From nteract-nightly
Uses nteract notebooks as persistent Python REPL for data exploration, analysis, plotting, and iterative computation. Replaces chained python3 -c commands or throwaway scripts with stateful cells and rich outputs.
npx claudepluginhub nteract/claude-plugin-nightly --plugin nteract-nightlyThis skill uses the workspace's default tool permissions.
When you have nteract MCP tools available and you're about to do multi-step Python work — chaining `python3 -c` commands, writing a throwaway `.py` script, or running exploratory code — use a notebook instead. You get persistent state between cells, rich output (tables, plots, errors with tracebacks), and a shareable `.ipynb` file.
Uses nteract notebooks as persistent Python REPL for data exploration, analysis, plotting, and iterative computation. Replaces chained python3 -c commands or throwaway scripts with stateful cells and rich outputs.
Creates and edits reproducible Jupyter notebooks (.ipynb) for experiments, explorations, or tutorials using templates and helper script to avoid JSON errors.
Interacts with a live local Jupyter notebook kernel for Jupyter-like in-memory REPL, notebook inspection/editing with persistent kernel, and explicit verification passes.
Share bugs, ideas, or general feedback.
When you have nteract MCP tools available and you're about to do multi-step Python work — chaining python3 -c commands, writing a throwaway .py script, or running exploratory code — use a notebook instead. You get persistent state between cells, rich output (tables, plots, errors with tracebacks), and a shareable .ipynb file.
create_notebook(path="~/analysis.ipynb")
create_cell(source="import pandas as pd\ndf = pd.read_csv('data.csv')\ndf.head()", cell_type="code", and_run=true)
Start a notebook:
create_notebook(path="~/analysis.ipynb") — creates and opens it.
Add and run code cells:
create_cell(source="your code here", cell_type="code", and_run=true) — creates the cell AND executes it in one call. State persists: variables from earlier cells are available in later ones.
Iterate on a cell:
set_cell(cell_id="...", source="updated code") then execute_cell(cell_id="...") — edit and re-run without creating a new cell.
Check your work:
get_all_cells(format="summary", include_outputs=true) — see all cells with output previews at a glance.
Save when done:
save_notebook() — writes the .ipynb to disk.
python3 -c commandspython3 -c "print(2+2)" is fine as-is)python3 script.py)