Wowerpoint

One doc in, one PDF out. Slide-deck only — videos and podcasts from the same engine are noticeably worse and out of scope; refer the user to the

notebooklm

CLI directly if they want those.

Triggers

"Wowerpoint <file>"
"Make a slide deck about <file>"
"Turn this report into slides"
"Kawaii-deck this"

Setup (one-time per machine)

notebooklm auth check

returns 0 and

command -v jq

resolves, skip.

bash

uv tool install --with playwright --force notebooklm-py
$(uv tool dir)/notebooklm-py/bin/playwright install chromium

jq

is required by the workflow's JSON parsing; install if missing (

brew install jq

on macOS, or your distro's package manager).

Then the user authenticates interactively — do not script. Tell them to type

! notebooklm login

so the OAuth ENTER lands in their terminal.

Workflow

1. The source doc

You need exactly one source doc. If it doesn't exist or is too thin to carry a deck, write it first — use mem-search and sequential thinking to make it comprehensive (long-form, narrative, several thousand words is normal). Do not paper over a weak source by adding more sources.

2. Auth pre-flight

bash

notebooklm auth check 2>&1 | tail -5

Exit 1 with

Run 'notebooklm login' to authenticate.

= halt and tell the user.

3. Create notebook, add the source

bash

NOTEBOOK_ID=$(notebooklm create "<title>" --json | jq -r .notebook.id)
SOURCE_ID=$(notebooklm source add "<doc-path>" --notebook "$NOTEBOOK_ID" --json | jq -r .source.id)

Title: H1 of the source doc, or its filename stem; append a date for dated work.

JSON envelope keys differ —

create

→

.notebook.id

source add

→

.source.id

generate

→

.task_id

. Wrong key = empty string = silent downstream failure.

4. Spawn the subagent

Generation takes ~10 minutes; never block on it. Use the template below with

run_in_background: true

5. End your turn

Print the notebook URL so the user can watch live:

text

https://notebooklm.google.com/notebook/<NOTEBOOK_ID>

The subagent's completion notification fires when the file is on disk.

Output path

Adjacent to the source, parallel filename:

text

<source-dir>/<source-stem>-slides.pdf

If the source isn't somewhere that makes sense as an output location, default to

reports/<stem>-slides.pdf

The prompt

One sentence. Default:

text

Use kawaii characters to tell the story of <subject>. Keep it warm and clear.

Replace

<subject>

with a one-phrase description from the source doc's H1 or the user's framing. If the user supplies their own prompt, pass it through verbatim — don't expand it.

Subagent template (copy-paste, parameterize)

text

You're handling NotebookLM slide-deck generation. Work in `<repo-absolute-path>`.

Context:
- The `notebooklm` CLI is installed and authenticated (parent verified with `notebooklm auth check`).
- A notebook and source already exist.

Inputs:
- Notebook ID: `<NOTEBOOK_ID>`
- Source ID: `<SOURCE_ID>`
- Generation prompt: `<PROMPT>`
- Output path: `<OUTPUT_PATH>`

Steps:

1. Wait for source: `notebooklm source wait <SOURCE_ID> -n <NOTEBOOK_ID> --timeout 600`
   Exit 0 = ready, 1 = error, 2 = timeout. On timeout, run `notebooklm source list -n <NOTEBOOK_ID> --json` and report status.

2. Generate: `notebooklm generate slide-deck "<PROMPT>" --format detailed --length default --notebook <NOTEBOOK_ID> --json --retry 2`
   Parse `task_id` from the JSON (key is `task_id` at top level).
   On `GENERATION_FAILED` or "No result found for RPC ID": sleep 300, retry once, then give up.

3. Wait for artifact: `notebooklm artifact wait <task_id> -n <NOTEBOOK_ID> --timeout 1800`

4. Download: `notebooklm download slide-deck <OUTPUT_PATH> -a <task_id> -n <NOTEBOOK_ID>`

5. Verify: `ls -la <OUTPUT_PATH>` confirms the file exists.

Report briefly (under 200 words):
- Final artifact ID
- Time per phase (source wait, generation, render wait, download)
- Output file path + size
- Any retries or warnings
- Exact error message if any step failed

Do NOT poll status manually. The `wait` commands handle backoff.

Failure modes

pip: command not found
— modern macOS doesn't ship pip on PATH. Use
```
uv tool install
```
.

Playwright not installed
— install

notebooklm-py

with

--with playwright

, then

playwright install chromium

Run 'notebooklm login' to authenticate
— only the user can complete OAuth.
task_id
parsed as empty string — wrong JSON envelope key.
```
generate
```
returns
```
{"task_id": "..."}
```
at top level.
Rate-limit (
GENERATION_FAILED
or "No result found for RPC ID") —
```
--retry 2
```
handles transients; persistent failure means wait 5–10 minutes or fall back to the web UI.
Source upload denied for sensitive docs — confirm before adding sources containing credentials, customer data, or unreleased product info. NotebookLM is a Google service.
--length long
does not exist — only
```
default|short
```
. If the user asks for "long slides," use
```
default
```
and explain.
No
--style
flag — kawaii lives in the prompt text.

Operational tips

Rerun cheaply — once the notebook + source exist, regenerating with a different prompt only repeats generation + download. Reuse
```
NOTEBOOK_ID
```
and
```
SOURCE_ID
```
.
Web UI fallback — if generation is rate-limited >30 minutes, open the notebook URL, trigger generation in the UI, then
```
notebooklm artifact list -n <NOTEBOOK_ID>
```
and
```
download
```
.

wowerpoint

NPX Install

Tags

SKILL.md Content

Wowerpoint

Triggers

Setup (one-time per machine)

Workflow

1. The source doc

2. Auth pre-flight

3. Create notebook, add the source

4. Spawn the subagent

5. End your turn

Output path

The prompt

Subagent template (copy-paste, parameterize)

Failure modes

Operational tips