working-with-marimo
Interactive development in marimo notebooks with validation loops. Use for creating/editing marimo notebooks and verifying execution.
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8Repository stars across indexed skills
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691Repository stars may repeat across skills from the same repository.
Interactive development in marimo notebooks with validation loops. Use for creating/editing marimo notebooks and verifying execution.
Loads internal CausalPy example datasets. Use when the user needs example data or asks about available demos.
Selects the appropriate quasi-experimental method (DiD, ITS, SC) based on data structure and research questions. Use when the user is unsure which method to apply.
Performs placebo-in-time sensitivity analysis to validate causal claims. Use when checking model robustness, verifying lack of pre-intervention effects, or ensuring observed effects are not spurious.
Fits causal models, estimates impacts, and plots results using CausalPy. Use when performing analysis with DiD, ITS, SC, or RD.
A clear description of what this skill does and when to use it. Include specific trigger keywords and task types that should activate this skill. Be specific about capabilities so the AI can decide when to load...
Bayesian statistical modeling with PyMC v5+. Use when building probabilistic models, specifying priors, running MCMC inference, diagnosing convergence, or comparing models. Covers PyMC, ArviZ, pymc-bart, pymc-e...
ALWAYS use when: creating/editing marimo notebooks, working with any .py file containing @app.cell decorators, building reactive Python notebooks, doing exploratory data analysis in notebook form, converting Ju...
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