Babysitter dls-particle-sizer

Dynamic Light Scattering skill for hydrodynamic size distribution and polydispersity analysis

install

source · Clone the upstream repo

git clone https://github.com/a5c-ai/babysitter

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/a5c-ai/babysitter "$T" && mkdir -p ~/.claude/skills && cp -r "$T/library/specializations/domains/science/nanotechnology/skills/dls-particle-sizer" ~/.claude/skills/a5c-ai-babysitter-dls-particle-sizer && rm -rf "$T"

manifest: library/specializations/domains/science/nanotechnology/skills/dls-particle-sizer/SKILL.md

DLS Particle Sizer

Purpose

The DLS Particle Sizer skill provides dynamic light scattering analysis for nanoparticle hydrodynamic size determination, enabling rapid, non-destructive measurement of size distributions and stability assessment.

Capabilities

Hydrodynamic diameter measurement
Polydispersity index (PDI) calculation
Size distribution analysis (intensity, volume, number)
Temperature-dependent measurements
Multi-angle DLS analysis
Particle concentration estimation

Usage Guidelines

DLS Measurement

Sample Preparation
- Dilute to appropriate concentration
- Filter to remove dust
- Equilibrate temperature
Data Analysis
- Use cumulants for monomodal samples
- Apply CONTIN for multimodal
- Report intensity-weighted Z-average
Quality Metrics
- PDI < 0.1: Monodisperse
- PDI 0.1-0.3: Narrow distribution
- PDI > 0.3: Broad distribution

Process Integration

Statistical Particle Size Distribution Analysis
Nanoparticle Synthesis Protocol Development
Nanoparticle Drug Delivery System Development

Input Schema

{
  "sample_id": "string",
  "solvent": "string",
  "temperature": "number (C)",
  "refractive_index": "number",
  "viscosity": "number (cP)"
}

Output Schema

{
  "z_average": "number (nm)",
  "pdi": "number",
  "distribution": {
    "intensity": {"peaks": [{"size": "number", "percent": "number"}]},
    "volume": {"peaks": [{"size": "number", "percent": "number"}]},
    "number": {"peaks": [{"size": "number", "percent": "number"}]}
  },
  "quality_metrics": {
    "intercept": "number",
    "baseline": "number"
  }
}