additive-manufacturing
Skill for additive manufacturing process selection, design optimization, and build preparation
Best use case
additive-manufacturing is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Skill for additive manufacturing process selection, design optimization, and build preparation
Teams using additive-manufacturing should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/additive-manufacturing/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How additive-manufacturing Compares
| Feature / Agent | additive-manufacturing | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Skill for additive manufacturing process selection, design optimization, and build preparation
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Additive Manufacturing Skill
## Purpose
The Additive Manufacturing skill provides capabilities for AM process selection, design optimization, and build preparation, enabling effective use of additive technologies for prototyping and production applications.
## Capabilities
- AM technology selection (SLS, DMLS, FDM, SLA)
- Design for additive manufacturing (DfAM)
- Build orientation optimization
- Support structure design and minimization
- Part nesting and build volume optimization
- Post-processing procedure specification
- Surface finish and tolerance expectations
- AM-specific material properties and considerations
## Usage Guidelines
### Technology Selection
#### Metal AM Processes
| Process | Materials | Resolution | Applications |
|---------|-----------|------------|--------------|
| DMLS/SLM | Ti, Al, Steel, Inconel | 30-50 um layer | Aerospace, medical |
| EBM | Ti, CoCr | 50-100 um layer | Orthopedic implants |
| DED | Most metals | 250+ um | Large parts, repair |
| Binder Jet | Steel, bronze | 80-100 um | Tooling, high volume |
#### Polymer AM Processes
| Process | Materials | Resolution | Applications |
|---------|-----------|------------|--------------|
| SLS | Nylon, TPU | 100-150 um | Functional prototypes |
| SLA/DLP | Photopolymers | 25-100 um | High detail, patterns |
| FDM | ABS, PLA, PC, PEEK | 100-300 um | Prototypes, tooling |
| MJF | Nylon | 80 um | Production parts |
### Design for Additive Manufacturing
#### Self-Supporting Angles
```
Minimum self-supporting angle:
- Metal (DMLS): 45 degrees from horizontal
- Polymer (SLS): 0 degrees (self-supporting)
- FDM: 45 degrees (with support)
- SLA: 30-45 degrees
Overhang rule:
- Unsupported distance < 2 mm (metal)
- Unsupported distance < 5 mm (polymer)
```
#### Minimum Feature Sizes
| Process | Min Wall | Min Hole | Min Detail |
|---------|----------|----------|------------|
| DMLS | 0.4 mm | 0.5 mm | 0.2 mm |
| SLS | 0.7 mm | 1.0 mm | 0.3 mm |
| SLA | 0.5 mm | 0.5 mm | 0.1 mm |
| FDM | 0.8 mm | 2.0 mm | 0.5 mm |
#### Design Optimization
1. **Topology Optimization**
- Define design space
- Apply loads and constraints
- Set mass reduction target
- Interpret and refine results
2. **Lattice Structures**
| Type | Relative Density | Application |
|------|-----------------|-------------|
| Octet truss | 10-40% | High stiffness |
| Diamond | 15-35% | Isotropic |
| Gyroid | 10-50% | Bone ingrowth |
| Honeycomb | 20-50% | Directional load |
3. **Part Consolidation**
- Identify assembly candidates
- Evaluate function integration
- Consider serviceability
- Calculate cost/benefit
### Build Preparation
#### Orientation Selection
```
Optimization criteria:
1. Minimize support volume
2. Optimize surface finish on critical surfaces
3. Reduce build height (time)
4. Ensure feature accuracy
Trade-off example:
- Flat orientation: Less support, rougher top surface
- Angled orientation: More support, better detail
```
#### Support Design
1. **Support Types**
| Type | Application | Removal |
|------|-------------|---------|
| Block | Large overhangs | Manual/machining |
| Tree | Complex geometry | Manual |
| Lattice | Heat dissipation | Manual |
| Cone | Point supports | Manual |
2. **Support Minimization**
- Reorient part
- Add self-supporting chamfers
- Split and assemble
- Modify geometry if allowed
#### Nesting and Packing
```
Minimum spacing:
- DMLS: 2-5 mm between parts
- SLS: 2-3 mm (powder acts as support)
- FDM: N/A (single part builds)
- SLA: 2-3 mm
Packing efficiency target: 5-15% of build volume
```
### Post-Processing
#### Metal AM
1. **Required**
- Stress relief (before removal)
- Support removal
- Heat treatment (as specified)
2. **Optional**
- Machining critical surfaces
- Shot peening
- Polishing/finishing
- HIP (for porosity closure)
#### Polymer AM
1. **SLS/MJF**
- Depowder and clean
- Dye or paint (optional)
- Sealing (if required)
2. **SLA/DLP**
- Wash (IPA or solvent)
- UV post-cure
- Support removal
- Sanding/finishing
## Process Integration
- ME-019: Additive Manufacturing Process Development
## Input Schema
```json
{
"part_model": "CAD file reference",
"material_requirement": {
"type": "metal|polymer",
"specific": "string (e.g., Ti6Al4V, Nylon 12)",
"properties": "strength|stiffness|temperature|biocompatible"
},
"quantity": "number",
"quality_requirements": {
"tolerance": "number (mm)",
"surface_finish": "string",
"critical_features": "array"
},
"timeline": "prototype|production",
"budget_constraint": "number (optional)"
}
```
## Output Schema
```json
{
"process_recommendation": {
"technology": "string",
"material": "string",
"machine": "string (if specific)"
},
"build_preparation": {
"orientation": "description and rationale",
"support_volume": "number (cm3)",
"build_time": "number (hours)",
"material_usage": "number (kg)"
},
"dfam_recommendations": [
{
"feature": "string",
"issue": "string",
"recommendation": "string"
}
],
"post_processing": "array of steps",
"cost_estimate": {
"material": "number",
"machine_time": "number",
"post_processing": "number",
"total": "number"
}
}
```
## Best Practices
1. Design for AM from the start, not as afterthought
2. Understand process limitations before design
3. Optimize orientation for quality, not just time
4. Plan for post-processing in design stage
5. Validate material properties for application
6. Consider total cost including post-processing
## Integration Points
- Connects with CAD Modeling for geometry
- Feeds into Material Testing for property validation
- Supports DFM Review for manufacturability
- Integrates with FAI Inspection for qualityRelated Skills
process-builder
Scaffold new babysitter process definitions following SDK patterns, proper structure, and best practices. Guides the 3-phase workflow from research to implementation.
babysitter
Orchestrate via @babysitter. Use this skill when asked to babysit a run, orchestrate a process or whenever it is called explicitly. (babysit, babysitter, orchestrate, orchestrate a run, workflow, etc.)
yolo
Run Babysitter autonomously with minimal manual interruption.
user-install
Install the user-level Babysitter Codex setup.
team-install
Install the team-pinned Babysitter Codex workspace setup.
retrospect
Summarize or retrospect on a completed Babysitter run.
resume
Resume an existing Babysitter run from Codex.
project-install
Install the Babysitter Codex workspace integration into the current project.
plan
Plan a Babysitter workflow without executing the run.
observe
Observe, inspect, or monitor a Babysitter run.
model
Inspect or change Babysitter model-routing policy by phase.
issue
Run an issue-centric Babysitter workflow.