NotebookLM Automation

Complete programmatic access to Google NotebookLM—including capabilities not exposed in the web UI. Create notebooks, add sources (URLs, YouTube, PDFs, audio, video, images), chat with content, generate all artifact types, and download results in multiple formats.

Step 0: Setup (Run Automatically on First Use)

When this skill is triggered and notebooklm is not yet installed or authenticated, complete setup first.

Pre-flight: Check Python Version

notebooklm-py requires Python 3.10+. Check the available version before installing:

python3 --version

If Python is below 3.10 (e.g. 3.9.x which is the macOS default), install a compatible version:

macOS (Homebrew):

brew install [email protected]

Then use /opt/homebrew/bin/python3.12 (Apple Silicon) or /usr/local/bin/python3.12 (Intel) for the venv below.

Linux (apt):

sudo apt update && sudo apt install -y python3.12 python3.12-venv

Install the CLI

Always use a virtual environment to avoid "externally-managed-environment" errors and PATH issues.

Determine which Python to use — if the system python3 is 3.10+, use it directly. Otherwise use the one you just installed (e.g. python3.12):

# Set PYTHON to the correct binary (adjust if needed)
PYTHON=$(command -v python3.12 2>/dev/null || command -v python3.11 2>/dev/null || command -v python3.10 2>/dev/null || command -v python3)

# Verify it's 3.10+
$PYTHON -c "import sys; assert sys.version_info >= (3,10), f'Python {sys.version} is too old — need 3.10+'; print(f'Using Python {sys.version}')"

# Create venv and install
$PYTHON -m venv ~/.notebooklm-venv
source ~/.notebooklm-venv/bin/activate
pip install "notebooklm-py[browser]"
playwright install chromium

Then symlink so it's always on PATH:

mkdir -p ~/bin
ln -sf ~/.notebooklm-venv/bin/notebooklm ~/bin/notebooklm
export PATH="$HOME/bin:$PATH"

Verify the CLI works:

notebooklm --help

Authenticate

IMPORTANT: The built-in notebooklm login command requires interactive terminal input (pressing Enter after sign-in). Claude Code's bash tool does NOT support interactive input, so notebooklm login will fail — the browser opens and closes instantly. Instead, use this custom login script.

Tell the user:

I'm going to open a browser window — just sign into your Google account and navigate to notebooklm.google.com. Take your time, I'll wait for you to confirm before closing it.

Then write and run this login script:

cat > /tmp/nlm_login.py << 'PYEOF'
import json, os, time
from pathlib import Path
from playwright.sync_api import sync_playwright

STORAGE_PATH = Path.home() / ".notebooklm" / "storage_state.json"
PROFILE_PATH = Path.home() / ".notebooklm" / "browser_profile"
SIGNAL_FILE = Path("/tmp/nlm_save_signal")

SIGNAL_FILE.unlink(missing_ok=True)
STORAGE_PATH.parent.mkdir(parents=True, exist_ok=True)

print("Opening browser for Google login...")
print("Sign in to Google and navigate to notebooklm.google.com")

with sync_playwright() as p:
    browser = p.chromium.launch_persistent_context(
        user_data_dir=str(PROFILE_PATH),
        headless=False,
        args=["--disable-blink-features=AutomationControlled"],
    )
    page = browser.pages[0] if browser.pages else browser.new_page()
    page.goto("https://notebooklm.google.com/")

    print("Browser is open. Waiting for save signal...")
    while not SIGNAL_FILE.exists():
        time.sleep(1)

    print("Save signal received! Capturing session...")
    storage = browser.storage_state()
    with open(STORAGE_PATH, "w") as f:
        json.dump(storage, f)

    cookie_names = [c["name"] for c in storage.get("cookies", [])]
    print(f"Saved {len(cookie_names)} cookies: {cookie_names}")
    browser.close()

SIGNAL_FILE.unlink(missing_ok=True)
print(f"Authentication saved to: {STORAGE_PATH}")
PYEOF

# Run the login script in the background
source ~/.notebooklm-venv/bin/activate
python3 /tmp/nlm_login.py > /tmp/nlm_login_output.txt 2>&1 &
echo "Login started (PID=$!). Browser should open in a few seconds..."

