scale-up-analyzer
Process scale-up analysis skill for dimensional analysis, similarity criteria, and pilot-to-production transitions
Best use case
scale-up-analyzer is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Process scale-up analysis skill for dimensional analysis, similarity criteria, and pilot-to-production transitions
Teams using scale-up-analyzer 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/scale-up-analyzer/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How scale-up-analyzer Compares
| Feature / Agent | scale-up-analyzer | 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?
Process scale-up analysis skill for dimensional analysis, similarity criteria, and pilot-to-production transitions
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
# Scale-Up Analyzer Skill
## Purpose
The Scale-Up Analyzer Skill supports process scale-up from laboratory to pilot to production scale using dimensional analysis, similarity criteria, and scale-up correlations.
## Capabilities
- Dimensional analysis
- Similarity criteria evaluation
- Scale-up factor calculation
- Heat transfer scale-up
- Mass transfer scale-up
- Mixing scale-up (power per volume, tip speed)
- Reaction scale-up considerations
- Risk assessment for scale-up
## Usage Guidelines
### When to Use
- Scaling from lab to pilot
- Scaling from pilot to production
- Evaluating scale-up feasibility
- Identifying scale-sensitive parameters
### Prerequisites
- Lab/pilot data available
- Process fundamentals understood
- Critical parameters identified
- Target scale defined
### Best Practices
- Identify controlling mechanisms
- Maintain appropriate similarity criteria
- Plan incremental scale-up steps
- Validate at each scale
## Process Integration
This skill integrates with:
- Scale-Up Analysis
- Process Simulation Model Development
- Performance Testing and Validation
## Configuration
```yaml
scale-up-analyzer:
scale-up-methods:
- geometric-similarity
- dynamic-similarity
- thermal-similarity
scale-factors:
- 10x
- 100x
- 1000x
```
## Output Artifacts
- Scale-up calculations
- Similarity analysis
- Risk assessments
- Scale-up recommendations
- Parameter predictionsRelated Skills
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