Babysitter tem-image-analyzer

Transmission Electron Microscopy image analysis skill for nanoparticle size, morphology, and crystallography assessment

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 "$T/library/specializations/domains/science/nanotechnology/skills/tem-image-analyzer" ~/.claude/skills/a5c-ai-babysitter-tem-image-analyzer && rm -rf "$T"

manifest: library/specializations/domains/science/nanotechnology/skills/tem-image-analyzer/SKILL.md

TEM Image Analyzer

Purpose

The TEM Image Analyzer skill provides comprehensive analysis of transmission electron microscopy data for nanomaterial characterization, enabling automated particle detection, size distribution analysis, and crystallographic structure determination.

Capabilities

Automated particle detection and sizing
Morphology classification
Lattice fringe analysis
Selected area electron diffraction (SAED) indexing
High-resolution TEM (HRTEM) analysis
STEM-HAADF imaging

Usage Guidelines

Image Analysis Workflow

Particle Detection
- Apply appropriate thresholding
- Use watershed for touching particles
- Count minimum 200 particles for statistics
Size Measurement
- Calibrate pixel size from scale bar
- Measure Feret diameter or equivalent circular diameter
- Report mean, standard deviation, distribution
Crystallographic Analysis
- Index SAED patterns to phase
- Measure d-spacings from lattice fringes
- Identify zone axis from HRTEM

Process Integration

Multi-Modal Nanomaterial Characterization Pipeline
Statistical Particle Size Distribution Analysis
In-Situ Characterization Experiment Design

Input Schema

{
  "image_path": "string",
  "analysis_type": "sizing|morphology|crystallography",
  "scale_bar": {"length": "number", "pixels": "number"},
  "expected_material": "string (for indexing)"
}

Output Schema

{
  "particle_statistics": {
    "count": "number",
    "mean_size": "number (nm)",
    "std_dev": "number (nm)",
    "size_distribution": {"bins": [], "counts": []}
  },
  "morphology": {
    "shapes": [{"type": "string", "fraction": "number"}],
    "aspect_ratio": "number"
  },
  "crystallography": {
    "phase": "string",
    "d_spacings": ["number (nm)"],
    "zone_axis": "string"
  }
}