/notebooklm-skill
Automate source-grounded research with Google NotebookLM. Create notebooks from URLs, text, or local files; ask cited questions; run fast or deep web research; create articles and social drafts; and generate or download audio, video, cinematic video, slides, reports, study
$ npx -y skills add claude-world/notebooklm-skill --skill notebooklm-skill --agent claude-codeHow it fires
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- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/notebooklm-skill
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Automate source-grounded research with Google NotebookLM. Create notebooks from URLs, text, or local files; ask cited questions; run fast or deep web research; create articles and social drafts; and generate or download audio, video, cinematic video, slides, reports, study
SKILL.md
notebooklm-skill.SKILL.mdname: notebooklm-research
description: >
Automate source-grounded research with Google NotebookLM. Create notebooks from
URLs, text, or local files; ask cited questions; run fast or deep web research;
create articles and social drafts; and generate or download audio, video,
cinematic video, slides, reports, study guides, quizzes, flashcards, mind maps,
infographics, and data tables. Use when a user asks for NotebookLM, cited source
analysis, research-to-content workflows, podcasts, slides, study material,
artifact generation, RSS digests, or trend research.
NotebookLM Research
Use the installed commands or the 13 MCP tools to turn user-provided sources into grounded answers and NotebookLM artifacts. Commands emit JSON on stdout and progress or diagnostics on stderr, so preserve stdout when another tool will consume it.
This integration uses NotebookLM's browser session and unofficial web API through `notebooklm-py`. Do not promise that Google-side availability, quotas, or generation time are stable.
Authentication
Prefer the profile-aware helper:
notebooklm-auth setup
notebooklm-auth verify
Use `notebooklm-auth setup --browser chrome --fresh` when the user explicitly wants the locally installed Google Chrome instead of bundled Chromium.
For a zero-install login:
uvx --from notebooklm-py notebooklm login
Profiles are supported through `--profile NAME` before the subcommand or through `NOTEBOOKLM_PROFILE`. Current sessions are normally stored below `~/.notebooklm/profiles/<profile>/storage_state.json`; never read, print, copy, or commit that file. If authentication expires, run setup again.
Core CLI
Create a notebook from mixed sources:
notebooklm-skill create \
--title "AI safety evidence" \
--sources https://example.com/article https://youtu.be/example \
--files ./paper.pdf \
--text-sources "A user-supplied observation" \
--strict
Inspect and ask:
notebooklm-skill list
notebooklm-skill list-sources --notebook "AI safety evidence"
notebooklm-skill summarize --notebook "AI safety evidence"
notebooklm-skill ask --notebook "AI safety evidence" --query "What findings conflict?"
Add exactly one source:
notebooklm-skill add-source --notebook "AI safety evidence" --url https://example.com/new
notebooklm-skill add-source --notebook "AI safety evidence" --file ./appendix.docx
notebooklm-skill add-source --notebook "AI safety evidence" \
--text "Raw notes" --text-title "Interview notes"
Run NotebookLM web research and import results:
notebooklm-skill research \
--notebook "AI safety evidence" \
--query "Recent empirical evaluations" \
--mode deep --max-sources 10
Use `--no-wait` for a task ID without waiting. Use `--no-import-results` when the research results should not become notebook sources.
Notebook titles may be used only when they resolve uniquely. Prefer IDs in automation.
Artifact generation
Supported canonical types:
`audio`, `video`, `cinematic`, `slides`, `report`, `study-guide`, `quiz`, `flashcards`, `mind-map`, `infographic`, `data-table`.
Generate and optionally download in one operation:
notebooklm-skill generate \
--notebook "AI safety evidence" \
--type slides --lang zh-TW \
--slide-format presenter-slides \
--output ./output/deck.pptx --output-format pptx
Long media jobs can be detached and downloaded later by exact ID:
notebooklm-skill generate --notebook NOTEBOOK_ID --type audio --no-wait
notebooklm-skill list-artifacts --notebook NOTEBOOK_ID --type audio
notebooklm-skill download --notebook NOTEBOOK_ID --type audio \
--artifact-id ARTIFACT_ID --output ./output/podcast.m4a
Convenience commands:
notebooklm-skill podcast --notebook NOTEBOOK_ID --output podcast.m4a
notebooklm-skill qa --notebook NOTEBOOK_ID --difficulty hard --output quiz.json
Generation supports per-type options. Inspect the live contract before composing an unfamiliar call:
notebooklm-skill generate --help
Existing output files and symlinks are rejected. Use `--force` only when the user explicitly wants an overwrite. Quiz and flashcard downloads support JSON, Markdown, or HTML; slide downloads support PDF or PPTX.
High-level pipelines
notebooklm-pipeline research-to-article \
--sources https://example.com/a https://example.com/b \
--title "Evidence review" --language zh-TW --audience "engineers"
notebooklm-pipeline research-to-social \
--sources https://example.com/a --platform threads --variants 3
notebooklm-pipeline batch-digest \
--rss https://example.com/feed.xml --max-entries 20 --qa-count 5
notebooklm-pipeline generate-all \
--files ./paper.pdf --types audio slides report mind-map \
--output-dir ./output --artifact-concurrency 2
`trend-to-content` requires a separately installed `trend-pulse` command. Override its executable safely with `TREND_PULSE_CMD`; the integration does not invoke a shell.
Pipelines create drafts and local artifacts. They do not publish to social networks, CMS products, or other remote destinations.
MCP server
Start stdio mode for an MCP client:
notebooklm-mcp
Example configuration:
{
"mcpServers": {
"notebooklm": {
"command": "uvx",
"args": ["--from", "notebooklm-skill", "notebooklm-mcp"]
}
}
}Available tools:
- `nlm_create_notebook`, `nlm_list`, `nlm_delete`
- `nlm_add_source`, `nlm_list_sources`
- `nlm_ask`, `nlm_summarize`
- `nlm_generate`, `nlm_download`, `nlm_list_artifacts`
- `nlm_research`, `nlm_research_pipeline`, `nlm_trend_research`
Notebook deletion requires `confirm=true`. HTTP mode binds only to loopback:
notebooklm-mcp --http --host 127.0.0.1 --port 8765
Do not expose HTTP mode directly to a network. If remote access is unavoidable, put it behind an authenticated TLS proxy and apply host-level access controls.
Operating rules
1. Verify authenticati
Read more
name: notebooklm-research description: > Automate source-grounded research with Google NotebookLM. Create notebooks from URLs, text, or local files; ask cited questions; run fast or deep web research; create articles and social drafts; and generate or download audio, video, cinematic video, slides, reports, study guides, quizzes, flashcards, mind maps, infographics, and data tables. Use when a user asks for NotebookLM, cited source analysis, research-to-content workflows, podcasts, slides, study material, artifact generation, RSS digests, or trend research.
NotebookLM Research
Use the installed commands or the 13 MCP tools to turn user-provided sources into grounded answers and NotebookLM artifacts. Commands emit JSON on stdout and progress or diagnostics on stderr, so preserve stdout when another tool will consume it.
This integration uses NotebookLM's browser session and unofficial web API through `notebooklm-py`. Do not promise that Google-side availability, quotas, or generation time are stable.
Authentication
Prefer the profile-aware helper:
notebooklm-auth setup notebooklm-auth verify
Use `notebooklm-auth setup --browser chrome --fresh` when the user explicitly wants the locally installed Google Chrome instead of bundled Chromium.
For a zero-install login:
uvx --from notebooklm-py notebooklm login
Profiles are supported through `--profile NAME` before the subcommand or through `NOTEBOOKLM_PROFILE`. Current sessions are normally stored below `~/.notebooklm/profiles/<profile>/storage_state.json`; never read, print, copy, or commit that file. If authentication expires, run setup again.
Core CLI
Create a notebook from mixed sources:
notebooklm-skill create \ --title "AI safety evidence" \ --sources https://example.com/article https://youtu.be/example \ --files ./paper.pdf \ --text-sources "A user-supplied observation" \ --strict
Inspect and ask:
notebooklm-skill list notebooklm-skill list-sources --notebook "AI safety evidence" notebooklm-skill summarize --notebook "AI safety evidence" notebooklm-skill ask --notebook "AI safety evidence" --query "What findings conflict?"