Wait ~10 seconds for the browser to open, then ask the user if they can see the browser and are signed in.

Once the user confirms they are on the NotebookLM homepage, save the session:

touch /tmp/nlm_save_signal
sleep 8
cat /tmp/nlm_login_output.txt

Then verify authentication:

export PATH="$HOME/bin:$PATH"
notebooklm auth check
notebooklm list

If auth passes (SID cookie present), confirm to the user that NotebookLM is set up and ready. Clean up the temp script:

rm -f /tmp/nlm_login.py /tmp/nlm_login_output.txt /tmp/nlm_save_signal

If auth fails (SID cookie missing), the user may not have fully signed in. Delete the browser profile and retry:

rm -rf ~/.notebooklm/browser_profile ~/.notebooklm/storage_state.json

Then run the login script again from the top.

Adding NotebookLM to Co-work

When the user asks to "add this to Co-work", "use this in Co-work", or "make this work in Co-work":

Step 1: Check auth exists

cat ~/.notebooklm/storage_state.json > /dev/null 2>&1

If it doesn't exist, run the install and authenticate steps above first.

Step 2: Generate the Co-work skill file

Read the contents of this skill file you are currently using. Then read the contents of ~/.notebooklm/storage_state.json.

Create a MODIFIED copy of this skill file where you replace the entire "Step 0: Setup" section and "Adding NotebookLM to Co-work" section with this:

## Auto-Authentication (Co-work)

This skill runs in a sandboxed Co-work environment. Before running ANY notebooklm command, run these setup commands:

\`\`\`bash
pip install notebooklm-py 2>/dev/null
export NOTEBOOKLM_AUTH_JSON='<CONTENTS OF storage_state.json MINIFIED INTO A SINGLE LINE>'
\`\`\`

Then verify:
\`\`\`bash
notebooklm auth check
notebooklm list
\`\`\`

If auth fails, the cookies may have expired. Ask the user to re-run `notebooklm login` in Claude Code and regenerate this file.

To minify the JSON, use:

python3 -c "import json; print(json.dumps(json.load(open('$HOME/.notebooklm/storage_state.json')), separators=(',',':')))"

Step 3: Save and instruct

Save the file to the user's Desktop as NotebookLMSkill-Cowork.md.

Tell the user:

Done! I've saved the Co-work skill to your Desktop as NotebookLMSkill-Cowork.md. Upload it as a skill in Claude Co-work and you'll have full NotebookLM access there too.

Heads up: the cookies in that file will expire eventually. When they do, just come back to Claude Code and say "regenerate my Co-work NotebookLM skill" and I'll make a fresh one.

Ensure AI Brain Notebook Exists

Whenever this skill activates in a project context, ensure the project's AI Brain notebook exists. This is the same notebook used by /wrapup to store session summaries.

Detect the repo name:

basename "$(git rev-parse --show-toplevel 2>/dev/null || basename "$PWD")"

The brain notebook is named <repo-name> AI Brain (e.g. my-project AI Brain)
Check for a saved notebook ID in memory (look for brain_notebook_id in the memory index)
If no ID saved, list notebooks: notebooklm list --json and look for a match
If not found, create it: notebooklm create "<repo-name> AI Brain" --json
Save the notebook ID to memory (reference_brain_notebook.md) and update MEMORY.md

Rule: Before exploring the codebase for any research task, first check the AI Brain for existing context:

notebooklm use <BRAIN_NOTEBOOK_ID>
notebooklm ask "What do we know about <topic>?" --json

Only fall back to codebase exploration if the Brain doesn't have relevant context.

