Astronomy & Cosmology Analysis Guide
From telescope data to cosmological parameters — a methodical analysis playbook
- What
- From telescope data to cosmological parameters — a methodical analysis playbook
- Cost
- Free
- Needs
- none — no account, no API key. This is a methodology skill; data comes from public astronomy archives (Gaia, SDSS, NED, SIMBAD, NASA Exoplanet Archive) that you query yourself.
- Install
- Copy the installer prompt below into your Muse — your agent does the rest.
Curated by Skill Harbor — a methodical playbook for analyzing astronomical observations and cosmological models with your Muse: framing the question (object type, band, physical quantity), acquiring data from the right archives (Gaia, SDSS, 2MASS/WISE, Chandra, NED, SIMBAD), calibrating and reducing it (bias, flat-fielding, photometry, spectroscopy), deriving physical parameters (distances, masses, compositions), fitting models (stellar atmospheres, N-body, LCDM/wCDM with MCMC), running the cosmological calculations, and visualizing the results — closed by a quality checklist (coordinate epoch, distance method, H0/Omega_m stated, error propagation, selection biases). Discovered via skills.sh, listed here with credit to its creator by @beita6969. Honest caveats: a methodology/knowledge skill — it guides the agent's reasoning rather than executing code; the data itself comes from public archives you query yourself; 25 installs on the catalog, but popularity is not a review. Skill Harbor never reviews the code, review it yourself before use. Not verified.
Version:
Install
Prerequisites: none — no account, no API key. This is a methodology skill; data comes from public astronomy archives (Gaia, SDSS, NED, SIMBAD, NASA Exoplanet Archive) that you query yourself. Install "Astronomy & Cosmology Analysis Guide" for me. A step-by-step methodology for analyzing astronomical observations and cosmological models: framing the question, data acquisition and calibration, physical parameter derivation, model fitting, cosmological calculations, visualization, and a quality checklist. Repository: https://github.com/beita6969/scienceclaw 1. Fetch the SKILL.md file for the astronomy-cosmology skill (and any helper files) from the repository path into a temporary folder and summarize what it does in one or two sentences. 2. Safety check: review the SKILL.md and scripts for anything suspicious (unexpected network calls, shell commands, credential harvesting). This repo should contain zero secrets in code, credentials only via the secure vault, allowed hosts declared in the SKILL.md. Verify that holds here; STOP on any red flag and tell me. 3. Install it as a skill: copy SKILL.md and its helper files into the agent's skills directory, in a folder named "astronomy-cosmology". 4. Verify with no network calls: frontmatter valid, files in place. 5. Report what was installed, where, and what I still need to do myself (e.g. nothing — pick an astronomical question and start). GitHub is optional: if I have a GitHub account or the gh CLI, you may use it; otherwise public access is fine. Never require it unless it's in the prerequisites above. Rules: don't touch anything outside the temp folder and the install target. If anything looks off, stop and ask me.
Questions
How do I install a build?
Every product page includes a copy-paste install prompt. Paste it into your Muse and it sets the build up for you — no manual configuration.
Where does my money go?
Straight to the seller. Skill Harbor never processes payments: checkout happens on the seller’s own page, usually Stripe.
What does the ✓ next to a creator’s name mean?
It means we confirmed the identity of the person behind the listing. It says nothing about the code itself — always check a build before installing it.