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Cómo pedir trabajo con esta skill instalada
Instalar la skill da un método a tu IA. Tu petición todavía debe aportar los hechos del caso, las restricciones y el entregable esperado.
Describe la decisión o el entregable, no solo el tema.
Añade materiales, público, límites y hechos conocidos.
Fija formato, criterios de calidad y comprobaciones.
Cuándo usarla
This skill should be used when:
- Creating neural network architecture diagrams (Transformers, CNNs, RNNs, etc.)
- Illustrating system architectures and data flow diagrams
- Drawing methodology flowcharts for study design (CONSORT, PRISMA)
- Visualizing algorithm workflows and processing pipelines
- Creating circuit diagrams and electrical schematics
- Depicting biological pathways and molecular interactions
- Generating network topologies and hierarchical structures
- Illustrating conceptual frameworks and theoretical models
- Designing block diagrams for technical papers
Errores que conviene evitar
AI Generation Issues
Problem: Overlapping text or elements
- Solution: AI generation automatically handles spacing
- Solution: Increase iterations:
--iterations 2for better refinement
Problem: Elements not connecting properly
- Solution: Make your prompt more specific about connections and layout
- Solution: Increase iterations for better refinement
Image Quality Issues
Problem: Export quality poor
- Solution: AI generation produces high-quality images automatically
- Solution: Increase iterations for better results:
--iterations 2
Problem: Elements overlap after generation
- Solution: AI generation automatically handles spacing
- Solution: Increase iterations:
--iterations 2for better refinement - Solution: Make your prompt more specific about layout and spacing requirements
Quality Check Issues
Problem: False positive overlap detection
- Solution: Adjust threshold:
detect_overlaps(image_path, threshold=0.98) - Solution: Manually review flagged regions in visual report
Problem: Generated image quality is low
- Solution: AI generation produces high-quality images by default
- Solution: Increase iterations for better results:
--iterations 2
Problem: Colorblind simulation shows poor contrast
- Solution: Switch to Okabe-Ito palette explicitly in code
- Solution: Add redundant encoding (shapes, patterns, line styles)
- Solution: Increase color saturation and lightness differences
Problem: High-severity overlaps detected
- Solution: Review overlap_report.json for exact positions
- Solution: Increase spacing in those specific regions
- Solution: Re-run with adjusted parameters and verify again
Problem: Visual report generation fails
- Solution: Check Pillow and matplotlib installations
- Solution: Ensure image file is readable:
Image.open(path).verify() - Solution: Check sufficient disk space for report generation
Accessibility Problems
Problem: Colors indistinguishable in grayscale
- Solution: Run accessibility checker:
verify_accessibility(image_path) - Solution: Add patterns, shapes, or line styles for redundancy
- Solution: Increase contrast between adjacent elements
Problem: Text too small when printed
- Solution: Run resolution validator:
validate_resolution(image_path) - Solution: Design at final size, use minimum 7-8 pt fonts
- Solution: Check physical dimensions in resolution report
Problem: Accessibility checks consistently fail
- Solution: Review accessibility_report.json for specific failures
- Solution: Increase color contrast by at least 20%
- Solution: Test with actual grayscale conversion before finalizing