When This Skill Activates

Explicit: User says "/notebooklm", "use notebooklm", "install notebooklm", or mentions the tool by name

Intent detection: Recognize requests like:

"Create a podcast about [topic]"
"Summarize these URLs/documents"
"Generate a quiz from my research"
"Turn this into an audio overview"
"Create flashcards for studying"
"Generate a video explainer"
"Make an infographic"
"Create a mind map of the concepts"
"Download the quiz as markdown"
"Add these sources to NotebookLM"
"Add this to Co-work" / "Make this work in Co-work"

Autonomy Rules

Run automatically (no confirmation):

notebooklm status - check context
notebooklm auth check - diagnose auth issues
notebooklm list - list notebooks
notebooklm source list - list sources
notebooklm artifact list - list artifacts
notebooklm language list - list supported languages
notebooklm language get - get current language
notebooklm language set - set language (global setting)
notebooklm artifact wait - wait for artifact completion
notebooklm source wait - wait for source processing
notebooklm research status - check research status
notebooklm research wait - wait for research
notebooklm use <id> - set context
notebooklm create - create notebook
notebooklm ask "..." - chat queries (without --save-as-note)
notebooklm history - display conversation history (read-only)
notebooklm source add - add sources

Ask before running:

notebooklm delete - destructive
notebooklm generate * - long-running, may fail
notebooklm download * - writes to filesystem
notebooklm ask "..." --save-as-note - writes a note
notebooklm history --save - writes a note

Quick Reference

| Task | Command | |------|---------| | List notebooks | notebooklm list | | Create notebook | notebooklm create "Title" | | Set context | notebooklm use <notebook_id> | | Show context | notebooklm status | | Add URL source | notebooklm source add "https://..." | | Add file | notebooklm source add ./file.pdf | | Add YouTube | notebooklm source add "https://youtube.com/..." | | List sources | notebooklm source list | | Wait for source processing | notebooklm source wait <source_id> | | Web research (fast) | notebooklm source add-research "query" | | Web research (deep) | notebooklm source add-research "query" --mode deep --no-wait | | Check research status | notebooklm research status | | Wait for research | notebooklm research wait --import-all | | Chat | notebooklm ask "question" | | Chat (specific sources) | notebooklm ask "question" -s src_id1 -s src_id2 | | Chat (with references) | notebooklm ask "question" --json | | Chat (save answer as note) | notebooklm ask "question" --save-as-note | | Show conversation history | notebooklm history | | Save all history as note | notebooklm history --save | | Get source fulltext | notebooklm source fulltext <source_id> | | Generate podcast | notebooklm generate audio "instructions" | | Generate video | notebooklm generate video "instructions" | | Generate report | notebooklm generate report --format briefing-doc | | Generate quiz | notebooklm generate quiz | | Generate flashcards | notebooklm generate flashcards | | Generate infographic | notebooklm generate infographic | | Generate mind map | notebooklm generate mind-map | | Generate slide deck | notebooklm generate slide-deck | | Revise a slide | notebooklm generate revise-slide "prompt" --artifact <id> --slide 0 | | Check artifact status | notebooklm artifact list | | Wait for completion | notebooklm artifact wait <artifact_id> | | Download audio | notebooklm download audio ./output.mp3 | | Download video | notebooklm download video ./output.mp4 | | Download slide deck (PDF) | notebooklm download slide-deck ./slides.pdf | | Download slide deck (PPTX) | notebooklm download slide-deck ./slides.pptx --format pptx | | Download report | notebooklm download report ./report.md | | Download mind map | notebooklm download mind-map ./map.json | | Download data table | notebooklm download data-table ./data.csv | | Download quiz | notebooklm download quiz quiz.json | | Download flashcards | notebooklm download flashcards cards.json | | List languages | notebooklm language list | | Set language | notebooklm language set zh_Hans |

Generation Types

All generate commands support:

