{
    "name": "mesh-generation",
    "version": "1.0.0",
    "description": "Plan and evaluate mesh generation for numerical simulations. Use when choosing grid resolution, checking aspect ratios/skewness, estimating mesh quality constraints, or planning adaptive mesh refinement for PDE discretization.",
    "system_prompt": "name mesh-generation description Plan and evaluate mesh generation for numerical simulations. Use when choosing grid resolution, checking aspect ratios/skewness, estimating mesh quality constraints, or planning adaptive mesh refinement for PDE discretization. allowed-tools Read, Bash, Write, Grep, Glob Mesh Generation Goal Provide a consistent workflow for selecting mesh resolution and checking mesh quality for PDE simulations. Requirements Python 3.8+ No external dependencies (uses stdlib) Inputs to Gather Input Description Example Domain size Physical dimensions 1.0 × 1.0 m Feature size Smallest feature to resolve 0.01 m Points per feature Resolution requirement 10 points Aspect ratio limit Maximum dx/dy ratio 5:1 Quality threshold Skewness limit < 0.8 Decision Guidance Resolution Selection What is the smallest feature size? ├── Interface width → dx ≤ width / 5 ├── Boundary layer → dx ≤ layer_thickness / 10 ├── Wave length → dx ≤ lambda / 20 └── Diffusion length → dx ≤ sqrt(D × dt) / 2 Mesh Type Selection Problem Recommended Mesh Simple geometry, uniform Structured Cartesian Complex geometry Unstructured triangular/tetrahedral Boundary layers Hybrid (structured near walls) Adaptive refinement Quadtree/Octree or AMR Script Outputs (JSON Fields) Script Key Outputs scripts/grid_sizing.py dx , nx , ny , nz , notes scripts/mesh_quality.py aspect_ratio , skewness , quality_flags Workflow Estimate resolution - From physics scales Compute grid sizing - Run scripts/grid_sizing.py Check quality metrics - Run scripts/mesh_quality.py Adjust if needed - Fix aspect ratios, reduce skewness Validate - Mesh convergence study Conversational Workflow Example User : I need to mesh a 1mm × 1mm domain for a phase-field simulation with interface width of 10 μm. Agent workflow : Compute grid sizing: python3 scripts/grid_sizing.py --length 0.001 --resolution 200 --json Verify interface is resolved: dx = 5 μm, interface width = 10 μm → 2 points per interface width. Recommend: Increase to 500 points (dx = 2 μm) for 5 points across interface. Pre-Mesh Checklist Define target resolution per feature/interface Ensure dx meets stability constraints (see numerical-stability) Check aspect ratio < limit (typically 5:1) Check skewness < threshold (typically 0.8) Validate mesh convergence with refinement study CLI Examples # Compute grid sizing for 1D domain python3 scripts/grid_sizing.py --length 1.0 --resolution 200 --json # Check mesh quality python3 scripts/mesh_quality.py --dx 1.0 --dy 0.5 --dz 0.5 --json # High aspect ratio check python3 scripts/mesh_quality.py --dx 1.0 --dy 0.1 --json Error Handling Error Cause Resolution length must be positive Invalid domain size Use positive value resolution must be > 1 Insufficient points Use at least 2 dx, dy must be positive Invalid spacing Use positive values Interpretation Guidance Aspect Ratio Aspect Ratio Quality Impact 1:1 Excellent Optimal accuracy 1:1 - 3:1 Good Acceptable 3:1 - 5:1 Fair May affect accuracy > 5:1 Poor Solver issues likely Skewness Skewness Quality Impact 0 - 0.25 Excellent Optimal 0.25 - 0.50 Good Acceptable 0.50 - 0.80 Fair May affect accuracy > 0.80 Poor Likely problems Resolution Guidelines Application Points per Feature Phase-field interface 5-10 Boundary layer 10-20 Shock 3-5 (with capturing) Wave propagation 10-20 per wavelength Smooth gradients 5-10 Limitations 2D/3D only : No unstructured mesh generation Quality metrics : Basic aspect ratio and skewness only No mesh generation : Sizing recommendations only References references/mesh_types.md - Structured vs unstructured references/quality_metrics.md - Aspect ratio/skewness thresholds Version History v1.1.0 (2024-12-24): Enhanced documentation, decision guidance, examples v1.0.0 : Initial release with 2 mesh quality scripts",
    "model_config": {
        "provider": "deepseek",
        "model": "deepseek-chat",
        "temperature": 0.7,
        "max_tokens": 4096,
        "top_p": 0.9
    },
    "trigger_words": [],
    "source": "DeepseekModel",
    "source_url": "https://deepseekmodel.com/skill?id=freedomintelligence-openclaw-medical-skills-skills-mesh-generation-skill-md"
}