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Automatiser la recherche NotebookLM avec ancrage et l'export d'…

Permet aux agents d'exploiter Google NotebookLM/Gemini Notebook via une API Python, une CLI, un skill, un serveur MCP ou un serveur REST pour créer des notebooks, ajouter des sources, poser des questions citées, générer des artefacts et télécharger des exports.

Qu'est-ce que Automatiser la recherche NotebookLM avec ancrage et l'export d'… ?

Ce skill permet aux agents d'IA (comme Claude Code, Cursor, Codex) d'interagir directement avec Google NotebookLM (Gemini Notebook) pour effectuer des recherches ancrées et gérer des exports. Il expose les fonctionnalités clés de NotebookLM via une API Python, une interface en ligne de commande (CLI), un serveur MCP (Model Context Protocol) ou un serveur REST, facilitant l'intégration dans des workflows automatisés ou multi-agents. L'agent peut créer et configurer des notebooks, y ajouter des sources (documents, web, etc.), poser des questions avec citations, générer des artefacts (résumés, FAQ, guides) et télécharger les résultats exportés. L'installation s'effectue via `uv tool install "notebooklm-py[browser]"` ou `pipx`, suivie d'une authentification par navigateur ou token maître. Une fois configuré, le skill permet aux agents de réaliser des tâches de recherche documentaire complexes et d'en récupérer les livrables de manière structurée.

Compatible avec~Claude Code~Codex CLI~Cursor✓Gemini CLI

npx skills add https://github.com/agentskillexchange/skills/tree/main/skills/automate-grounded-notebooklm-research-and-artifact-export-with-notebooklm-py

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Automatiser la recherche NotebookLM avec ancrage et l'export d'artefacts via notebooklm-py

Permet aux agents d'exploiter Google NotebookLM/Gemini Notebook via une API Python, une CLI, un skill, un serveur MCP ou un serveur REST pour créer des notebooks, ajouter des sources, poser des questions citées, générer des artefacts et télécharger des exports.

Prérequis

CLI ou paquet Python notebooklm-py, compte Google NotebookLM/Gemini Notebook, authentification par navigateur ou par token maître, serveur MCP ou REST optionnel.

Installation

Installez ou configurez à partir des instructions basées sur la source :

Installez la CLI avec uv tool install "notebooklm-py[browser]" ou pipx install "notebooklm-py[browser]", exécutez notebooklm login, vérifiez avec notebooklm auth check --test --json, puis installez le skill agent avec notebooklm skill install ou npx skills add teng-lin/notebooklm-py.

Source : https://github.com/teng-lin/notebooklm-py

Documentation

https://github.com/teng-lin/notebooklm-py

Source

Agent Skill Exchange

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

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Add Claude design-system and accessibility workflows with UX/UI

Use UX/UI Agent Skills when Claude should generate tokens, component specs, accessibility audits, and framework-specific UI code from a repeatable design workflow.

Add executable smoke tests for shell scripts and CLIs before ref

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Add graph-backed memory and context retrieval to agent workflows

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Add multimodal lifelong memory to MCP and Python agents with Sim

Use SimpleMem to store, compress, index, and retrieve text or multimodal memories for agents through MCP or Python integrations.

Add persistent project memory and hook-driven synthesis with Cla

Keep Claude Code sessions grounded in prior decisions, project context, and daily handoff notes instead of starting from zero every time.

Add Postgres-native vector retrieval to agent and RAG workflows

Store embeddings beside application data in Postgres, create vector indexes, and query nearest neighbors for semantic search, RAG, recommendations, or agent memory retrieval.

Address GitHub PR review comments from the current branch with g

Find the open PR for the current branch, gather unresolved review comments, and drive a focused comment-resolution workflow with gh-authenticated context.

Add runtime guardrails to TypeScript agents with VoltAgent

Use VoltAgent to intercept, validate, and enforce input/output policies in TypeScript agent workflows.

Add temporal context memory to agent workflows with Zep

Use Zep as an external context layer for agents that need to store events, assemble temporal graph context, and retrieve relevant memory before model calls.

Adobe Firefly API Batch Image Generator

Calls Adobe Firefly

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