clawpyter

name	clawpyter
description	Use ClawPyter for ALL Jupyter notebook, kernel, and file operations. RULE 1 — Before any cell operation, you MUST activate a notebook first. Use jupyter_create_notebook for a new notebook, or jupyter_use_notebook for an existing notebook. RULE 2 — notebook_path is the file path on the Jupyter server. RULE 3 — notebook_name is a label you choose; if unsure, use the same value as notebook_path.

ClawPyter

When to use this skill

Use ClawPyter for EVERY operation that involves Jupyter notebooks, kernels, or files on a Jupyter server. This includes: listing files, creating notebooks, reading or editing cells, and running code.

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MANDATORY PREREQUISITE: Jupyter server URL and token

Before doing ANYTHING with ClawPyter, you MUST have a valid Jupyter server URL and token.

If the user asks you to do anything Jupyter-related and you do not already have the URL and token (either from the current conversation or from a previous jupyter_connect_to_jupyter call), stop and ask the user for them immediately:

"To connect to your Jupyter server, I need the server URL and token. You can get these by running ./start-jpy.sh -n <notebook_dir> and copying the Connect to Jupyter at … line it prints."

Do not attempt any Jupyter tool call before the connection is established. Even jupyter_list_files will fail or silently hit the wrong server if the URL and token are not set.

Decision tree:

1. Do you have a URL and token from this conversation? → proceed.
2. Did you already call jupyter_connect_to_jupyter successfully in this session? → proceed.
3. Otherwise → ask the user for the URL and token before doing anything else.

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Available tools

There are 17 tools in three categories.

Category 1 — Server tools (4 tools) These tools do not require an active notebook. Use them to inspect the server.

• jupyter_list_files — list files on the server
• jupyter_list_kernels — list running kernels
• jupyter_connect_to_jupyter — switch to a different Jupyter server
• jupyter_server_info — show the current server URL and token

Category 2 — Notebook tools (6 tools + 3 compatibility wrappers = 9 tools) These tools manage notebook sessions. You must use one of these before doing any cell operations.

• jupyter_create_notebook — create a new notebook (also activates it automatically)
• jupyter_use_notebook — open and activate an existing notebook
• jupyter_list_notebooks — list all notebooks currently open in this session
• jupyter_restart_notebook — restart the kernel for an open notebook
• jupyter_restart_notebook_compat — same as above, but accepts either argument name
• jupyter_unuse_notebook — close a notebook and free its resources
• jupyter_unuse_notebook_compat — same as above, but accepts either argument name
• jupyter_read_notebook — read cell contents of an open notebook
• jupyter_read_notebook_compat — same as above, but accepts either argument name

Category 3 — Cell tools (7 tools) These tools REQUIRE an active notebook. They will fail if no notebook is activated.

• jupyter_insert_cell — add a new cell at a position
• jupyter_overwrite_cell_source — replace the content of an existing cell
• jupyter_execute_cell — run an existing cell and save its output
• jupyter_insert_execute_code_cell — add a new code cell and run it immediately
• jupyter_read_cell — read one cell's content and outputs
• jupyter_delete_cell — delete one or more cells
• jupyter_execute_code — run code directly in the kernel (output NOT saved to notebook)

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Two arguments you will use in almost every tool

notebook_path

notebook_path is the path to the notebook file on the Jupyter server, starting from the server's root folder.

Examples:

• notes.ipynb — a file in the server root folder
• projects/demo/analysis.ipynb — a file in a subfolder

Use this to identify which file you are working with.

notebook_name

notebook_name is a short label YOU choose to identify the notebook inside ClawPyter. ClawPyter uses it to track open notebooks. The Jupyter server never sees this value.

Rules for notebook_name:

• Do NOT pass an empty string. If you have no specific label in mind, set notebook_name to the same string value as notebook_path.
• Example: if notebook_path is demo.ipynb, set notebook_name to demo.ipynb as well.
• Once you assign a notebook_name, use the same value every time you refer to that notebook.

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MANDATORY RULE: You must activate a notebook before using any cell tool

Cell tools (Category 3) operate on the currently active notebook. If no notebook is active, every cell tool will return an error.

How to activate a notebook — pick ONE of the two cases below:

Case A — You are creating a new notebook: Call jupyter_create_notebook. It creates the file AND activates it automatically. Do NOT call jupyter_use_notebook afterwards. The notebook is already active.

Case B — You are opening an existing notebook: Call jupyter_use_notebook. This opens the file and activates it.

