Astropy
Astropy provides a streamlined interface for astronomical data manipulation and visualization, simplifying complex tasks for users.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add swn94-astropy npx -- -y @trustedskills/swn94-astropy
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"swn94-astropy": {
"command": "npx",
"args": [
"-y",
"@trustedskills/swn94-astropy"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
This skill provides access to Astropy, a Python library for astronomy. It enables AI agents to perform calculations and analyses related to astronomical data, including coordinate transformations, unit conversions, and working with FITS files (a common format for storing astronomical images). The skill allows for manipulation of celestial objects and their properties within an AI workflow.
When to use it
- Analyzing astronomical image data: Extracting information from FITS files, such as star positions or galaxy shapes.
- Calculating distances between celestial objects: Performing coordinate transformations to determine the separation between stars or planets.
- Converting between different units of measurement in astronomy: Easily switch between light-years and parsecs, for example.
- Simulating astronomical observations: Generating synthetic data based on known physical parameters.
Key capabilities
- FITS file I/O
- Coordinate transformations
- Unit conversions
- Astronomical calculations
Example prompts
- "Convert the J2000 coordinates of this star to galactic coordinates."
- "Read the data from this FITS file and calculate the average brightness."
- "What is the distance in light-years between these two stars?"
Tips & gotchas
- Requires a working Python environment with Astropy installed.
- Familiarity with astronomical concepts (e.g., coordinate systems, units) will be helpful for interpreting results.
Tags
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