Skip to main content

notebooklm

Use for querying Google NotebookLM notebooks from Codex via local browser automation. Trigger when the user mentions NotebookLM, shares a NotebookLM URL, wants source-grounded answers from uploaded docs, or needs to add, list, search, activate, or remove notebooks from a local NotebookLM library.

来源信息

仓库
alffei/skill_share
最近来源活动
2026年3月17日 13:05
检测到的 SKILL.md 语言
英语
星标
69
Forks
18

安装方式

默认使用会先检查来源的 Prompt;你也可以切换为直接命令,或下载本地副本。

检查来源文件

决定是否安装前,请先阅读 SKILL.md,以及 SkillsMP 当前展示的配套文件。

文件资源管理器
18 个文件

正在显示 SKILL.md

SKILL.md
来源说明 · 只读预览
name
notebooklm
description
Use for querying Google NotebookLM notebooks from Codex via local browser automation. Trigger when the user mentions NotebookLM, shares a NotebookLM URL, wants source-grounded answers from uploaded docs, or needs to add, list, search, activate, or remove notebooks from a local NotebookLM library.
# NotebookLM Use this skill to let Codex query Google NotebookLM and return answers grounded in the user's uploaded documents. This skill is for local Codex environments that can: - run shell commands - install Python dependencies - access the network - open a visible browser window for Google login ## Use bundled scripts as black boxes Always use the wrapper: ```bash python scripts/run.py <script> [args...] ``` Do not call scripts in `scripts/` directly unless you are debugging the skill itself. The wrapper creates `.venv`, installs dependencies, and runs the script with the correct interpreter. If the first setup is interrupted, rerun the same wrapper command. The wrapper now repairs incomplete `.venv` directories automatically. ## When to use Trigger this skill when the user: - mentions NotebookLM - shares a NotebookLM URL - asks to query their docs through NotebookLM - wants to save or manage NotebookLM notebooks locally - asks for answers grounded only in uploaded notebook sources ## Core workflow ### 1. Check authentication first ```bash python scripts/run.py auth_manager.py status ``` If authentication is missing or stale, run setup. ### 2. Authenticate with Google ```bash python scripts/run.py auth_manager.py setup ``` Important: - the browser must be visible for login - tell the user a browser window will open - wait for them to complete Google login manually ### 3. Resolve the notebook List saved notebooks: ```bash python scripts/run.py notebook_manager.py list ``` If the user provided a notebook URL that is not in the library yet, prefer Smart Add: ```bash python scripts/run.py ask_question.py \ --question "What is the content of this notebook? What topics are covered? Provide a brief overview." \ --notebook-url "[URL]" python scripts/run.py notebook_manager.py add \ --url "[URL]" \ --name "[Specific notebook name]" \ --description "[Specific description based on notebook content]" \ --topics "[topic1,topic2,topic3]" ``` Do not invent generic metadata if the notebook content is still unknown. ### 4. Ask the notebook Use one of: ```bash python scripts/run.py ask_question.py --question "Your question here" python scripts/run.py ask_question.py --question "..." --notebook-id notebook-id python scripts/run.py ask_question.py --question "..." --notebook-url "https://notebooklm.google.com/notebook/..." ``` Add `--show-browser` only when debugging UI failures. ## Follow-up rule `ask_question.py` appends a follow-up reminder to every answer. Treat that as an internal prompt to keep researching before answering the user. Before you respond: 1. Compare the NotebookLM answer to the user's actual request. 2. Identify missing details, edge cases, or implementation gaps. 3. Ask one or more follow-up questions if the first answer is incomplete. 4. Synthesize the final response only after the information is sufficient. Each NotebookLM query is stateless, so follow-up questions must include the needed context. ## Command reference Read [commands.md](./references/commands.md) when you need the exact CLI for: - authentication - library management - notebook queries - cleanup ## Troubleshooting Read [troubleshooting-codex.md](./references/troubleshooting-codex.md) when: - login fails - the browser does not launch - selectors break after a NotebookLM UI change - Patchright or Chrome installation fails ## Operational notes - Skill data is stored under the skill directory in `data/`. - First use creates `.venv` in the skill directory. - Environment setup installs Python dependencies and Patchright's Chrome runtime. - Dependency installation streams pip output so DNS or mirror failures are visible instead of appearing stuck. - `NOTEBOOKLM_PIP_INDEX_URL` can be used to point pip at a reachable package mirror. - Authentication uses a persistent browser profile plus saved storage state. - Free Google accounts may hit NotebookLM rate limits. ## Limits - Each query opens a fresh browser session. - The user must already have a NotebookLM notebook with uploaded sources. - Browser automation may break if NotebookLM changes its UI.
在 GitHub 查看