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 eric861129/SKILLS_All-in-one --skill notebooklmgit clone --depth 1 https://github.com/eric861129/SKILLS_All-in-oneWrote 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/eric861129/skills_all-in-one/notebooklm)<a href="https://agentmods.dev/skills/eric861129/skills_all-in-one/notebooklm"><img src="https://agentmods.dev/badge/skills/eric861129/skills_all-in-one/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/eric861129/skills_all-in-one/notebooklm"><img src="https://agentmods.dev/badge/skills/eric861129/skills_all-in-one/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 | $0.00069 | $0.00620 |
| Opus 5 | $0.00034 | $0.00310 |
| Sonnet 5 | $0.00014 | $0.00124 |
| Haiku 4.5 | $0.00007 | $0.00062 |
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 7d 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.
This is a copy
100% identical to notebooklm — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
NotebookLM Skill
Query NotebookLM notebooks and manage notebooks/sources via Playwright browser automation.
All commands run from the skill directory. All scripts output JSON to stdout and exit 1 on error. Use --help on any script for full flag reference.
Workflow
- Authenticate:
python scripts/auth_manager.py setup --profile <name> - Register notebook:
python scripts/notebook_manager.py add --url <url> --name <name> --description <desc> --topics <topics> - Ask questions:
python scripts/ask_question.py --question "..." --notebook-id <id> - Manage sources:
python scripts/remote_manager.py add-source|sync-sources ...
Key Behaviors
- Runs headless by default; use
--show-browserfor debugging only. - Persistent Chrome profiles stored at
~/.config/claude/notebooklm-skill/(override withNOTEBOOKLM_DATA_DIR). - Hash-based dedupe: file uploads skip unchanged sources automatically.
--dry-runavailable on all destructive/bulk operations (create, add-source, delete-source, sync-sources).--retries Nretries transient browser failures with screenshot/HTML artifact capture.- Batch mode (
--questions "q1||q2||q3") and multi-notebook comparison (--compare-notebook-ids) supported. - Exports to JSON or Markdown via
--export-format markdown --save-notes. - Answers include a follow-up reminder prompting Claude to ask clarifying questions before replying.
Quick Reference
# Auth
python scripts/auth_manager.py setup --profile work
python scripts/auth_manager.py status --profile work
# Library
python scripts/notebook_manager.py add --url "..." --name "..." --description "..." --topics "..."
python scripts/notebook_manager.py list
# Ask
python scripts/ask_question.py --question "..." --notebook-id <id>
python scripts/ask_question.py --questions "q1||q2" --notebook-id <id>
# Sources
python scripts/remote_manager.py add-source --notebook-id <id> --dir ./docs --recursive
python scripts/remote_manager.py sync-sources --notebook-id <id> --dir ./docs --recursive --delete-missing --dry-run
What ships with it
12 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.
- .gitignore 34 B
- references/commands.md 4.1 KB
- requirements.txt 19 B
- scripts/ask_question.py 27 KB runs code
- scripts/auth_manager.py 7.9 KB runs code
- scripts/common.py 8.1 KB runs code
- scripts/notebook_manager.py 7.3 KB runs code
- scripts/remote_manager.py 55 KB runs code
- tests/conftest.py 148 B runs code
- tests/test_ask_question_modes.py 2.0 KB runs code
- tests/test_remote_manager_filters.py 2.5 KB runs code
- tests/test_smoke_playwright.py 2.8 KB runs code
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.
- 7d ago First seen · 55 lines · 69 tokens per session scan A 849c83056639
notebooklm is a skill published in the GitHub repository eric861129/SKILLS_All-in-one (52 stars, last pushed 4mo ago), licensed MIT. It adds 69 tokens to every session and 620 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to notebooklm, differing in 0 lines, and is treated as a copy.
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