xrd-pyfai
Skill4 starsChanged 6 months agoNo licenceView on GitHub
Reduce and analyze raw 2D XRD, GIWAXS, or WAXS detector images with pyFAI. Use when the task starts from detector images plus geometry calibration (.poni) and the goal is 1D radial integration, 2D cake/polar remapping, azimuthal texture profiling, mask/dark/flat correction, or reusable preprocessing artifacts for thin-film diffraction analysis. Especially useful for orientation evidence, texture spread, and image-to-curve preprocessing before downstream peak fitting. Not for Rietveld refinement, structure solution, or fitting already-integrated x-y curves.
In this repository12 other files it gives its agents.
- AGENTS.mdAGENTS.md
- band-align-plotSkill
- band-diagram-calcSkill
- comsol-opto-simulationSkill
- humanizerSkill
- interface-band-offsetSkill
- literature-searchSkill
- origin-pro-mcpSkill
- photodetector-pyradiSkill
- pythesis-plotSkill
- scientifySkill
- zotero-literature-reviewSkill
The file
We split this skill into the rules it gives an agent
8 rules. About 0 are common, 6 are distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈6
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
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