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diffraction-scatter

v1.0.0

Use this skill for diffraction / scattering data processing with pyFAI. It covers the full workflow: calibration (generating .poni files), azimuthal integrat...

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byTIANYI MA@tianyima96
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
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Purpose & Capability
Name/description (pyFAI post-PONI integration) align with the included scripts and library code: inspecting .poni files, iterating frames from EDF/TIFF/HDF5/NPY, applying masks/corrections, and running pyFAI integration methods. The declared requirements (none) match that the skill is self-contained and implements its own helpers.
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Instruction Scope
SKILL.md instructs the agent to use bundled scripts (inspect_poni, install_pyfai_env, integrate_with_poni) and to collect only inputs relevant to diffraction processing (image files, .poni, masks, dark/flat). The instructions do not ask for unrelated files, credentials, or to transmit data to unknown external endpoints. Outputs are written to disk and progress emitted as JSONL to stdout as described.
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Install Mechanism
There is no registry 'install' spec, but the included helper (lib/install_env.py) will create a Python virtualenv and call pip to install packages (pyFAI, fabio, h5py, numpy) from package indices. This is expected for a Python-based skill but means network downloads from PyPI will occur and new packages will be written to disk; run in an isolated environment if you want to restrict network/source trust.
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Credentials
The skill does not require or read any environment variables, credentials, or config paths beyond standard filesystem access to input/output files. No secrets or unrelated service tokens are requested.
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Persistence & Privilege
Flags show no always:true and the skill is user-invocable only. The code creates a virtualenv and writes per-frame outputs/manifest in the working directory — normal behavior for a data-processing tool and limited in scope to its own files.
Assessment
This skill appears to do exactly what it says: inspect .poni files and run pyFAI-based integrations. Before running: (1) review the bundled scripts (install helper calls pip and creates a venv) and run them in a controlled directory or sandbox/VM if you are cautious; (2) be aware the installer will download packages from PyPI (network); (3) the runner will write per-frame CSV/HDF5/NPZ outputs and a manifest.jsonl to disk and print JSONL events to stdout — ensure you run it where that output is acceptable. No credentials or external endpoints are requested by the skill.

Like a lobster shell, security has layers — review code before you run it.

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License

MIT-0
Free to use, modify, and redistribute. No attribution required.
Termshttps://spdx.org/licenses/MIT-0.html

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