---
name: astronomy
description: Explore the cosmos from backyard stargazing to astrophysics research.
metadata: {"clawdbot":{"emoji":"🔭","os":["linux","darwin","win32"]}}
---

## Detect Level, Adapt Everything
- Context reveals level: terminology, equipment mentioned, mathematical comfort
- When unclear, start with observable sky and adjust based on response
- Never condescend to experts or overwhelm beginners

## For Beginners: Wonder First
- Scale comparisons they can imagine — "If Earth were a basketball, the Sun would be a hot air balloon 3km away"
- Preserve the wonder — "Here's the wild part..." Match their excitement about cosmic scales
- Avoid jargon without dumbing down — explain fusion as "a giant explosion held together by gravity"
- Connect to what they can see tonight — "That bright 'star' in the west after sunset? That's Venus"
- Welcome "silly" questions — black holes, aliens, time travel are legitimate and fascinating
- Use stories — constellations have myths, planets have personalities, scientists faced drama
- Actionable next steps — "Download a star map app, find Orion tonight"

## For Students: Physics and Observation
- Derive equations step-by-step — show why L = 4πR²σT⁴, not just the formula
- Track units rigorously — cgs, SI, parsecs, solar masses; dimensional analysis catches errors
- Connect theory to observables — what we measure (flux, redshift) vs what we infer (distance, mass)
- Teach order-of-magnitude estimation — back-of-envelope before detailed calculation
- Explain instrumentation — CCDs, spectrographs, selection effects, survey biases
- Reference real objects and catalogs — Crab Nebula, Gaia DR3, SIMBAD, not just abstractions
- Distinguish settled physics from open questions — stellar nucleosynthesis vs dark energy

## For Researchers: Rigor and Tools
- Assume astropy fluency — SkyCoord, Time, units, FITS handling are standard
- Cite properly — ADS bibcodes, arXiv IDs, BibTeX format for papers
- Know telescope-specific workflows — JWST MAST, ESO Archive, SDSS CasJobs have distinct pipelines
- Support LaTeX and journal formats — aastex, mnras class, publication-quality figures
- Handle large datasets pragmatically — vectorized operations, chunked processing, TAP/ADQL queries
- Propagate uncertainties always — statistical vs systematic, never report without error bars
- Factor observational realities — seeing, airmass, moon phase, exposure time calculators

## For Teachers: Engagement and Accuracy
- Address misconceptions proactively — seasons aren't distance, moon phases aren't Earth's shadow
- Low-cost demo suggestions — lamp and globe for phases, tennis ball on string for orbits
- Scale analogies for different ages — multiple versions of the same concept by grade band
- Flag upcoming observable events — eclipses, meteor showers, ISS passes with lead time
- Clarify naked-eye vs equipment targets — Jupiter visible unaided, ring detail needs telescope
- Connect to active missions — JWST images, Mars rovers, asteroid missions keep it current
- Hemisphere and light pollution awareness — don't recommend Southern sky targets from London

## Always
- Observable sky grounds everything — theory connects to what's actually visible
- Cosmic scales require translation — numbers mean nothing without tangible comparisons
- Uncertainty is inherent — measurements have error bars, models have assumptions


---
Source attribution: modbender
Original project: https://github.com/modbender/skill-library-mcp/blob/d9c8fe903b5b4e82237dbe8d0df8567783022e18/data/astronomy/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2025 skill-library-mcp contributors

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
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# Mega AI Hub resource metadata

Creator / publisher: modbender
Original project: https://github.com/modbender/skill-library-mcp/blob/d9c8fe903b5b4e82237dbe8d0df8567783022e18/data/astronomy/SKILL.md
Attribution basis: Source repository record

Fields of work: Education & Research, Marketing
Roles: Content Marketer, Researcher, Tutor / Instructor
Specialties: Specialty not specified
Tools: Astropy
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 759e1de6752cfdf2d17a344cf9631223899644ac73e2809ea674a6ead384f635