After activation, call jupyter_list_notebooks to confirm the notebook is active.

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Compatibility wrappers (_compat tools)

Three tools have a _compat version: jupyter_restart_notebook_compat, jupyter_unuse_notebook_compat, and jupyter_read_notebook_compat.

When to use the _compat version: Use it when you are unsure whether to supply notebook_name or notebook_path. The _compat version accepts either — it will use notebook_name if you provide it, and fall back to notebook_path otherwise.

When to use the regular version: Use the regular version when you already know the notebook_name from jupyter_list_notebooks. The regular version requires only notebook_name.

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Tool reference

jupyter_list_files

Lists files on the Jupyter server.

Arguments:

• path (optional, default ""): folder to start listing from. Empty string means the root folder.
• max_depth (optional, default 1, maximum 3): how many folder levels deep to look. 1 means only the top folder. 2 means the top folder and one level of subfolders.
• start_index (optional, default 0): skip this many results before returning. Use for pagination.
• limit (optional, default 25): maximum number of results to return. Set to 0 to return all results.
• pattern (optional): filename filter using wildcard characters. Example: *.ipynb returns only notebook files.

Returns a table with four columns:

• Path — full path to the file or folder
• Type — one of: "file", "directory", "notebook"
• Size — file size in B, KB, or MB. Empty for directories.
• Last_Modified — date and time in YYYY-MM-DD HH:MM:SS format

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jupyter_list_kernels

Lists all kernels currently running on the Jupyter server.

Arguments: none

Returns a table with eight columns:

• ID — unique identifier for this kernel
• Name — kernel type name (example: python3)
• Display_Name — human-readable kernel name (example: Python 3)
• Language — programming language (example: python)
• State — current state: "idle", "busy", or "unknown"
• Connections — number of clients connected to this kernel
• Last_Activity — date and time in YYYY-MM-DD HH:MM:SS format
• Environment — kernel environment variables, truncated to 100 characters

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jupyter_connect_to_jupyter

Switches ClawPyter to connect to a different Jupyter server. Use this when the server URL or token has changed, or when you need to work with a different machine.

Arguments:

• jupyter_url (required): full URL of the Jupyter server, for example http://localhost:8888
• jupyter_token (optional): authentication token for the new server
• provider (optional): a text label for the server type. This value is not used by ClawPyter — it is for your reference only.

Returns: a message confirming the new server URL.

SECURITY NOTE: The token is a credential — do not log or display it unnecessarily. However, you MUST ask the user for it if you do not already have it. Never attempt to connect without a token.

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jupyter_server_info

Returns the URL and token that ClawPyter is currently using to connect to Jupyter.

Arguments: none

Returns a JSON object with exactly two fields:

• jupyter_url — the current server URL (example: http://127.0.0.1:8888)
• jupyter_token — the current authentication token

How to build a link to a notebook for the user: Use this exact URL format:

{jupyter_url}/lab/tree/{notebook_path}?token={jupyter_token}

Example: http://127.0.0.1:8888/lab/tree/demo.ipynb?token=abc123

Note: jupyter_create_notebook already builds and returns this URL automatically. Only call jupyter_server_info if you need to build the URL yourself.

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jupyter_create_notebook

Creates a new notebook file on the server. Also starts a kernel and activates the notebook as the current notebook.

After this tool succeeds, do NOT call jupyter_use_notebook. The notebook is already active.

Arguments:

• notebook_name (optional): the filename to use for the new notebook. If you include .ipynb it is used as-is. If you do not include .ipynb, it is added automatically.

If you do not provide notebook_name, the tool uses:

1. The defaultNotebook value from the plugin configuration, if one is set.
2. Otherwise the name "Untitled".

If the chosen filename already exists, the tool adds a number suffix automatically:

• demo.ipynb exists → tries demo-1.ipynb
• demo-1.ipynb also exists → tries demo-2.ipynb
• Continues until it finds a name that does not exist.

Returns: a message with the final filename and a URL to open the notebook.

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jupyter_use_notebook

Opens an existing notebook and activates it as the current notebook. Call this before using any cell tool on an existing notebook.

Do NOT call this tool after jupyter_create_notebook. The notebook is already active.

Arguments:

• notebook_path (required): path to the notebook file on the server (example: demo.ipynb)
• notebook_name (required): the label you are assigning to this notebook in ClawPyter. If you have no specific label, use the same value as notebook_path.
• mode (optional, default "connect"):
  • "connect" — open an existing file. Use this in almost all cases.
  • "create" — create the file if it does not exist, then connect.
• kernel_id (optional): attach a specific kernel by its ID. If not provided, the server picks a kernel automatically.

