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notebooklm-management

notebooklm-management is a skill for Codex from PracticalSwan/agent-skills. It costs 38 tokens per session (1,253 once invoked), scanned A, original, MIT.

A guide to writing serverless functions for Netlify in TypeScript, JavaScript, or Go. A serverless function is backend code that runs on demand without managing a dedicated server.

In plain words
What is it for?
Use it for API endpoints, form handlers, login hooks, streamed or AI-proxy responses, scheduled jobs, and long-running background work.
Why use it?
It provides the file locations and request-handling patterns needed to add backend behavior to a Netlify site without setting up a separate server.

Skill for Codex

Written for Codex: reads $CODEX_HOME. Also seen: mentions subagents; mentions Claude Code; mentions Codex.

not rated 22repo +1 changed 1mo ago A scan 38 tokens original MIT

Good fit Use it for API endpoints, form handlers, login hooks, streamed or AI-proxy responses, scheduled jobs, and long-running background work.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/practicalswan/agent-skills/notebooklm-management
View source ↗ PracticalSwan/agent-skills
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 PracticalSwan/agent-skills --skill notebooklm-management
Clone the repo
git clone --depth 1 https://github.com/PracticalSwan/agent-skills

Made for: 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 notebooklm-management

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/practicalswan/agent-skills/notebooklm-management"><img src="https://agentmods.dev/badge/skills/practicalswan/agent-skills/notebooklm-management.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 38 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,253 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 original No closer match found 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 $0.00038 $0.01253
Opus 5.5 $0.00015 $0.00501
Sonnet 5.5 $0.00008 $0.00251
Haiku 4.5 $0.00004 $0.00125

Measured 1mo ago against content hash 2e21fba8082b, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

notebooklm-management 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.

The scan reads SKILL.md. This mod also ships 6 executable files (examples/add-notebook.py, examples/adhoc-query.py, examples/library-management.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

notebooklm-management/SKILL.md · 123 lines

How it starts

The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.

NotebookLM MCP Management

Tech Stack Target / Version: NotebookLM current web release, Markdown session capture, and URL-tracked research workflows.

Use this skill when research should be grounded in NotebookLM notebooks instead of a generic web search.

  • Leverage native parallel subagent dispatch and 200k+ context windows where available.

Current MCP Reality

This repository already targets a real NotebookLM MCP workflow. The concrete tool surface available in this environment includes:

  • get_health
  • list_notebooks, search_notebooks, select_notebook
  • ask_question
  • add_notebook, update_notebook, remove_notebook
  • list_sessions, reset_session, close_session
  • setup_auth, re_auth, cleanup_data

Activation Conditions

Use symptom -> action triggers: when one matches, apply this skill and verify with the protocol below.

  • Querying a specific NotebookLM notebook
  • Adding a notebook from a share URL
  • Managing a notebook library or switching active notebooks
  • Recovering authentication or cleaning NotebookLM state
  • Continuing a multi-turn research session
  1. Call get_health first to confirm authentication and server readiness.
  2. Reuse an existing session when the task is the same.
  3. Prefer search_notebooks or list_notebooks before asking the user to restate what is already in the library.
  4. Use ask_question iteratively in the same session for deep work.
  5. Use setup_auth or re_auth only when health indicates auth problems.

Library Management Rules

  • Do not add or remove notebooks without explicit user confirmation.
  • When adding a notebook, collect URL, description, topics, and use cases first.
  • Update metadata instead of creating duplicates when the notebook already exists.

Troubleshooting

  • Auth broken: get_health -> re_auth
  • Stale browser state: cleanup_data(preserve_library=true) after closing browsers
  • Wrong context: reset_session or switch notebooks
  • Ambiguous notebook choice: search the library before creating a new one

Read the full file on GitHub · 123 lines

Files

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.

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 Changed · +1 lines 2e21fba8082b
  2. 1mo ago Changed b6662ce5adb0
  3. 1mo ago First seen · 122 lines · 38 tokens per session scan A 2dde2f285876

Subscribe to this mod's changes

notebooklm-management is a skill published in the GitHub repository PracticalSwan/agent-skills (22 stars, last pushed 8d ago), licensed MIT. It adds 38 tokens to every session and 1,253 once invoked, about $0.0002 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 2026-09-03.

Backend and APIsCloudDevOps and cloudDocumentsProductivityResearchautomationmanagement
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