scale-up-analyzer
Process scale-up analysis skill for dimensional analysis, similarity criteria, and pilot-to-production transitions
Profile →npx skills add a5c-ai/babysitter --skill scale-up-analyzer --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.
# 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 - the
- Purpose
- Capabilities
- Usage Guidelines
- When to Use
- Prerequisites
- Best Practices
- Process Integration
- Configuration
- Output Artifacts
What does the scale-up-analyzer skill do?
Process scale-up analysis skill for dimensional analysis, similarity criteria, and pilot-to-production transitions
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill scale-up-analyzer --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.