Returns: a message with the activation status, the kernel ID, and a brief overview of the first 20 cells.

Special cases the tool handles automatically:

• If the notebook is already active with the same name and path, the tool returns immediately. Do not call it again.
• If mode is "create" but the notebook was already created, the tool returns immediately. Do not call it again.
• If notebook_path does not match the path stored for that notebook_name, the tool returns an error message.

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jupyter_list_notebooks

Lists all notebooks that are currently open in this ClawPyter session.

Arguments: none

Returns a table with five columns:

• Name — the notebook_name label
• Path — the notebook_path value
• Kernel_ID — the kernel attached to this notebook
• Kernel_Status — always shows "unknown" (live kernel status is not fetched by this tool)
• Activate — shows ✓ for the notebook that is currently active

Use this tool to: confirm which notebook is active, look up a notebook's kernel_id, and verify that activation succeeded.

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jupyter_restart_notebook

Restarts the kernel for a notebook. This clears all variables and state in the kernel.

Arguments:

• notebook_name (required): the label for the notebook, as shown in jupyter_list_notebooks

Returns: a message confirming the kernel was restarted.

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jupyter_restart_notebook_compat

Same function as jupyter_restart_notebook. Use this version when you are not sure whether to use notebook_name or notebook_path.

Arguments (provide at least one):

• notebook_name (optional)
• notebook_path (optional)

The tool uses notebook_name if you provide it. If notebook_name is missing or empty, it uses notebook_path instead.

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jupyter_unuse_notebook

Closes a notebook and deletes its session on the Jupyter server. The notebook file is not deleted — only the active session is ended.

Arguments:

• notebook_name (required): the label for the notebook, as shown in jupyter_list_notebooks

Returns: a message confirming the session was closed.

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jupyter_unuse_notebook_compat

Same function as jupyter_unuse_notebook. Use this version when you are not sure whether to use notebook_name or notebook_path.

Arguments (provide at least one):

• notebook_name (optional)
• notebook_path (optional)

The tool uses notebook_name if you provide it. If notebook_name is missing or empty, it uses notebook_path instead.

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jupyter_read_notebook

Reads the contents of an open notebook. The notebook must be open (activated via jupyter_use_notebook or created via jupyter_create_notebook).

Arguments:

• notebook_name (required): the label for the notebook
• response_format (optional, default "brief"):
  • "brief" — shows the first line and total line count of each cell. Use this for a quick overview.
  • "detailed" — shows the full source of each cell. Use this when you need to read the exact code.
• start_index (optional, default 0): index of the first cell to return. Cell numbering starts at 0.
• limit (optional, default 20): number of cells to return. Set to 0 to return all cells.

Returns: the total cell count, followed by the cell listing.

Recommended steps: first call with response_format: "brief" and a large limit to see the full structure. Then call with response_format: "detailed" and a small start_index + limit to read specific cells.

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jupyter_read_notebook_compat

Same function as jupyter_read_notebook. Use this version when you are not sure whether to use notebook_name or notebook_path.

Arguments (provide at least one of the first two):

• notebook_name (optional)
• notebook_path (optional)
• response_format (optional)
• start_index (optional)
• limit (optional)

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jupyter_insert_cell

Inserts a new cell into the active notebook at the position you specify. Requires an active notebook.

Arguments:

• cell_index (required, integer): position where the new cell will be inserted. Cell numbering starts at 0. Use -1 to append the cell at the end.
• cell_type (required): "code" for a code cell, or "markdown" for a text/documentation cell.
• cell_source (required): the content of the new cell.

Returns: a message confirming the insertion, and a brief listing of the cells around the new cell (up to 5 above and 5 below).

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jupyter_overwrite_cell_source

Replaces the content of an existing cell in the active notebook. Requires an active notebook. For code cells, this also clears all previous outputs and resets the execution count.

Arguments:

• cell_index (required, integer ≥ 0): 0-based index of the cell to overwrite.
• cell_source (required): the new content to write into the cell. This replaces ALL existing content in the cell.

Returns: a diff showing what was removed (- lines) and what was added (+ lines).

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jupyter_execute_cell

Runs an existing code cell and saves the outputs to the notebook file. The cell must already exist in the active notebook. Requires an active notebook.

