metallurgical-analysis
Specialized skill for metallic materials analysis and metallography including grain size measurement, phase quantification, and inclusion rating
Best use case
metallurgical-analysis is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Specialized skill for metallic materials analysis and metallography including grain size measurement, phase quantification, and inclusion rating
Teams using metallurgical-analysis 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
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/metallurgical-analysis/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How metallurgical-analysis Compares
| Feature / Agent | metallurgical-analysis | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Specialized skill for metallic materials analysis and metallography including grain size measurement, phase quantification, and inclusion rating
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
# Metallurgical Analysis Skill
## Purpose
The Metallurgical Analysis skill provides specialized capabilities for characterizing metallic materials through metallographic techniques, enabling systematic evaluation of microstructure, grain size, phase distribution, and inclusion content per industry standards.
## Capabilities
- Metallographic preparation protocol selection
- Etching reagent selection for different alloys
- Grain size measurement (ASTM E112, intercept method)
- Phase fraction quantification (point count, image analysis)
- Inclusion rating (ASTM E45)
- Banding and segregation assessment
- Prior austenite grain boundary revelation
- Weld microstructure evaluation (HAZ mapping)
## Usage Guidelines
### Sample Preparation
1. **Sectioning**
- Select appropriate cutting method (abrasive, EDM, precision saw)
- Minimize heat input to prevent microstructural changes
- Identify orientation relative to processing direction
2. **Mounting**
- Choose mount type (hot compression, cold setting)
- Add conductive filler for SEM/EBSD samples
- Consider edge retention requirements
3. **Grinding and Polishing**
- Follow systematic grit progression (120 to 1200 to diamond)
- Use appropriate lubricant and rotation direction
- Verify scratch-free surface before etching
### Etching Selection
| Alloy System | Etchant | Purpose |
|--------------|---------|---------|
| Carbon steels | 2% Nital | General microstructure |
| Stainless steel | Vilella's | Martensitic structures |
| Aluminum | Keller's | Grain boundaries, precipitates |
| Titanium | Kroll's | Alpha-beta microstructure |
| Copper | FeCl3/HCl | Grain boundaries |
| Nickel superalloys | Glyceregia | Gamma prime, carbides |
### Grain Size Measurement
1. **ASTM E112 Methods**
- Comparison method: Match to standard charts
- Planimetric method: Count grains in known area
- Intercept method: Count grain boundary intersections
2. **Calculation**
- Apply magnification correction
- Use minimum 5 fields for statistical validity
- Report ASTM grain size number with standard deviation
3. **Special Cases**
- Duplex structures: Report both phases separately
- Elongated grains: Measure aspect ratio
- Prior austenite: Use specific etchants (picric acid based)
### Inclusion Rating (ASTM E45)
1. **Method Selection**
- Method A: Worst field rating
- Method D: Quantitative measurement
- Specify inclusion type (A, B, C, D sulfides, oxides)
2. **Reporting**
- Include severity (thin, heavy) and length
- Note distribution (random, stringer, cluster)
- Compare to specification limits
## Process Integration
- MS-002: Electron Microscopy Characterization
- MS-017: Root Cause Failure Analysis
## Input Schema
```json
{
"sample_id": "string",
"alloy_system": "steel|aluminum|titanium|copper|nickel",
"alloy_grade": "string",
"analysis_type": "grain_size|phase_fraction|inclusion|weld_eval",
"magnification": "number",
"etchant_used": "string"
}
```
## Output Schema
```json
{
"sample_id": "string",
"grain_size": {
"astm_number": "number",
"average_diameter": "number (microns)",
"standard_deviation": "number",
"method": "string"
},
"phase_fractions": [
{
"phase": "string",
"fraction": "number (percent)",
"morphology": "string"
}
],
"inclusion_rating": {
"method": "string",
"type_a": "number",
"type_b": "number",
"type_c": "number",
"type_d": "number"
},
"observations": "string"
}
```
## Best Practices
1. Document complete preparation procedure for reproducibility
2. Use consistent magnification within a comparative study
3. Apply appropriate etching time - under-etched is better than over-etched
4. Verify grain boundaries are fully revealed before measurement
5. Use image analysis software for quantitative phase measurements
6. Include representative micrographs in reports
## Integration Points
- Connects with Electron Microscopy for high-resolution analysis
- Feeds into Failure Analysis for metallographic investigation
- Supports Mechanical Testing for structure-property correlation
- Integrates with Heat Treatment Optimization for process developmentRelated Skills
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