pleaseprompto/notebooklm-skill

Use this skill to enable Claude Code to communicate directly with your Google NotebookLM notebooks. Query your uploaded documents and get source-grounded,...

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Summary Information

Updated 19 minutes ago
Added to GitGenius on September 1st, 2026
Created on October 19th, 2025
Open Issues & Pull Requests: 40 (+0)
GitHub issues: Enabled
Number of forks: 878
Total Stargazers: 7,759 (+0)
Total Subscribers: 32 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 9.1 hours
Mean response time: 18.3 days
90th percentile: 123.8 days
Tracked items: 7

How this project is maintained

Around half of the issues opened in the past year never receive a reply. Only 10% of issues opened in the past year have been closed.

Charts & Analytics

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Issue Activity (beta)

Open issues: 12
New in 7 days: 1
Closed in 7 days: 0
Avg open age: 125 days
Stale 30+ days: 9
Stale 90+ days: 6

Recent activity

Opened in 7 days: 1
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

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Most active issues this week

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Detailed Description

NotebookLM Claude Code Skill is a Claude Code extension that enables direct integration with Google NotebookLM notebooks for querying documents and retrieving source-grounded answers.

The tool solves the problem of inefficient document retrieval when working with Claude Code. Without it, developers face massive token consumption from repeatedly reading files, inaccurate keyword-based searches that miss context, hallucinations when information cannot be found, and the friction of manually copying content between NotebookLM and their editor. The skill works by automating browser interaction with NotebookLM, which uses Gemini to synthesize answers exclusively from uploaded documents. Claude Code can now ask questions directly and receive citation-backed responses without the overhead of local retrieval-augmented generation or the unreliability of web search.

Developers should adopt this skill if they maintain a knowledge base in NotebookLM and want Claude Code to reference it during development work. It suits projects where reducing hallucinations and token consumption matter more than instant setup, and where documents are already organized in NotebookLM. The README compares it to feeding documents directly to Claude, web search, and local RAG systems, positioning it as superior in hallucination reduction and answer quality while requiring minimal setup time and token cost. However, the skill requires local Claude Code installation with network access; it does not work in the web UI due to sandbox restrictions.

Development activity shows consistent maintenance with regular updates addressing user needs and bug fixes. The project maintains active engagement with the community through issue responses and feature refinements. Documentation is thorough and regularly updated to reflect current capabilities and limitations. The maintainers provide clear guidance on setup and troubleshooting, indicating ongoing attention to the user experience.