# Gemini Notebook CLI

Installs and runs notebooklm-py to manage notebooks, sources, chat, and artifacts.

- Repository: https://github.com/teng-lin/notebooklm-py (20056 stars)
- Category: AI and agents
- License: MIT
- Last updated: 2026-10-31
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add teng-lin/notebooklm-py --skill notebooklm -g -a claude-code -y`
Codex: `npx skills add teng-lin/notebooklm-py --skill notebooklm -g -a codex -y`
Cursor: `npx skills add teng-lin/notebooklm-py --skill notebooklm -g -a cursor -y`
Gemini CLI: `npx skills add teng-lin/notebooklm-py --skill notebooklm -g -a gemini-cli -y`

## Description

Install, authenticate, troubleshoot, and operate Gemini Notebook through the notebooklm-py CLI or typed async Python API. Use for notebook and source management, grounded chat and research, and artifact generation or download when the user mentions Gemini Notebook, notebooklm-py, the notebooklm CLI, or its Python API. Do not use for the generic Gemini API or unrelated content creation.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Gemini Notebook Automation

Use the `notebooklm` CLI for agent workflows. Prefer `--json` and explicit IDs so every
operation is inspectable and safe under concurrency. Use the typed async Python API only when the
user requests application code or the CLI cannot express the workflow. The readiness, identity,
authorization, and credential-handling rules below apply to both interfaces.

## Setup and Authentication

Requires Python 3.10+. Install the package in the user's existing environment; do not create a
separate environment unless requested:

```bash
pip install "notebooklm-py[browser]"
pip install "notebooklm-py[cookies]"  # optional browser-cookie extraction
```

If system `pip` reports `externally-managed-environment`, do not use `--break-system-packages`.
For CLI-only use, offer `uv tool install "notebooklm-py[browser]"` or the equivalent `pipx`
command; for application code, use the user's active project environment.

For unattended or headless work, prefer durable profile-backed master-token auth over a copied
cookie snapshot. Install `pip install "notebooklm-py[headless]"`; the one-time automatic OAuth
capture also needs `[browser]`. On a trusted workstation run
`notebooklm login --master-token --account <email>`, then deploy `master_token.json`, not
`storage_state.json`, to the selected profile. `NOTEBOOKLM_HOME` selects the private base directory
and `NOTEBOOKLM_PROFILE` selects its profile; defaults resolve to
`~/.notebooklm/profiles/default/master_token.json`.

In CI, `NOTEBOOKLM_MASTER_TOKEN_JSON` is a secret-transport convention, not an environment variable
the package reads directly. Write its exact value to the selected profile's `master_token.json`
with mode `0600`, unset it, then run `notebooklm auth refresh` to mint `storage_state.json`. A
sibling master token can automatically re-mint expired file-backed cookies. Inline
`NOTEBOOKLM_AUTH_JSON` is only a short-lived fallback; it bypasses this recovery path.

The rest: https://github.com/teng-lin/notebooklm-py/blob/HEAD//SKILL.md