Arguments:

• cell_index (required, integer ≥ 0): 0-based index of the cell to run.
• timeout (optional, default 90): maximum seconds to wait for the cell to finish. If the cell takes longer, execution stops and an error is returned.
• stream (optional, default false): set to true to receive progress updates while the cell is running. Useful for long-running cells.
• progress_interval (optional, default 5): when stream is true, how many seconds between progress updates.

Returns: all outputs produced by the cell (text, HTML, images).

Note: if the cell is a markdown cell (not a code cell), this tool returns an error.

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jupyter_insert_execute_code_cell

Inserts a new code cell at the position you specify, then runs it immediately. This tool does both steps in one call. Use this instead of calling jupyter_insert_cell followed by jupyter_execute_cell. Requires an active notebook.

Arguments:

• cell_index (required, integer): position where the new cell will be inserted. Use -1 to append at the end. Cell numbering starts at 0.
• cell_source (required): the code to insert and run.
• timeout (optional, default 90): maximum seconds to wait for the code to finish.

Returns: a message confirming the insertion, followed by all execution outputs.

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jupyter_read_cell

Reads the content and outputs of a single cell in the active notebook. Requires an active notebook.

Arguments:

• cell_index (required, integer ≥ 0): 0-based index of the cell to read.
• include_outputs (optional, default true): set to false to skip outputs. Outputs are only returned for code cells.

Returns: the cell's index, type, execution count, source text, and (if include_outputs is true) its outputs.

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jupyter_delete_cell

Deletes one or more cells from the active notebook. Requires an active notebook.

Arguments:

• cell_indices (required): a list of 0-based cell indices to delete. Example: [0, 2, 5].
• include_source (optional, default true): set to false to skip returning the deleted cell content.

Returns: the number of cells deleted, and (if include_source is true) the source text of each deleted cell.

IMPORTANT: You do NOT need to sort the indices. The tool automatically processes indices from largest to smallest to prevent index shifting.

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jupyter_execute_code

Runs code directly in the active kernel. The code runs, but it is NOT inserted into the notebook and outputs are NOT saved to the notebook file. Requires an active notebook.

Use this tool for:

• Running a quick check or inspection (example: print a variable value)
• Installing packages: %pip install pandas
• Timing code: %timeit my_function()
• Shell commands: !ls -la

Do NOT use this tool for:

• Code that defines variables or imports that other cells will depend on. That code will not be saved to the notebook. Use jupyter_insert_execute_code_cell instead.

Arguments:

• code (required): the code to run.
• timeout (optional, default 30, maximum 60): maximum seconds to wait. Cannot exceed 60 seconds.

Returns: all execution outputs.

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Step-by-step workflows

Workflow A: Open an existing notebook and edit a cell

1. Call jupyter_list_files to confirm the notebook file exists. Note its path.
2. Call jupyter_use_notebook with notebook_path set to that path, and notebook_name set to the same value.
3. Call jupyter_list_notebooks to confirm the notebook is now active.
4. Call jupyter_read_notebook with response_format: "brief" to see the cell structure.
5. Call jupyter_overwrite_cell_source (to replace a cell) or jupyter_insert_cell (to add a cell).
6. Call jupyter_execute_cell to run the changed cell.

Workflow B: Create a new notebook and run code

1. Call jupyter_create_notebook with the desired filename. The notebook is now active.
2. Call jupyter_insert_execute_code_cell to add code and run it in one step.

Workflow C: Switch to a different notebook

1. Call jupyter_list_notebooks to see all open notebooks and find the one you want.
2. Call jupyter_use_notebook with the target notebook_path and notebook_name. If it is already tracked, ClawPyter switches to it immediately.

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Mistakes to avoid

Mistake	What happens	Correct action
Calling any cell tool before activating a notebook	Error: "No active notebook"	Always call jupyter_use_notebook or jupyter_create_notebook first
Calling jupyter_use_notebook after jupyter_create_notebook	Tool returns "already activated" and stops	Do not call jupyter_use_notebook after jupyter_create_notebook — the notebook is already active
Passing an empty string for notebook_name	ClawPyter uses notebook_path as the name instead, which may create duplicate sessions	Always pass a non-empty value for notebook_name. When unsure, use the same value as notebook_path
Using jupyter_execute_code to set up variables for later cells	The variables exist in the kernel but are not saved in the notebook	Use jupyter_insert_execute_code_cell so the code is saved in the notebook
Passing cell indices to jupyter_delete_cell in ascending order and expecting correct results	Not a problem — the tool handles ordering automatically	Pass all indices you want to delete in a single call; order does not matter