Agent skill · Data & Analytics

materials-characterization

Measurement techniques for identifying composition, microstructure, and properties of engineering materials — optical and electron microscopy, x-ray diffraction, EDS and WDS spectroscopy, thermal analysis, mechanical testing, and fractography. Covers when to use which technique, sample-preparation pitfalls, and how to build a characterization plan that answers a specific engineering question rather than accumulating data for its own sake.

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill materials-characterization --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 13 KB
Bundled scripts: none
Path: skills/analysis/materials-characterization/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Materials Characterization Every materials-engineering question eventually becomes a characterization question. "Why did this fail?" becomes "what is on the fracture surface, what is the microstructure underneath, and what is the chemistry of the included phases?" "Will this alloy meet specification?" becomes "what is the grain size, the precipitate distribution, the hardness, and the tensile behavior?" "What is this stuff?" becomes a choice among the two dozen measurement techniques that can answer compositional and structural questions. This skill surveys the core techniques, identifies the question each is best at answering, and warns of the sample-preparation and interpretation mistakes that waste instrument time. **Agent affinity:** cottrell (dislocation and microstructure imaging), gordon (failure-surface characterization) **Concept IDs:** materials-measurement, materials-microstructure, materials-composition-analysis ## The Characterization Plan A plan is more important than a technique. Instruments are expensive and time-limited; characterization that does not answer a specific question is a waste. The plan has three components. 1. **The question.** Written in a single se

What's inside
Steps it walks through
  1. The Characterization Plan
  2. Hierarchy of Resolution
  3. Optical Microscopy
  4. Sample preparation (metallography)
  5. What optical answers
  6. Scanning Electron Microscopy (SEM)
  7. Secondary-electron imaging
  8. Backscatter imaging
  9. EDS and WDS
  10. Transmission Electron Microscopy (TEM)
  11. Sample preparation
  12. What TEM answers
  13. X-Ray Diffraction (XRD)
  14. Thermal Analysis
Ships with 1 file
  • metadata.json
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About this skill
What does the materials-characterization skill do?

Measurement techniques for identifying composition, microstructure, and properties of engineering materials — optical and electron microscopy, x-ray diffraction, EDS and WDS spectroscopy, thermal analysis, mechanical testing, and fractography. Covers when to use which technique, sample-preparation pitfalls, and how to build a characterization plan that answers a specific engineering question rather than accumulating data for its own sake.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill materials-characterization --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 majiayu000/claude-skill-registry, a repository with 534 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.

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