tem-image-analyzer
Transmission Electron Microscopy image analysis skill for nanoparticle size, morphology, and crystallography assessment
Profile →npx skills add a5c-ai/babysitter --skill tem-image-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.
# 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 1. **Particle Detection** - Apply appropriate thresholding - Use watershed for touching particles - Count minimum 200 particles for statistics 2. **Size Measurement** - Calibrate pixel size from scale bar - Measure Feret diameter or equivalent circular diameter - Report mean, standard deviation, distribution 3. **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 ```json {
- Purpose
- Capabilities
- Usage Guidelines
- Image Analysis Workflow
- Process Integration
- Input Schema
- Output Schema
What does the tem-image-analyzer skill do?
Transmission Electron Microscopy image analysis skill for nanoparticle size, morphology, and crystallography assessment
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill tem-image-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.