by teng-lin · Claude Skill · ★ 20.2k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
pip install notebooklm-py
pip install "notebooklm-py[browser]"Taken from the project's README on GitHub. Check the security audit before running it.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 20,151 |
| Forks | 2,679 |
| Language | Python |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 74/100 |
| Open Issues | 27 |
| Last Updated | 2026-11-07 |
| Created | 2026-01-07 |
| Platforms | browser, claude-code, cli, codex, gemini, python |
| Est. Tokens | ~15k |
notebooklm-py Unofficial Python API and agentic skill for Google NotebookLM. Full programmatic access to NotebookLM's features—including capabilities the web UI doesn't expose—via Python, CLI, and AI agents like Claude Code, Codex, and OpenClaw. Source & Development: ⚠️ Unofficial Library - Use at Your Own Risk This library uses undocumented Google APIs that can change without notice.
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: