Ssw Plugin
- Updated February 7, 2026
- tykimos/ssw-plugin
ssw-plugin is a Claude Code marketplace that distributes a Sun and Space Weather toolkit with four skills to download, preprocess, train ML on, and visualize solar observation FITS data from SDO, STEREO, and Solar Orbite
About
ssw-plugin is tykimos's Claude Code marketplace bundling one plugin with four slash skills: ssw-download, ssw-prep, ssw-ml, and ssw-viz. The workflow moves from raw FITS downloads through ML-ready preprocessing, PyTorch model training, and matplotlib visualizations using the ssw-tools Python package and SunPy stack. Supported missions include SDO/AIA (7 wavelengths from 94-335 Å), STEREO SECCHI EUVI, and Solar Orbiter EUI, with JSOC registration required for SDO. SDO/AIA spans 2010-present at 12-second cadence; STEREO-A remains active while STEREO-B contact ended in 2014; Solar Orbiter EUI runs from 2020 with intermittent coverage. Optional torch, torchvision, and scikit-image packages unlock ssw-ml training workflows. Natural-language prompts can invoke skills without typing slash commands once the plugin is enabled. Install via `/plugin marketplace add https://github.com/tykimos/ssw-plugin.git` then `/plugin install ssw-plugin@ssw-plugin`, and pip install git+https://github.com/sswlab/ssw-tools plus sunpy and optional torch. Use when building solar-physics ML pipelines inside Claude Code—not for unrelated web app development.
- 4 skills: ssw-download, ssw-prep, ssw-ml, ssw-viz slash commands
- Supports SDO/AIA (7 wavelengths), STEREO EUVI, Solar Orbiter EUI missions
- Pipeline: raw FITS download → ML-ready prep → PyTorch training → matplotlib viz
- Depends on git+https://github.com/sswlab/ssw-tools, sunpy, astropy, aiapy
- README documents install guide with marketplace and pip prerequisites
Ssw Plugin by the numbers
- Data as of Jul 7, 2026 (Skillselion catalog sync)
/plugin marketplace add tykimos/ssw-pluginAdd your badge
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| Last updated | February 7, 2026 |
|---|---|
| Repository | tykimos/ssw-plugin ↗ |
How do you automate solar FITS download and ML prep in Claude Code?
Download SDO, STEREO, or Solar Orbiter FITS data, preprocess it, train ML models, and plot results via four Claude Code slash skills.
Who is it for?
Space-weather or solar-physics developers using Claude Code who work with SDO, STEREO, or Solar Orbiter FITS archives.
Skip if: General web developers or projects without Python solar-data dependencies and mission-specific download credentials.
What you get
Downloaded FITS datasets, ML-ready preprocessed files, trained model artifacts, and matplotlib visualization plots from the four-skill pipeline.
- FITS datasets
- Preprocessed ML arrays
- Training outputs
By the numbers
- Bundles 4 slash skills across download, prep, ML, and visualization
- Documents 7 SDO/AIA wavelengths from 94 Å through 335 Å
Plugins in this marketplace
1 plugin - install individually after you add the marketplace.
Recommended Marketplaces
How it compares
Pick ssw-plugin for solar FITS science pipelines; use generic data-science MCPs when you are not working with heliophysics mission archives.
FAQ
Which missions does Ssw Plugin support?
Ssw Plugin covers SDO/AIA (7 wavelengths, 2010-present), STEREO-A/B SECCHI EUVI, and Solar Orbiter EUI FSI data, with JSOC registration required for SDO downloads.
How do you install Ssw Plugin dependencies?
After installing the marketplace plugin, run `pip install git+https://github.com/sswlab/ssw-tools sunpy matplotlib astropy aiapy` and optional `torch torchvision scikit-image` for ssw-ml.
What is the Ssw Plugin skill pipeline order?
Ssw Plugin expects ssw-download for raw FITS, ssw-prep for ML-ready preprocessing, ssw-ml for model training, and ssw-viz for plotting and animation outputs.