rudrathegreat
UserA catered AI toolkit for astronomers
Categories
Indexed Skills (31)
enterprise-noise-model-builder
Build white, red, dispersion-measure, and common noise models for pulsar timing arrays with Enterprise.
literature-review-builder
Synthesize astronomy papers into a structured literature review with themes, evidence, and open questions.
methodology-extractor
Extract datasets, pipelines, model parameterizations, equations, and assumptions from astronomy papers.
paper-summariser
Summarize astronomy papers with emphasis on observations, instruments, methods, and physical parameters.
research-gap-analysis
Identify unresolved questions, inconsistent measurements, and promising research gaps in astronomy literature.
testing-assistant
Design pytest suites for scientific calculations, numerical edge cases, and regression protection.
bilby-model-builder
Construct Bayesian likelihoods, priors, and model classes with Bilby for astronomical observations.
bilby-model-comparison
Compare physical models fitted with Bilby using Bayesian evidence and posterior statistics.
bilby-prior-design
Design, evaluate, and implement prior probability distributions for astronomical inference with Bilby.
bilby-result-interpreter
Interpret Bilby result files, Bayes factors, evidence values, and posterior parameter bounds.
emcee-convergence-analysis
Diagnose emcee chain convergence using autocorrelation, acceptance fractions, and stability checks.
emcee-mcmc-debugger
Diagnose and fix MCMC likelihood, prior, initialization, NaN, and sampling failures.
emcee-posterior-diagnostics
Analyze posterior distributions, credible intervals, correlations, and diagnostic summaries from emcee chains.
emcee-sampler-design
Design robust emcee samplers, probability functions, initialization strategies, and production runs.
enterprise-debugger
Diagnose numerical, configuration, and sampling failures in Enterprise pulsar timing array analyses.
enterprise-hypermodel-assistant
Configure and troubleshoot Enterprise hypermodels for Bayesian model selection and trans-dimensional sampling.
enterprise-pta-model-designer
Design Enterprise PTA models with spatial correlations and gravitational-wave background components.
enterprise-result-interpreter
Interpret Enterprise chains, parameter constraints, Bayes factors, and gravitational-wave background limits.
paper-comparison
Compare astronomy papers across datasets, methods, assumptions, measurements, and conclusions.
documentation-writer
Write scientific Python documentation, docstrings, READMEs, and reference material.
performance-optimizer
Optimize scientific Python workloads with profiling, vectorization, compilation, and parallel execution.
pipeline-designer
Design reproducible scientific data-processing, modeling, and visualization pipelines.
python-analysis-architect
Structure maintainable Python analysis packages and research codebases for astronomy projects.
replication-assistant
Translate published scientific methods and equations into a reproducible implementation plan and code.
reproducibility-auditor
Audit scientific analyses for deterministic environments, provenance, repeatability, and complete documentation.
scientific-code-reviewer
Review scientific Python for numerical correctness, units, precision, robustness, and maintainability.
astronomy-style-guide
Apply astronomy journal conventions and accessibility standards to scientific figures.
corner-plot-specialist
Design and customize publication-quality corner plots for posterior samples and correlations.
figure-critic
Critique astronomy figures for clarity, accessibility, correctness, and publication readiness.
publication-figure-designer
Create publication-quality scientific figure layouts, styles, and plotting templates.
timing-residual-visualisation
Visualize pulsar timing residuals against time, frequency, or orbital phase for analysis and publication.
Bio shown is the top-scored skill's repo description as a fallback — real GitHub bios land in a future update.