Agent skill

Jupyter Live Kernel

by RedWoodOG in RedWoodOG/Hermes-Desktop

Use a live Jupyter kernel for stateful, iterative Python execution via hamelnb.

Install Jupyter Live Kernel

skills CLI

$ npx skills add RedWoodOG/Hermes-Desktop --skill jupyter-live-kernel -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install RedWoodOG/Hermes-Desktop jupyter-live-kernel --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/RedWoodOG/Hermes-Desktop.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/data-science/jupyter-live-kernel .claude/skills/jupyter-live-kernel && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "jupyter-live-kernel" agent skill from https://github.com/RedWoodOG/Hermes-Desktop/tree/main/skills/data-science/jupyter-live-kernel into .claude/skills/jupyter-live-kernel/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jupyter-live-kernel", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/RedWoodOG/Hermes-Desktop/tree/main/skills/data-science/jupyter-live-kernel

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add RedWoodOG/Hermes-Desktop --skill jupyter-live-kernel -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install RedWoodOG/Hermes-Desktop jupyter-live-kernel --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/RedWoodOG/Hermes-Desktop.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/data-science/jupyter-live-kernel .agents/skills/jupyter-live-kernel && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "jupyter-live-kernel" agent skill from https://github.com/RedWoodOG/Hermes-Desktop/tree/main/skills/data-science/jupyter-live-kernel into .agents/skills/jupyter-live-kernel/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jupyter-live-kernel", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add RedWoodOG/Hermes-Desktop --skill jupyter-live-kernel -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install RedWoodOG/Hermes-Desktop jupyter-live-kernel --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/RedWoodOG/Hermes-Desktop.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/data-science/jupyter-live-kernel .cursor/skills/jupyter-live-kernel && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "jupyter-live-kernel" agent skill from https://github.com/RedWoodOG/Hermes-Desktop/tree/main/skills/data-science/jupyter-live-kernel into .cursor/skills/jupyter-live-kernel/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jupyter-live-kernel", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/RedWoodOG/Hermes-Desktop.git --path skills/data-science/jupyter-live-kernel

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add RedWoodOG/Hermes-Desktop --skill jupyter-live-kernel -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install RedWoodOG/Hermes-Desktop jupyter-live-kernel --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/RedWoodOG/Hermes-Desktop.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/data-science/jupyter-live-kernel .gemini/skills/jupyter-live-kernel && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "jupyter-live-kernel" agent skill from https://github.com/RedWoodOG/Hermes-Desktop/tree/main/skills/data-science/jupyter-live-kernel into .gemini/skills/jupyter-live-kernel/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jupyter-live-kernel", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install RedWoodOG/Hermes-Desktop jupyter-live-kernel

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add RedWoodOG/Hermes-Desktop --skill jupyter-live-kernel -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/RedWoodOG/Hermes-Desktop.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/data-science/jupyter-live-kernel .github/skills/jupyter-live-kernel && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "jupyter-live-kernel" agent skill from https://github.com/RedWoodOG/Hermes-Desktop/tree/main/skills/data-science/jupyter-live-kernel into .github/skills/jupyter-live-kernel/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jupyter-live-kernel", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add RedWoodOG/Hermes-Desktop --skill jupyter-live-kernel -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install RedWoodOG/Hermes-Desktop jupyter-live-kernel --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/RedWoodOG/Hermes-Desktop.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/data-science/jupyter-live-kernel .opencode/skills/jupyter-live-kernel && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "jupyter-live-kernel" agent skill from https://github.com/RedWoodOG/Hermes-Desktop/tree/main/skills/data-science/jupyter-live-kernel into .opencode/skills/jupyter-live-kernel/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jupyter-live-kernel", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: jupyter-live-kernel
GitHub stars: 177
Used in: 5 other repos
Token cost: ~1.4k tokens
SKILL.md length: 479 words
Files: 1
Skills in repo: 62
Repo updated: May 30, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Use a live Jupyter kernel for stateful, iterative Python execution via hamelnb.

Works in 5 steps: Discover servers and notebooks → Execute code (primary operation) → Inspect live variables → …
Tasks that involve Jupyter notebooks
SKILL.md covers When to Use This vs Other Tools, Prerequisites, Setup and Core Workflow, plus 2 more sections
Calls uv, git and curl; reaches github.com

What it does

Jupyter Live Kernel is an agent skill from RedWoodOG/Hermes-Desktop. 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.

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Data & Analytics, covering Jupyter notebooks. It works with Jupyter and Python. The licence is MIT.

When your agent uses it

Tasks that involve Jupyter notebooks

Example prompts

“/jupyter-live-kernel”

Requirements

Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

Discover servers and notebooks
Execute code (primary operation)
Inspect live variables
Edit notebook cells
Verification (restart + run all)

What it can do on your machine

Read from SKILL.md and the folder at commit be46b39. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
- uv
- git
- curl
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
- github.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Jupyter Live Kernel loads about 1.4k tokens when it runs. Until then it costs about 95 tokens; SKILL.md has 479 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~95
When it runs · the whole SKILL.md, loaded when a task matches: ~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from RedWoodOG/Hermes-Desktop at commit be46b39, republished under its MIT licence (© RedWoodOG). 479 words, ~1,390 tokens.

Download SKILL.mdSave it as .claude/skills/jupyter-live-kernel/SKILL.md (or your agent's skills folder).

