional LaTeX formatting, extensive visual generation with scientific-schematics and generate-image, deep integration with research-lookup for data gathering, and multi-framework strategic analysis including Porter's Five Forces, PESTLE, SWOT, TAM/SAM/SOM, and BCG Matrix.
Plotly
Interactive scientific and statistical data visualization library for Python. Use when creating charts, plots, or visualizations including scatter plots, line charts, bar charts, heatmaps, 3D plots, geographic maps, statistical distributions, financial charts, and dashboards. Supports both quick visualizations (Plotly Express) and fine-grained customization (graph objects). Outputs interactive HTML or static images (PNG, PDF, SVG).
Dask
Parallel/distributed computing. Scale pandas/NumPy beyond memory, parallel DataFrames/Arrays, multi-file processing, task graphs, for larger-than-RAM datasets and parallel workflows.
Scikit Survival
Comprehensive toolkit for survival analysis and time-to-event modeling in Python using scikit-survival. Use this skill when working with censored survival data, performing time-to-event analysis, fitting Cox models, Random Survival Forests, Gradient Boosting models, or Survival SVMs, evaluating survival predictions with concordance index or Brier score, handling competing risks, or implementing any survival analysis workflow with the scikit-survival library.
