What problem does it solve? Working with Quarto .qmd notebooks that use a Python kernel involves subtle conventions—kernel registration, papermill parameter injection, and render environment quirks—that cause confusing failures like missing nbclient errors or silently failed renders. This Skill codifies the correct patterns so notebooks render reliably every time. ## Core Features & Use Cases - Standardized front matter: Enforces the jupyter: py_general kernel with code-fold: true and toc: true defaults for all Python qmd notebooks. - Parameterized notebooks with papermill: Shows how to tag a parameters cell and render with overrides via render_notebook render notebook.qmd -P key:value, clarifying that params arrive as plain Python variables, not an R-style params dict. - Reliable rendering and verification: Uses the render_notebook shim (which logs host, Slurm allocation, and peak memory) and teaches how to confirm success via Output created: and HTML timestamps, since conda run can exit 0 despite internal cell errors. - Use Case: You need to rerun the same gene-analysis notebook for a dozen different genes. Define defaults in a tagged parameters cell, then loop render_notebook render analysis.qmd -P gene:MBD5 for each target. ## Quick Start Ask the AI to create a parameterized Quarto Python notebook for a gene analysis using the py_general kernel and render it with a specific gene override.
