feat(skills): add jupyter-live-kernel skill for stateful Python REPL

Adds a new data-science skill category with jupyter-live-kernel, which
uses hamelnb (https://github.com/hamelsmu/hamelnb) to give the agent
a live Jupyter kernel for stateful, iterative Python execution.

Key features:
- Variables persist across executions (unlike execute_code which is stateless)
- Inspect live variables, edit notebook cells, restart-and-run-all
- Clear trigger conditions and distinction from execute_code/terminal
- Practical tips based on hands-on testing
- No new tools required — uses terminal to run CLI commands

Prerequisites: uv, jupyterlab, hamelnb cloned to ~/.agent-skills/hamelnb

skills/data-science/DESCRIPTION.md

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+Skills for data science workflows — interactive exploration, Jupyter notebooks, data analysis, and visualization.

skills/data-science/jupyter-live-kernel/SKILL.md

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+---
+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
+tags: [jupyter, notebook, repl, data-science, exploration, iterative]
+triggers:
+  - user asks to explore data or an API interactively
+  - user wants to build code incrementally with state between steps
+  - user says "notebook", "jupyter", "REPL", "explore", "iterate"
+  - task involves data science, ML training, or complex multi-step computation
+  - user wants to inspect intermediate variables or results
+  - user says "keep state", "persistent python", "don't lose variables"
+---
+
+# 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 "$SCRIPT" edit --path <notebook.ipynb> delete --cell-id <id> --compact
+```
+
+### 5. Verification (restart + run all)
+
+Only use when the user asks for a clean verification or you need to confirm
+the notebook runs top-to-bottom:
+
+```
+uv run "$SCRIPT" restart-run-all --path <notebook.ipynb> --save-outputs --compact
+```
+
+## Practical Tips from Experience
+
+1. **First execution after server start may timeout** — the kernel needs a moment
+   to initialize. If you get a timeout, just retry.
+
+2. **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.
+
+3. **--compact flag saves significant tokens** — always use it. JSON output can
+   be very verbose without it.
+
+4. **For pure REPL use**, create a scratch.ipynb and don't bother with cell editing.
+   Just use `execute` repeatedly.
+
+5. **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`.
+
+6. **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.
+
+7. **Errors are returned as JSON** with traceback — read the `ename` and `evalue`
+   fields to understand what went wrong.
+
+8. **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.