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From nightly
Uses nteract notebooks as a persistent Python REPL for data exploration, analysis, plotting, and iterative computation. Replaces throwaway python3 -c commands and .py scripts with stateful notebook cells.
npx claudepluginhub nteract/nteractHow this skill is triggered — by the user, by Claude, or both
Slash command
/nightly:replThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
When nteract notebook tools are 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-backed REPL instead. You get persistent state between cells, rich output (tables, plots, errors with tracebacks), and users and agents can view the notebook in realtime.
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 nteract notebook tools are 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-backed REPL instead. You get persistent state between cells, rich output (tables, plots, errors with tracebacks), and users and agents can view the notebook in realtime.
Prefer the direct pi tools when present:
python — execute code in the persistent notebook session.python_add_dependencies — batch-add packages and hot-sync the environment.python_save_notebook — save the backing notebook.If only MCP tools are available, use create_notebook, create_cell, execute_cell, set_cell, and get_all_cells.
If you loaded this skill but neither the direct pi tools (python, python_add_dependencies) nor the MCP notebook tools are available, don't fall back to python3 -c. Ask the user to verify that the nteract plugin is installed and enabled in Codex, then restart Codex after any plugin or marketplace changes. The most common cause is that the plugin was installed or updated after the current Codex session started.
If tools still don't appear after restarting Codex:
runt doctor to check the installation. (runt-nightly if this is the nightly release)python({
"code": "import numpy as np\nnp.arange(3)",
"dependencies": ["numpy"]
})
Pass dependencies on the first python call when imports may be missing. The pi REPL records them before kernel startup when possible; later dependency additions use hot-sync.
create_notebook(dependencies=["numpy"])
create_cell(source="import numpy as np\nnp.arange(3)", cell_type="code", and_run=true)
Start or reuse a notebook-backed REPL:
python(...); the session is created lazily and state persists.create_notebook(...) or connect_notebook(...).Declare dependencies before import-heavy code:
dependencies to python or call python_add_dependencies.dependencies to create_notebook or use manage_dependencies.Run and iterate:
python repeatedly; variables/imports persist.set_cell(...) and rerun with execute_cell(...).Check your work:
get_all_cells(format="summary", include_outputs=true).Save when done:
python_save_notebook(...) or save_notebook(...).
Open the app for the user:
show_notebook() when they ask to see it. This can be disruptive if unexpected.
python3 -c commandspython3 -c "print(2+2)" is fine as-is)python3 script.py)