physical-sciences Plugin
Physics, astronomy, quantum computing, materials and earth science.
So installierst du das physical-sciences Plugin
Führe beide Befehle in Claude Code aus. Der erste fügt den Marketplace einmalig hinzu; der zweite installiert das Plugin.
/plugin marketplace add KalarisLabs/research-agent-skills
/plugin install physical-sciences@research-agent-skillsWas ist in physical-sciences enthalten
10 Teile wurden aus den eigenen Dateien des Plugins gelesen.
Skills 10
Claude lädt es, wenn die Aufgabe passt- astropy
Core Python library for astronomy and astrophysics workflows that need Astropy APIs, including units/quantities, coordinates, FITS I/O, tables, time systems, WCS, and cosmology. Use when implementing or debugging astronomical data analysis code with Astropy.
- cirq
Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip.
- fluidsim
Plan, configure, inspect, restart, and analyze bounded FluidSim computational-fluid-dynamics simulations with explicit numerical-validity and HPC safety checks. Use for FluidSim solver selection, parameter review, FFT/MPI setup, output diagnostics, or restart compatibility.
- geomaster
Provides geospatial and Earth observation workflows using GeoPandas, Rasterio, GDAL, Xarray, Shapely, Laspy, PDAL, Google Earth Engine, and STAC/Planetary Computer, covering Sentinel, Landsat, MODIS, SAR and hyperspectral imagery, spectral indices, terrain and network analysis, point clouds, COGs, CRS handling, and spatial ML, with code in Python, R, Julia, JavaScript, C++, Java, Go, and Rust. Use when computing NDVI or other indices from satellite imagery, when running vector overlays, reprojection, or spatial statistics on shapefiles, GeoJSON, or GeoPackage data, when searching STAC catalogs and reading cloud-optimized GeoTIFFs, when classifying land cover or training ML models on Earth observation data, or when doing terrain, hydrology, or point cloud analysis. Not for general non-spatial data analysis or tabular ML.
- geopandas
Guidance and local audit CLIs for Python workflows using GeoPandas 1.1.4 GeoSeries and GeoDataFrame for planar vector data: CRS handling, geometry validity and repair, sjoin, overlay, clip, dissolve, union, GeoPackage, GeoParquet and PostGIS I/O, and plotting. Use when reprojecting or assigning a CRS, auditing invalid or empty geometries, running spatial joins and checking cardinality, exporting vector data with a reproducible contract, or migrating code from GeoPandas 0.14 to 1.x. Use when checking privacy risks in coordinate data. Do not use for raster data or geodesic-only calculations.
- openpiv
Keine Beschreibung in der Datei gefunden.
- pennylane
Keine Beschreibung in der Datei gefunden.
- pymatgen
Keine Beschreibung in der Datei gefunden.
- qiskit
Keine Beschreibung in der Datei gefunden.
- qutip
Keine Beschreibung in der Datei gefunden.
Verwendung von physical-sciences in Claude Code
Skills benötigen keinen Command. Claude liest sie, wenn deine Anfrage dem entspricht, was sie beschreiben.
Aktualisieren, deaktivieren oder entfernen
- Plugin aktualisieren (shell)
- claude plugin update physical-sciences@research-agent-skills
- marketplace aktualisieren
- /plugin marketplace update research-agent-skills
- Vorerst deaktivieren
- /plugin disable physical-sciences@research-agent-skills
- Entfernen
- /plugin uninstall physical-sciences@research-agent-skills
Skills in physical-sciences
- cirqKalarisLabs/research-agent-skills
Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip.
7 Dateien126Stars - fluidsimKalarisLabs/research-agent-skills
Plan, configure, inspect, restart, and analyze bounded FluidSim computational-fluid-dynamics simulations with explicit numerical-validity and HPC safety checks. Use for FluidSim solver selection, parameter review, FFT/MPI setup, output diagnostics, or restart compatibility.
16 Dateien126Stars - geopandasKalarisLabs/research-agent-skills
Guidance and local audit CLIs for Python workflows using GeoPandas 1.1.4 GeoSeries and GeoDataFrame for planar vector data: CRS handling, geometry validity and repair, sjoin, overlay, clip, dissolve, union, GeoPackage, GeoParquet and PostGIS I/O, and plotting. Use when reprojecting or assigning a CRS, auditing invalid or empty geometries, running spatial joins and checking cardinality, exporting vector data with a reproducible contract, or migrating code from GeoPandas 0.14 to 1.x. Use when checking privacy risks in coordinate data. Do not use for raster data or geodesic-only calculations.
14 Dateien126Stars - astropyKalarisLabs/research-agent-skills
Core Python library for astronomy and astrophysics workflows that need Astropy APIs, including units/quantities, coordinates, FITS I/O, tables, time systems, WCS, and cosmology. Use when implementing or debugging astronomical data analysis code with Astropy.
8 Dateien126Stars - geomasterKalarisLabs/research-agent-skills
Provides geospatial and Earth observation workflows using GeoPandas, Rasterio, GDAL, Xarray, Shapely, Laspy, PDAL, Google Earth Engine, and STAC/Planetary Computer, covering Sentinel, Landsat, MODIS, SAR and hyperspectral imagery, spectral indices, terrain and network analysis, point clouds, COGs, CRS handling, and spatial ML, with code in Python, R, Julia, JavaScript, C++, Java, Go, and Rust. Use when computing NDVI or other indices from satellite imagery, when running vector overlays, reprojection, or spatial statistics on shapefiles, GeoJSON, or GeoPackage data, when searching STAC catalogs and reading cloud-optimized GeoTIFFs, when classifying land cover or training ML models on Earth observation data, or when doing terrain, hydrology, or point cloud analysis. Not for general non-spatial data analysis or tabular ML.
16 Dateien126Stars
Fragen zum physical-sciences Plugin
Wie installiere ich das physical-sciences Plugin?
Führe in Claude Code /plugin marketplace add KalarisLabs/research-agent-skills aus, dann /plugin install physical-sciences@research-agent-skills.
Was enthält das physical-sciences Plugin?
physical-sciences bündelt 10 Skills.
Wie aktualisiere oder entferne ich das physical-sciences Plugin?
Aktualisiere es mit claude plugin update physical-sciences@research-agent-skills in deiner shell oder über den Installed-Tab von /plugin. Entferne es mit /plugin uninstall physical-sciences@research-agent-skills.
Unter welcher Lizenz steht das physical-sciences Plugin?
MIT, wie im Manifest des Plugins angegeben.