Notebooks & cells
The notebook is the workspace. Cells are its parts, including code cells that hold both code and a plain-language description.
The notebook is where the work lives. If you know Jupyter, the basics carry over: a notebook is an ordered list of cells, code cells share a Python kernel, and output shows up underneath. Clusy notebooks are .ipynb-compatible, so you can import one and download one.
A couple of things work differently.
Cell types
Not every cell is Python. You'll run into a few kinds:
- Code cells: Python that runs in the kernel.
- Markdown cells: formatted notes, written in a rich editor with a live preview.
- Agent insight cells: short notes the agent drops in to flag something worth your attention.
- Control cells: small inputs the agent uses to ask you for a value or a choice, inline in the notebook.
- Rich display cells: sandboxed cells for richer rendered content.
Code cells have two faces
Every code cell holds two views of the same thing: a code face with the Python, and a text face with a plain-language description of what the cell does. You can read or edit either one, and switch between them with a click.
The two stay linked, and the cell shows you whether they still agree:
| Status | Meaning |
|---|---|
synced | Code and text match |
text_ahead | You changed the description, and the code hasn't caught up |
code_ahead | You changed the code, and the description hasn't caught up |
diverged | Both changed separately |
You decide how much of this you want. Auto-writing the text description is optional. It's a per-model toggle in Settings → Models, and you can set the language it's written in. Turn it off and code cells behave like ordinary code cells. The Code & text cells guide goes deeper.
The kernel
Code cells share a running kernel, so a variable from one cell is available in the next. Running cells out of order works like it does in Jupyter, with the same gotcha: the kernel remembers what you last ran, not what's written above. That's worth keeping in mind when a result looks stale.
A cell's execution status shows as a colored left border:
| Status | What it means |
|---|---|
idle | Nothing running |
queued | Waiting to run |
running | Executing now |
completed | Finished cleanly |
error | Raised an exception |
Ghost cells
When the agent proposes a cell but hasn't committed it, it shows up as a ghost: a dashed, faded cell you can accept, edit, or dismiss. Nothing the agent writes lands in your notebook before you've seen it this way.
Output
Cells render output richly: DataFrames as tables, Plotly charts inline, images, progress bars for long loops, training run cards, and readable tracebacks when something fails. Reading output covers each kind.
Working with cells
You can run, duplicate, reorder, insert, and delete cells from the cell toolbar. The notebook is virtualized, so only the cells near your view are mounted and a long notebook stays responsive.