jupyter-live-kernel
Use a live Jupyter kernel for stateful, iterative Python execution via hamelnb.
Skill by Tommy-yw
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
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About
Use cases: backend, data, ml, productivity
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 26, 2026.
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/jupyter-live-kernel
What's inside
- Skill name
jupyter-live-kernel- Description
- Use a live Jupyter kernel for stateful, iterative Python execution via hamelnb. Load this skill when the task involves exploration, iteration, or inspecting intermediate results — data science, ML experimentation, API exploration, or building up complex code step-by-step. Uses terminal to run CLI commands against a live Jupyter kernel. No new tools required.
- License
- MIT
- Instructions
- 156 lines in SKILL.md · view on GitHub
Before installing
- Instructions call the network
Files (1)
- SKILL.md
SKILL.md (first lines)
# Jupyter Live Kernel (hamelnb)
Gives you a **stateful Python REPL** via a live Jupyter kernel. Variables persist
across executions. Use this instead of `execute_code` when you need to build up
state incrementally, explore APIs, inspect DataFrames, or iterate on complex code.
## When to Use This vs Other Tools
| Tool | Use When |
|------|----------|
| **This skill** | Iterative exploration, state across steps, data science, ML, "let me try this and check" |
| `execute_code` | One-shot scripts needing hermes tool access (web_search, file ops). Stateless. |
| `terminal` | Shell commands, builds, installs, git, process management |
**Rule of thumb:** If you'd want a Jupyter notebook for the task, use this skill.
## Prerequisites
1. **uv** must be installed (check: `which uv`)
2. **JupyterLab** must be installed: `uv tool install jupyterlab`
3. A Jupyter server must be running (see Setup below)
## Setup
The hamelnb script location:
```
SCRIPT="$HOME/.agent-skills/hamelnb/skills/jupyter-live-kernel/scripts/jupyter_live_kernel.py"
```
If not cloned yet:
```
git clone https://github.com/hamelsmu/hamelnb.git ~/.agent-skills/hamelnb
```
### Starting JupyterLab
Check if a server is already running:
```
uv run "$SCRIPT" servers
```
If no servers found, start one:
```
jupyter-lab --no-browser --port=8888 --notebook-dir=$HOME/notebooks \
--IdentityProvider.token='' --ServerApp.password='' > /tmp/jupyter.log 2>&1 &
sleep 3
```
Note: Token/password disabled for local agent access. The server runs headless.
### Creating a Notebook for REPL Use
If you just need a REPL (no existing notebook), create a minimal notebook file:
```
mkdir -p ~/notebooks
```
Write a minimal .ipynb JSON file with one empty code cell, then start a kernel
session via the Jupyter REST API:
```
curl -s -X POST http://127.0.0.1:8888/api/sessions \
-H "Content-Type: application/json" \
-d '{"path":"scratch.ipynb","type":"notebook","name":"scratch.ipynb","kernel":{"name":"python3"}}'
```
## Core Workflow
All commands return structured JSON. Always use `--compact` to save tokens.
### 1. Discover servers and notebooks
```
uv run "$SCRIPT" servers --compact
uv run "$SCRIPT" notebooks --compact
```
### 2. Execute code (primary operation)
```
uv run "$SCRIPT" execute --path <notebook.ipynb> --code '<python code>' --compact
```
State persists across execute calls. Variables, imports, objects all survive.
Multi-line code works with $'...' quoting:
```
uv run "$SCRIPT" execute --path scratch.ipynb --code $'import os\nfiles = os.listdir(".")\nprint(f"Found {len(files)} files")' --compact
```
### 3. Inspect live variables
```
uv run "$SCRIPT" variables --path <notebook.ipynb> list --compact
uv run "$SCRIPT" variables --path <notebook.ipynb> preview --name <varname> --compact
```
### 4. Edit notebook cells
```
# View current cells
uv run "$SCRIPT" contents --path <notebook.ipynb> --compact
# Insert a new cell
uv run "$SCRIPT" edit --path <notebook.ipynb> insert \
--at-index <N> --cell-type code --source '<code>' --compact
# Replace cell source (use cell-id from contents output)
uv run "$SCRIPT" edit --path <notebook.ipynb> replace-source \
--cell-id <id> --source '<new code>' --compact
# Delete a cell
uv run "$SCRIPT" edit --path <notebook.ipynb> delete --cell-id <id> --compact
```
### 5. Verification (restart + run all)
Only use when the user asks for a clean verification or you need to confirm
the notebook runs top-to-bottom:
```From Tommy-yw/RunbookHermes, MIT.
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Compare and alternatives
Featured in
Signals
- Stars
- 510
- Forks
- 36
- Open issues
- 2
- Last commit (this folder)
- May 1, 2026 (5 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/Tommy-yw/RunbookHermes
- Website
- kheish.ai
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
jupyter-live-kernel skill. Agent Mart. https://agentmart.dev/skills/tommy-yw-jupyter-live-kernel (last updated 2026-10-24)