Add exactly one source:
notebooklm-skill add-source --notebook "AI safety evidence" --url https://example.com/new notebooklm-skill add-source --notebook "AI safety evidence" --file ./appendix.docx notebooklm-skill add-source --notebook "AI safety evidence" \ --text "Raw notes" --text-title "Interview notes"
Run NotebookLM web research and import results:
notebooklm-skill research \ --notebook "AI safety evidence" \ --query "Recent empirical evaluations" \ --mode deep --max-sources 10
Use `--no-wait` for a task ID without waiting. Use `--no-import-results` when the research results should not become notebook sources.
Notebook titles may be used only when they resolve uniquely. Prefer IDs in automation.
Artifact generation
Supported canonical types:
`audio`, `video`, `cinematic`, `slides`, `report`, `study-guide`, `quiz`, `flashcards`, `mind-map`, `infographic`, `data-table`.
Generate and optionally download in one operation:
notebooklm-skill generate \ --notebook "AI safety evidence" \ --type slides --lang zh-TW \ --slide-format presenter-slides \ --output ./output/deck.pptx --output-format pptx
Long media jobs can be detached and downloaded later by exact ID:
notebooklm-skill generate --notebook NOTEBOOK_ID --type audio --no-wait notebooklm-skill list-artifacts --notebook NOTEBOOK_ID --type audio notebooklm-skill download --notebook NOTEBOOK_ID --type audio \ --artifact-id ARTIFACT_ID --output ./output/podcast.m4a
Convenience commands:
notebooklm-skill podcast --notebook NOTEBOOK_ID --output podcast.m4a notebooklm-skill qa --notebook NOTEBOOK_ID --difficulty hard --output quiz.json
Generation supports per-type options. Inspect the live contract before composing an unfamiliar call:
notebooklm-skill generate --help
Existing output files and symlinks are rejected. Use `--force` only when the user explicitly wants an overwrite. Quiz and flashcard downloads support JSON, Markdown, or HTML; slide downloads support PDF or PPTX.
High-level pipelines
notebooklm-pipeline research-to-article \ --sources https://example.com/a https://example.com/b \ --title "Evidence review" --language zh-TW --audience "engineers" notebooklm-pipeline research-to-social \ --sources https://example.com/a --platform threads --variants 3 notebooklm-pipeline batch-digest \ --rss https://example.com/feed.xml --max-entries 20 --qa-count 5 notebooklm-pipeline generate-all \ --files ./paper.pdf --types audio slides report mind-map \ --output-dir ./output --artifact-concurrency 2
`trend-to-content` requires a separately installed `trend-pulse` command. Override its executable safely with `TREND_PULSE_CMD`; the integration does not invoke a shell.
Pipelines create drafts and local artifacts. They do not publish to social networks, CMS products, or other remote destinations.
MCP server
Start stdio mode for an MCP client:
notebooklm-mcp
Example configuration:
{
"mcpServers": {
"notebooklm": {
"command": "uvx",
"args": ["--from", "notebooklm-skill", "notebooklm-mcp"]
}
}
}Available tools:
- `nlm_create_notebook`, `nlm_list`, `nlm_delete`
- `nlm_add_source`, `nlm_list_sources`
- `nlm_ask`, `nlm_summarize`
- `nlm_generate`, `nlm_download`, `nlm_list_artifacts`
- `nlm_research`, `nlm_research_pipeline`, `nlm_trend_research`
Notebook deletion requires `confirm=true`. HTTP mode binds only to loopback:
notebooklm-mcp --http --host 127.0.0.1 --port 8765
Do not expose HTTP mode directly to a network. If remote access is unavoidable, put it behind an authenticated TLS proxy and apply host-level access controls.
Operating rules
1. Verify authenticati
Source-grounded NotebookLM automation for terminals and AI agents. notebooklm-skill gives humans and MCP clients one consistent interface for Google NotebookLM.

