tem-image-analyzer

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

509 stars

Best use case

tem-image-analyzer is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

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

Teams using tem-image-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

$curl -o ~/.claude/skills/tem-image-analyzer/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/specializations/domains/science/nanotechnology/skills/tem-image-analyzer/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/tem-image-analyzer/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How tem-image-analyzer Compares

Feature / Agenttem-image-analyzerStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

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

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

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

## Output Schema

```json
{
  "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"
  }
}
```

Related Skills

image-optimization

509
from a5c-ai/babysitter

Image formats, responsive images, lazy loading, and CDN integration.

responsive-image

509
from a5c-ai/babysitter

Generate responsive image sets with srcset, WebP/AVIF conversion, and art direction

terraform-analyzer

509
from a5c-ai/babysitter

Specialized skill for analyzing Terraform configurations. Supports parsing, security scanning (tfsec, checkov), cost estimation (infracost), drift detection, and plan visualization across AWS, Azure, and GCP.

db-query-analyzer

509
from a5c-ai/babysitter

Analyze database query performance with execution plans and index recommendations

code-complexity-analyzer

509
from a5c-ai/babysitter

Analyze code complexity metrics including cyclomatic complexity, code smells, and technical debt

cloudformation-analyzer

509
from a5c-ai/babysitter

Validate and analyze AWS CloudFormation templates for security and best practices

semantic-code-analyzer

509
from a5c-ai/babysitter

LLM-powered semantic analysis of code diffs to detect business-logic trojans

sast-analyzer

509
from a5c-ai/babysitter

Static Application Security Testing orchestration and analysis. Execute Semgrep, Bandit, ESLint security plugins, CodeQL, and other SAST tools. Parse, prioritize, and deduplicate findings across multiple tools with remediation guidance.

crypto-analyzer

509
from a5c-ai/babysitter

Cryptographic implementation analysis and validation for encryption algorithms, key sizes, and certificate management

semver-analyzer

509
from a5c-ai/babysitter

Analyze code changes and determine semantic version bumps. Detect breaking changes automatically, suggest version bump (major/minor/patch), generate changelog entries, and validate version consistency.

api-diff-analyzer

509
from a5c-ai/babysitter

Compare API specifications to detect breaking changes. Compare OpenAPI spec versions, categorize changes by severity, generate migration guides, and block breaking changes in CI.

process-analyzer

509
from a5c-ai/babysitter

Analyze processes, identify workflows, define boundaries and scope, and map process requirements for specialization creation.