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 leanhduy-iuh/notebooklm-mcp-fork --skill datagit clone --depth 1 https://github.com/leanhduy-iuh/notebooklm-mcp-forkWrote 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/leanhduy-iuh/notebooklm-mcp-fork/data)<a href="https://agentmods.dev/skills/leanhduy-iuh/notebooklm-mcp-fork/data"><img src="https://agentmods.dev/badge/skills/leanhduy-iuh/notebooklm-mcp-fork/data/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/leanhduy-iuh/notebooklm-mcp-fork/data"><img src="https://agentmods.dev/badge/skills/leanhduy-iuh/notebooklm-mcp-fork/data.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 | $0.00146 | $0.09873 |
| Opus 5 | $0.00073 | $0.04936 |
| Sonnet 5 | $0.00029 | $0.01975 |
| Haiku 4.5 | $0.00015 | $0.00987 |
Grade A, and why
nlm-skill 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 8d 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
92% identical to nlm-skill — 311 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 — 877 lines — stays where its author put it; the contents beside it link to each section on GitHub.
NotebookLM CLI & MCP Expert
This skill provides comprehensive guidance for using NotebookLM via both the nlm CLI and MCP tools.
Tool Detection (CRITICAL - Read First!)
ALWAYS check which tools are available before proceeding:
- Check for MCP tools: Look for tools starting with
mcp__notebooklm-mcp__*ormcp_notebooklm_* - If BOTH MCP tools AND CLI are available: ASK the user which they prefer to use before proceeding
- If only MCP tools are available: Use them directly (refer to tool docstrings for parameters)
- If only CLI is available: Use
nlmCLI commands via Bash
Decision Logic:
has_mcp_tools = check_available_tools() # Look for mcp__notebooklm-mcp__* or mcp_notebooklm_*
has_cli = check_bash_available() # Can run nlm commands
if has_mcp_tools and has_cli:
# ASK USER: "I can use either MCP tools or the nlm CLI. Which do you prefer?"
user_preference = ask_user()
else if has_mcp_tools:
# Use MCP tools directly
mcp__notebooklm-mcp__notebook_list()
else:
# Use CLI via Bash
bash("nlm notebook list")
This skill documents BOTH approaches. Choose the appropriate one based on tool availability and user preference.
Quick Reference
Run nlm --ai to get comprehensive AI-optimized documentation - this provides a complete view of all CLI capabilities.
nlm --help # List all commands
nlm <command> --help # Help for specific command
nlm --ai # Full AI-optimized documentation (RECOMMENDED)
nlm --version # Check installed version
Critical Rules (Read First!)
- Authenticate when needed: Run
nlm loginfor first-time setup or confirmed stale/missing credentials. Saved cookies often remain usable for weeks. - Do not confuse network failures with expired auth:
auth_status="unverified"means the probe was inconclusive. Check connectivity or try an API call before asking the user to log in again. - ⚠️ ALWAYS ASK USER BEFORE DELETE: Before executing ANY delete command, ask the user for explicit confirmation. Deletions are irreversible. Show what will be deleted and warn about permanent data loss.
- Always obtain approval before generation or deletion: Direct
studio_createand delete operations enforce--confirm/confirm=True. The current MCP batch Studio path does not enforce its confirm parameter, so the agent must preserve the approval gate. - Research needs a destination: Pass
--notebook-id <id>for an existing notebook or--title <title>to create one. - Capture IDs from output: Create/start commands return IDs needed for subsequent operations
- Use aliases: Simplify long UUIDs with
nlm alias set <name> <uuid> - Check aliases before creating: Run
nlm alias listbefore creating a new alias to avoid conflicts with existing names. - DO NOT launch REPL: Never use
nlm chat start- it opens an interactive REPL that AI tools cannot control. Usenlm notebook queryfor one-shot Q&A instead. - Choose output format wisely: Default output (no flags) is compact and token-efficient—use it for status checks. Use
--quietto capture IDs for piping. Only use--jsonwhen you need to parse specific fields programmatically. - Use
--helpwhen unsure: Runnlm <command> --helpto see available options and flags for any command. - Studio: fast track by default: Infer format/style/prompt silently—one compact line, then
studio_create(confirm=True). No intake questionnaires. Fast track reduces clarifying questions, not the confirm gate. Cinematic video is always guided (quota-limited). Full preview only when vague, high-stakes, cinematic, or user asks. See references/studio-prompting-guide.md.
What ships with it
7 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.
- 8d ago First seen · 877 lines · 146 tokens per session scan A 5d9196c500f6
nlm-skill is a skill published in the GitHub repository leanhduy-iuh/notebooklm-mcp-fork (0 stars, last pushed 2mo ago), licensed MIT. It adds 146 tokens to every session and 9,873 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to nlm-skill, differing in 311 lines, and is treated as a copy.
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