nlm-skill

nlm-skill is a skill for Claude Code, Codex from whmathews15/notebooklm-mcp-cli. It costs 146 tokens per session (9,873 once invoked), scanned A, a copy of nlm-skill, MIT.

A guide for using NotebookLM, Google's tool for working with sources and generating documents such as reports, quizzes, and podcasts.

In plain words
What is it for?
Use it to create notebooks, add sources from places such as websites, YouTube, text, or Google Drive, and generate content.
Why use it?
It explains how to use the NotebookLM command-line tool or connected tools without guessing which interface is available.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: built for openclaw.

Good fit Use it to create notebooks, add sources from places such as websites, YouTube, text, or Google Drive, and generate content.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/whmathews15/notebooklm-mcp-cli/data
Install

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.

Any agent
npx skills add whmathews15/notebooklm-mcp-cli --skill data
Clone the repo
git clone --depth 1 https://github.com/whmathews15/notebooklm-mcp-cli

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for nlm-skill

README.md
[![agentmods](https://agentmods.dev/badge/skills/whmathews15/notebooklm-mcp-cli/data/github.svg)](https://agentmods.dev/skills/whmathews15/notebooklm-mcp-cli/data)
Your own site
<a href="https://agentmods.dev/skills/whmathews15/notebooklm-mcp-cli/data"><img src="https://agentmods.dev/badge/skills/whmathews15/notebooklm-mcp-cli/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.

agentmods 80×15 button for nlm-skill

Your own site · 80×15
<a href="https://agentmods.dev/skills/whmathews15/notebooklm-mcp-cli/data"><img src="https://agentmods.dev/badge/skills/whmathews15/notebooklm-mcp-cli/data.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 146 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 9,873 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 92% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00146 $0.09873
Opus 5.5 $0.00058 $0.03949
Sonnet 5.5 $0.00029 $0.01975
Haiku 4.5 $0.00015 $0.00987

Measured 1mo ago against content hash 5d9196c500f6, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 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.

Origin

This is a copy

92% identical to nlm-skill — 507 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.

src/notebooklm_tools/data/SKILL.md · 877 lines

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:

  1. Check for MCP tools: Look for tools starting with mcp__notebooklm-mcp__* or mcp_notebooklm_*
  2. If BOTH MCP tools AND CLI are available: ASK the user which they prefer to use before proceeding
  3. If only MCP tools are available: Use them directly (refer to tool docstrings for parameters)
  4. If only CLI is available: Use nlm CLI 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!)

  1. Authenticate when needed: Run nlm login for first-time setup or confirmed stale/missing credentials. Saved cookies often remain usable for weeks.
  2. 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.
  3. ⚠️ 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.
  4. Always obtain approval before generation or deletion: Direct studio_create and 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.
  5. Research needs a destination: Pass --notebook-id <id> for an existing notebook or --title <title> to create one.
  6. Capture IDs from output: Create/start commands return IDs needed for subsequent operations
  7. Use aliases: Simplify long UUIDs with nlm alias set <name> <uuid>
  8. Check aliases before creating: Run nlm alias list before creating a new alias to avoid conflicts with existing names.
  9. DO NOT launch REPL: Never use nlm chat start - it opens an interactive REPL that AI tools cannot control. Use nlm notebook query for one-shot Q&A instead.
  10. Choose output format wisely: Default output (no flags) is compact and token-efficient—use it for status checks. Use --quiet to capture IDs for piping. Only use --json when you need to parse specific fields programmatically.
  11. Use --help when unsure: Run nlm <command> --help to see available options and flags for any command.
  12. 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.

Read the full file on GitHub · 877 lines

Files

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.

Changes

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.

  1. 1mo ago First seen · 877 lines · 146 tokens per session scan A 5d9196c500f6

Subscribe to this mod's changes

nlm-skill is a skill published in the GitHub repository whmathews15/notebooklm-mcp-cli (1 stars, last pushed 4mo ago), licensed MIT. It adds 146 tokens to every session and 9,873 once invoked, about $0.0006 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 92% identical to nlm-skill, differing in 507 lines, and is treated as a copy.

Related

Other skills, from other repositories

hr-onboarding

A new-hire onboarding plan as a single page — first week schedule, buddy + manager intro, learning track, equipment checklist, and "you're set when…" outcomes. Use when the brief mentions "onboarding", "new hire", "first week plan", or "入职".

nexu-io/open-design · 62 tokens

book-mirror

Take any book (EPUB/PDF), produce a personalized chapter-by-chapter analysis. Each chapter is preserved in detail (The Chapter) and mirrored back to the reader's actual life (The Mirror) using brain context. The mirror observes and resonates — a friend pointing out parallels, NOT a consultant rearranging the reader's…

garrytan/gbrain · 138 tokens

exam-forecast

Analyze past exams from the same professor to surface patterns — subject weighting, recurring issue-spot traps, favored hypo types, policy-vs-doctrine mix — and forecast likely emphases for the upcoming exam. Use when the user says "what's on the exam", "analyze past exams", "predict the exam", or shares past exams.

anthropics/claude-for-legal · 73 tokens

lean-formalize

Develop and verify a mathematical proof in Lean, continue an incomplete Lean project, or audit whether it proves the original statement. Connect actual inputs to intermediate lemmas, assemble the target theorem, check its transitive axioms, and provide a reproducible handoff. Use when Lean is requested or a specific…

wanshuiyin/Auto-claude-code-research-in-sleep · 81 tokens

eli5

Explain research, papers, or technical ideas in plain English with minimal jargon, concrete analogies, and clear takeaways. Use when the user says "ELI5 this", asks for a simple explanation of a paper or research result, wants jargon removed, or asks what something technically dense actually means.

companion-inc/feynman · 63 tokens

deck-course-module

A course or workshop slide template with persistent learning goals, teaching pages, multiple-choice self-tests, and a wrap-up.

nexu-io/html-anything · 25 tokens