Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Buzzmatic/awesome-agent-skills --skill notebooklmgit clone --depth 1 https://github.com/Buzzmatic/awesome-agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/buzzmatic/awesome-agent-skills/notebooklm)<a href="https://agentmods.dev/skills/buzzmatic/awesome-agent-skills/notebooklm"><img src="https://agentmods.dev/badge/skills/buzzmatic/awesome-agent-skills/notebooklm/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/buzzmatic/awesome-agent-skills/notebooklm"><img src="https://agentmods.dev/badge/skills/buzzmatic/awesome-agent-skills/notebooklm.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00099 | $0.01884 |
| Opus 5.5 | $0.00040 | $0.00754 |
| Sonnet 5.5 | $0.00020 | $0.00377 |
| Haiku 4.5 | $0.00010 | $0.00188 |
Grade A, and why
notebooklm scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 165 lines — stays where its author put it; the contents beside it link to each section on GitHub.
NotebookLM CLI
Wraps Google NotebookLM through the nlm command-line tool (notebooklm-mcp-cli package, installed via uv tool install). Talks to NotebookLM's internal API using cookies from a real browser login - no API key required.
Authentication (check first)
Sessions last ~20 minutes. Before any operation, verify:
nlm login --check
If it reports "not authenticated" or "cookies expired", the user has to run nlm login themselves in their terminal - it opens a browser for Google sign-in and extracts cookies. Tell them to type ! nlm login in the prompt (the ! runs it in the live shell so output lands here). Do not try to launch it from a sub-agent or background bash - it needs an interactive browser.
Profiles for multiple Google accounts: nlm login --profile work, then nlm login switch work to make it default. List with nlm login profile list.
Auth state and cookies live in ~/.notebooklm-mcp-cli/.
Command structure
Two equivalent forms - pick whichever reads cleaner:
nlm notebook create "My Project" # noun-first
nlm create notebook "My Project" # verb-first
--json or --quiet for machine-readable output. --confirm skips destructive-action prompts (required for any non-interactive call).
Common workflows
Ingest URLs and generate a deep-dive podcast
# `notebook create` prints "ID: <uuid>" - extract it:
NB=$(nlm notebook create "Topic XYZ" | awk '/^ ID:/ {print $2}')
nlm source add $NB --url "https://example.com/article-1" --wait
nlm source add $NB --url "https://example.com/article-2" --wait
nlm audio create $NB --format deep_dive --length long --confirm
# Poll until ready, then download (artifact ID goes via --id, NOT positional):
nlm studio status $NB
nlm download audio $NB --id <artifact-id> --output podcast.mp3
nlm download <type> <notebook> alone grabs the latest artifact of that type. Pass --id to pick a specific one.
--wait matters - sources must finish processing before any artifact generation will use them. Note: --json works on list-type commands (nlm notebook list --json) but not on create; parse stdout for the ID, or alias the notebook with nlm alias set my-nb <id> once you have it.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 165 lines · 99 tokens per session scan A 221e12380e02
notebooklm is a skill published in the GitHub repository Buzzmatic/awesome-agent-skills (1 stars, last pushed 4mo ago), licensed MIT. It adds 99 tokens to every session and 1,884 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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