fea-mesh-generator
Finite element mesh generation skill optimized for biomedical geometries including implants, anatomical structures, and tissue models
npx skills add a5c-ai/babysitter --skill fea-mesh-generator --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# FEA Mesh Generator Skill ## Purpose The FEA Mesh Generator Skill creates optimized finite element meshes for biomedical applications, supporting analysis of implants, anatomical structures, and tissue models with appropriate element types and mesh quality. ## Capabilities - Automatic mesh generation from CAD/STL - Mesh quality assessment and repair - Boundary layer meshing for fluid-structure - Mesh convergence study automation - Anatomical landmark identification - Patient-specific mesh generation from imaging - Adaptive mesh refinement - Multi-material mesh handling - Contact surface mesh preparation - Hexahedral and tetrahedral meshing - Mesh smoothing and optimization ## Usage Guidelines ### When to Use - Preparing FEA models for biomedical analysis - Creating patient-specific anatomical models - Conducting mesh sensitivity studies - Optimizing computational efficiency ### Prerequisites - CAD geometry or imaging data available - Material regions identified - Analysis requirements defined - Contact interfaces specified ### Best Practices - Verify mesh quality metrics before analysis - Conduct mesh convergence studies - Use appropriate element types for physics - Document mesh
- Purpose
- Capabilities
- Usage Guidelines
- When to Use
- Prerequisites
- Best Practices
- Process Integration
- Dependencies
- Configuration
- Output Artifacts
- Quality Criteria
What does the fea-mesh-generator skill do?
Finite element mesh generation skill optimized for biomedical geometries including implants, anatomical structures, and tissue models
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill fea-mesh-generator --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.