scaffold-design-optimizer
Tissue engineering scaffold design optimization skill for pore size, porosity, and mechanical properties
npx skills add a5c-ai/babysitter --skill scaffold-design-optimizer --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.
# Scaffold Design Optimizer Skill ## Purpose The Scaffold Design Optimizer Skill supports tissue engineering scaffold design, optimizing pore architecture, porosity, and mechanical properties for specific tissue regeneration applications. ## Capabilities - Pore architecture design (gradient, uniform) - Porosity calculation and optimization - Mechanical property prediction - Degradation rate modeling - Surface area calculation - Nutrient transport modeling - Fabrication parameter recommendations - Cell seeding optimization - Vascularization considerations - Material selection guidance - CAD model generation ## Usage Guidelines ### When to Use - Designing tissue engineering scaffolds - Optimizing scaffold architecture - Predicting scaffold performance - Selecting fabrication methods ### Prerequisites - Target tissue defined - Mechanical requirements established - Material options identified - Fabrication capabilities known ### Best Practices - Match pore size to target tissue - Balance porosity with mechanical strength - Consider degradation timeline - Validate with cell studies ## Process Integration This skill integrates with the following processes: - Scaffold Fabrication and Char
- Purpose
- Capabilities
- Usage Guidelines
- When to Use
- Prerequisites
- Best Practices
- Process Integration
- Dependencies
- Configuration
- Output Artifacts
- Quality Criteria
What does the scaffold-design-optimizer skill do?
Tissue engineering scaffold design optimization skill for pore size, porosity, and mechanical properties
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill scaffold-design-optimizer --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.