| name | notebooklm-research |
| description | Research a topic with NotebookLM — create notebook, run deep research, auto-import sources, and summarize. Checks notebooklm installation, login, and skill installation first. |
NotebookLM Research Workflow
Research a topic using NotebookLM: create a notebook, run deep web research with auto-import sources, and summarize.
Core Principle: Non-Blocking
Never use notebooklm research wait, notebooklm source wait, or notebooklm artifact wait in main conversation. These commands block for minutes. Instead:
- Launch the operation (e.g.,
--no-wait flag)
- Immediately return to the user — tell them what's running and how long it'll take
- The user will check back later and re-invoke if needed
Workflow Steps
When this skill is invoked, follow these steps in order:
Prerequisites: Check Environment
Before starting, verify prerequisites:
-
Check NotebookLM Installation
notebooklm --version 2>/dev/null || pip3 show notebooklm-py 2>/dev/null
If not installed:
pip install notebooklm-py
notebooklm skill install
-
Check Login Status
notebooklm status 2>&1
If authentication fails or session expired:
notebooklm auth check 2>&1
If not logged in, tell the user to run notebooklm login first and stop.
-
Check NotebookLM Skill Installation
ls ~/.claude/skills/notebooklm/SKILL.md 2>/dev/null && echo "Skill installed"
If not installed:
notebooklm skill install
Step 1: Create Notebook & Start Research
-
If no topic is provided, ask the user: "What research topic would you like to explore?"
-
Create a new notebook with the research topic as title:
notebooklm create "<research-title>" --json
Parse the notebook ID from the JSON output.
-
Set the notebook as current context:
notebooklm use <notebook-id>
-
Start deep web research (non-blocking):
notebooklm source add-research "<research-query>" --mode deep --no-wait
-
Immediately return to the user with:
- Notebook title and ID
- Research has started in background (deep mode takes ~3-5 minutes)
- Tell the user to wait and then come back to check progress and import sources
- The user can later run
notebooklm research status -n <notebook-id> to check
Step 2: Check Research Status (User Returns)
When the user comes back to check:
-
Check research status:
notebooklm research status -n <notebook-id>
-
If research is still in progress → tell the user it's still running, wait a bit more.
-
If research is complete → show the found sources and ask the user whether to proceed with importing.
Step 3: Import Sources (User Confirms)
-
Do NOT run research wait --import-all in main conversation. Instead:
- Tell the user this step takes a few minutes
- Suggest running:
notebooklm research wait --import-all -n <notebook-id> and waiting for it to complete
- The user can come back after running it
-
Alternatively, check if sources are already imported:
notebooklm source list -n <notebook-id>
If sources are already there and ready → proceed to Step 5.
Step 4: Wait for Source Processing (User-Initiated)
- Tell the user that after importing, sources need ~1-2 minutes to process
- User can check with:
notebooklm source list -n <notebook-id> (look for "ready" status)
- Come back when all key sources show "ready"
Step 5: Show General Description
Ask NotebookLM to generate a general description/summary of the notebook content:
notebooklm ask "Summarize the core content and key findings of this notebook in Chinese" -n <notebook-id>
Present the generated summary to the user.
Example
User: /notebooklm-research Russian space program 2026
Agent:
- ✅ Checks notebooklm installed (v0.4.1)
- ✅ Verifies login status (authenticated)
- ✅ Confirms skill installed
- ✅ Creates notebook "Russian space program 2026", starts deep research
- ✅ Returns immediately — tells user "Research started (~5 min), come back later to check"
- 🔄 User returns → agent checks status → shows found sources → asks user to import
- 🔄 User imports → comes back → agent verifies and generates summary
