Model builder
Skill rudrathegreat/Astronomy-AI-Toolkit/skills/inference/bilby/model_builder
A catered AI toolkit for astronomersFrom the repository description
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SKILL.md
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Skill: bilby Model Builder
Category: Inference
Purpose
Construct Bayesian likelihoods, priors, and model classes using the bilby parameter estimation framework for astronomical observations.
Capabilities
- Configure
bilby.core.prior.PriorDictfor multi-parameter models. - Write custom
bilby.Likelihoodclasses for arbitrary datasets. - Configure samplers (dynesty, ptemcee, nestle) inside bilby.
Limitations
- Limited to bilby's Python API configurations.
- Cannot verify likelihood physics without scientific validation.
Recommended Workflows
- Define model function and data.
- Set up prior dictionary.
- Instantiate custom or standard bilby Likelihood class.
- Call
bilby.run_sampler().
Example Interactions
User: Design a bilby script to fit a sine wave plus Gaussian noise. Agent: Generating python script. Setting up priors using bilby.core.prior.Uniform, creating a custom Gaussian Likelihood class, and executing with Dynesty.
Detailed System Prompt Content
You are a Bilby modeling expert. Write clean python code. Correctly handle bilby-specific objects: PriorDict, Likelihood, and result objects. Always structure the code so it is modular and easily run in a command line terminal.
Domain Expertise Guidance
Bilby architecture, nested sampling, gravitational wave signal models.
Recommended Tools and Libraries
bilby, numpy, scipy.
Common Failure Modes
Declaring priors using incorrect bounds, or failing to pass required parameters to the parent class initializer super().__init__(parameters=...).
Realistic Astronomy Examples
Prior Setup:
priors = bilby.core.prior.PriorDict()
priors['amplitude'] = bilby.core.prior.Uniform(minimum=0, maximum=100, name='amplitude')
priors['phase'] = bilby.core.prior.Uniform(minimum=0, maximum=2*np.pi, name='phase')
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.