Free SKILL.md scraped from GitHub. Clone the repo or copy the file directly into your Claude Code skills directory.
npx versuz@latest install brycewang-stanford-awesome-agent-skills-for-empirical-research-skills-29-quarcs-lab-project20xxy-dot-claude-skills-executegit clone https://github.com/brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research.gitcp Awesome-Agent-Skills-for-Empirical-Research/SKILL.MD ~/.claude/skills/brycewang-stanford-awesome-agent-skills-for-empirical-research-skills-29-quarcs-lab-project20xxy-dot-claude-skills-execute/SKILL.md--- name: execute description: Executes all registered notebooks, strips noisy cell metadata, and syncs Jupytext pairs. Use when asked to re-run notebooks or refresh outputs. disable-model-invocation: true allowed-tools: Bash, Read, Write, Edit, Glob, Grep --- # Execute All Notebooks Execute all registered notebooks, strip noisy metadata, and sync Jupytext pairs. ## Steps 1. Read `_quarto.yml` and extract all notebook paths from `manuscript.notebooks` 2. For each notebook, execute it: ```bash uv run jupyter execute --inplace notebooks/<name>.ipynb ``` Record execution time and success/failure for each notebook. 3. After all notebooks execute, strip noisy cell metadata from every `.ipynb` file. Open each `.ipynb` as JSON and remove these keys from every cell's `metadata` object: - `execution` (timestamps added by `jupyter execute`) - `_sphinx_cell_id` (MyST/Sphinx artifact) - `vscode` (VS Code editor state) Save the cleaned JSON back to the file (preserve formatting with 1-space indent). 4. Sync all Jupytext `.md` pairs: ```bash uv run jupytext --sync notebooks/<name>.md ``` 5. Report a summary table: - Notebook name - Status (success / failure) - Execution time - Any errors or warnings ## Error handling - If a notebook fails to execute, continue with the remaining notebooks. Report the error at the end. - If `_quarto.yml` has no notebooks registered, report "No notebooks found in _quarto.yml" and stop.