skills.rest
kaminocorp
kaminocorpOFFICIAL
Explore all skills by this author →
Website𝕏@kaminocorpoGitHub

jupyter-live-kernel

Execute stateful Python code against a live Jupyter kernel via hamelnb CLI.

1|Updated Mar 12, 2026
Search Tags:#python#data science#repl#exploration#kernel#jupyter#notebook
One-click install
npx skills add https://github.com/kaminocorp/hermes-alpha-hunter --skill jupyter-live-kernel-kaminocorp
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: jupyter-live-kernel
Source: https://github.com/kaminocorp/hermes-alpha-hunter/tree/main/skills/data-science/jupyter-live-kernel
Command: npx skills add https://github.com/kaminocorp/hermes-alpha-hunter --skill jupyter-live-kernel-kaminocorp

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires jupyterlab, uv, and includes scripts (resource) components.

What problem does it solve? One-shot code execution loses all state between runs, forcing you to re-import libraries, reload data, and rebuild variables on every step. This Skill provides a persistent Python REPL backed by a live Jupyter kernel, so variables, imports, and objects survive across executions for iterative exploration. ## Core Features & Use Cases - Stateful Code Execution: Run Python code against a live Jupyter kernel where variables, imports, and DataFrames persist across calls. - Live Variable Inspection: List and preview variables currently held in the kernel to inspect intermediate results without re-running code. - Notebook Cell Editing: View, insert, replace, and delete notebook cells, plus restart-and-run-all verification for top-to-bottom reproducibility. - Use Case: During a data science task, load a CSV into a pandas DataFrame once, then iteratively filter, transform, and plot it across multiple executions while inspecting intermediate DataFrames at each step. ## Quick Start Start a JupyterLab server and use the jupyter-live-kernel skill to run Python code in a persistent kernel so I can explore this dataset step by step.

Frequently Asked Questions about jupyter-live-kernel

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run stateful Python code in a Jupyter kernel from the terminal?▼

Use the hamelnb script's execute command with a notebook path and code string, for example: uv run "$SCRIPT" execute --path scratch.ipynb --code '<python code>' --compact. State persists across calls, so variables and imports survive between executions.

When should I use a live Jupyter kernel instead of one-shot code execution?▼

Use a live kernel when you need iterative exploration, state across steps, or inspection of intermediate results like DataFrames. One-shot execution is better for single self-contained scripts that do not need persistent variables.

What are the prerequisites for running a live Jupyter kernel?▼

You need uv installed, JupyterLab installed via uv tool install jupyterlab, and a running Jupyter server. You also must create a kernel session through the Jupyter REST API before executing code.

Why does the first Jupyter kernel execution time out?▼

The kernel needs time to initialize after the server starts, so the first execution may hit the 30-second default timeout. Retry the command, or pass a longer timeout such as --timeout 120 for heavy computation.

How do I inspect variables in a running Jupyter kernel?▼

Use the variables subcommand: uv run "$SCRIPT" variables --path notebook.ipynb list --compact to list variables, or add preview --name <varname> to inspect a specific one. Note that --path goes before the list or preview sub-subcommand.

Related Skills

Explore More Data & Analytics Skills→
zengbaochengzengbaocheng

jupyter-live-kernel

Start a stateful Jupyter kernel session for iterative Python exploration.

Community
Advanced
nimrodfishernimrodfisher
351

insight-synthesis

Summarize analysis findings into decision-oriented insights for executive stakeholders.

Community
Advanced
rose4320rose4320

notebook-guidance

Guide Jupyter notebook workflows for BigQuery data analysis and visualization.

Community
Advanced
automatedigitalautomatedigital
1

jupyter-live-kernel

Execute iterative Python code against a live Jupyter kernel with persistent variables.

Official
Intermediate