Awesome-Agent-Skills-for-Empirical-Research execute

Executes all registered notebooks, strips noisy cell metadata, and syncs Jupytext pairs. Use when asked to re-run notebooks or refresh outputs.

install

source · Clone the upstream repo

git clone https://github.com/brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/29-quarcs-lab-project20XXy/dot-claude/skills/execute" ~/.claude/skills/brycewang-stanford-awesome-agent-skills-for-empirical-research-execute && rm -rf "$T"

manifest: skills/29-quarcs-lab-project20XXy/dot-claude/skills/execute/SKILL.md

source content

Execute All Notebooks

Execute all registered notebooks, strip noisy metadata, and sync Jupytext pairs.

Steps

Read
```
_quarto.yml
```
and extract all notebook paths from
```
manuscript.notebooks
```

For each notebook, execute it:

uv run jupyter execute --inplace notebooks/<name>.ipynb

Record execution time and success/failure for each notebook.

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).

Sync all Jupytext

.md

pairs:

uv run jupytext --sync notebooks/<name>.md

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.