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.
version: 1.0.0
author: Hermes Agent
license: MIT

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

uv must be installed (check: which uv)
JupyterLab must be installed: uv tool install jupyterlab
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:

uv run "$SCRIPT" restart-run-all --path <notebook.ipynb> --save-outputs --compact

Show full SKILL.md (204 more words)Show less

Practical Tips from Experience

First execution after server start may timeout — the kernel needs a moment to initialize. If you get a timeout, just retry.
The kernel Python is JupyterLab's Python — packages must be installed in that environment. If you need additional packages, install them into the JupyterLab tool environment first.
--compact flag saves significant tokens — always use it. JSON output can be very verbose without it.
For pure REPL use, create a scratch.ipynb and don't bother with cell editing. Just use execute repeatedly.
Argument order matters — subcommand flags like --path go BEFORE the sub-subcommand. E.g.: variables --path nb.ipynb list not variables list --path nb.ipynb.
If a session doesn't exist yet, you need to start one via the REST API (see Setup section). The tool can't execute without a live kernel session.
Errors are returned as JSON with traceback — read the ename and evalue fields to understand what went wrong.
Occasional websocket timeouts — some operations may timeout on first try, especially after a kernel restart. Retry once before escalating.

Timeout Defaults

The script has a 30-second default timeout per execution. For long-running operations, pass --timeout 120. Use generous timeouts (60+) for initial setup or heavy computation.

Files

Just SKILL.md in skills/data-science/jupyter-live-kernel of RedWoodOG/Hermes-Desktop.

Open the folder on GitHubat commit be46b39

Used in 5 other repositories

We found 6 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 5 other GitHub owners. This page covers the copy in RedWoodOG/Hermes-Desktop, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Jupyter Live Kernel next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Jupyter Live Kernel compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Jupyter Live Kernel this skillRedWoodOG/Hermes-Desktop	177	5 repos	~1.4k	Automated safety check: Pass	MIT	4 mo ago
Save Research Notebooknapjon/krisk	117	—	~702	Automated safety check: Pass	BSD-3-Clause	9 days ago
Export ML Notebookprobabl-ai/skills	138	—	~1.7k	Automated safety check: Pass	BSD-3-Clause	today
Jupyter Live Kerneltaracodlabs/aiden	852	—	~949	Automated safety check: Pass	Apache-2.0	27 days ago
Bio Reporting Quarto ReportsGPTomics/bioSkills	1.2k	1 repos	~2.4k	Automated safety check: Pass	MIT	1 mo ago
Marimobrycewang-stanford/Auto-Empirical-Research-Skills	4.6k	—	~2.8k	Automated safety check: Pass	Custom licence	5 days ago

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Questions about Jupyter Live Kernel

What does Jupyter Live Kernel do?

Use a live Jupyter kernel for stateful, iterative Python execution via hamelnb. Jupyter Live Kernel is an agent skill from RedWoodOG/Hermes-Desktop. Use a live Jupyter kernel for stateful, iterative Python execution via hamelnb.

When should I use Jupyter Live Kernel?

Jupyter Live Kernel fits situations like: tasks that involve Jupyter notebooks.

How do I install Jupyter Live Kernel in Claude Code?

Run `npx skills add RedWoodOG/Hermes-Desktop --skill jupyter-live-kernel -a claude-code`. Or copy the skill folder (skills/data-science/jupyter-live-kernel in RedWoodOG/Hermes-Desktop) into .claude/skills/jupyter-live-kernel in your project. Claude Code loads it when a task matches its description.

How do I install Jupyter Live Kernel in Codex?

Run `npx skills add RedWoodOG/Hermes-Desktop --skill jupyter-live-kernel -a codex`. Or copy the skill folder (skills/data-science/jupyter-live-kernel in RedWoodOG/Hermes-Desktop) into .agents/skills/jupyter-live-kernel in your project. Codex loads it when a task matches its description.

Can I use Jupyter Live Kernel in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add RedWoodOG/Hermes-Desktop --skill jupyter-live-kernel -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/jupyter-live-kernel, .gemini/skills/jupyter-live-kernel, .github/skills/jupyter-live-kernel and .opencode/skills/jupyter-live-kernel in your project.

What does Jupyter Live Kernel need to run?

Going by SKILL.md and its folder, Jupyter Live Kernel needs the command-line tools its instructions call (uv, git and curl). Our summary lists: Python 3.

Does Jupyter Live Kernel access the network?

SKILL.md names 1 domain. In commands or code: github.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Jupyter Live Kernel safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Jupyter Live Kernel use?

Jupyter Live Kernel is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Jupyter Live Kernel use?

About 1.4k tokens (SKILL.md is roughly 5.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Jupyter Live Kernel?

Skills that share tags, products or a category with Jupyter Live Kernel: Save Research Notebook (napjon/krisk, 117 stars), Export ML Notebook (probabl-ai/skills, 138 stars), Jupyter Live Kernel (taracodlabs/aiden, 852 stars) and Bio Reporting Quarto Reports (GPTomics/bioSkills, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Jupyter Live Kernel?

RedWoodOG (a GitHub user) maintains it in RedWoodOG/Hermes-Desktop, which has 177 GitHub stars. The repository holds 62 skills in this directory. The repository was last updated on May 30, 2026.

Source: RedWoodOG/Hermes-Desktop on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Jupyter Live Kernel

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Jupyter Live Kernel (hamelnb)

When to Use This vs Other Tools

Prerequisites

Setup

Starting JupyterLab

Creating a Notebook for REPL Use

Core Workflow

1. Discover servers and notebooks

2. Execute code (primary operation)

3. Inspect live variables

4. Edit notebook cells

5. Verification (restart + run all)

Practical Tips from Experience

Timeout Defaults

Files

Used in 5 other repositories

Compare with similar skills

Similar skills

More from RedWoodOG/Hermes-Desktop

Related

Questions about Jupyter Live Kernel