-s, --source to use specific source(s) instead of all sources
--language to set output language (defaults to 'en')
--json for machine-readable output
--retry N to automatically retry on rate limits

| Type | Command | Options | Download | |------|---------|---------|----------| | Podcast | generate audio | --format [deep-dive\|brief\|critique\|debate], --length [short\|default\|long] | .mp3 | | Video | generate video | --format [explainer\|brief], --style [auto\|classic\|whiteboard\|kawaii\|anime\|watercolor\|retro-print\|heritage\|paper-craft] | .mp4 | | Slide Deck | generate slide-deck | --format [detailed\|presenter], --length [default\|short] | .pdf / .pptx | | Slide Revision | generate revise-slide "prompt" --artifact <id> --slide N | --wait, --notebook | (re-downloads parent deck) | | Infographic | generate infographic | --orientation [landscape\|portrait\|square], --detail [concise\|standard\|detailed] | .png | | Report | generate report | --format [briefing-doc\|study-guide\|blog-post\|custom], --append "extra instructions" | .md | | Mind Map | generate mind-map | (sync, instant) | .json | | Data Table | generate data-table | description required | .csv | | Quiz | generate quiz | --difficulty [easy\|medium\|hard], --quantity [fewer\|standard\|more] | .json/.md/.html | | Flashcards | generate flashcards | --difficulty [easy\|medium\|hard], --quantity [fewer\|standard\|more] | .json/.md/.html |

Common Workflows

Research to Podcast

notebooklm create "Research: [topic]"
notebooklm source add for each URL/document
Wait for sources: notebooklm source list --json until all status=READY
notebooklm generate audio "Focus on [specific angle]"
Check notebooklm artifact list for status
notebooklm download audio ./podcast.mp3 when complete

Document Analysis

notebooklm create "Analysis: [project]"
notebooklm source add ./doc.pdf (or URLs)
notebooklm ask "Summarize the key points"
Continue chatting as needed

Output Formats (--json)

// notebooklm list --json
{"notebooks": [{"id": "...", "title": "...", "created_at": "..."}]}

// notebooklm source list --json
{"sources": [{"id": "...", "title": "...", "status": "ready|processing|error"}]}

// notebooklm artifact list --json
{"artifacts": [{"id": "...", "title": "...", "type": "Audio Overview", "status": "in_progress|pending|completed|unknown"}]}

Error Handling

| Error | Cause | Action | |-------|-------|--------| | Auth/cookie error | Session expired | Re-run notebooklm login | | "No notebook context" | Context not set | Run notebooklm use <id> | | Rate limiting | Google throttle | Wait 5-10 min, retry | | Download fails | Generation incomplete | Check artifact list for status |

Known Limitations

Audio, video, quiz, flashcard, infographic, and slide deck generation may fail due to Google rate limits
Generation times: audio 10-20 min, video 15-45 min, quiz/flashcards 5-15 min
This is an unofficial API — Google can change things without warning

NotebookLM Automation

Step 0: Setup (Run Automatically on First Use)

When this skill is triggered and notebooklm is not yet installed or authenticated, complete setup first.

Pre-flight: Check Python Version

notebooklm-py requires Python 3.10+. Check the available version before installing:

python3 --version

If Python is below 3.10 (e.g. 3.9.x which is the macOS default), install a compatible version:

macOS (Homebrew):

brew install [email protected]

Then use /opt/homebrew/bin/python3.12 (Apple Silicon) or /usr/local/bin/python3.12 (Intel) for the venv below.

Linux (apt):

sudo apt update && sudo apt install -y python3.12 python3.12-venv

Install the CLI

Always use a virtual environment to avoid "externally-managed-environment" errors and PATH issues.

Determine which Python to use — if the system python3 is 3.10+, use it directly. Otherwise use the one you just installed (e.g. python3.12):

# Set PYTHON to the correct binary (adjust if needed)
PYTHON=$(command -v python3.12 2>/dev/null || command -v python3.11 2>/dev/null || command -v python3.10 2>/dev/null || command -v python3)

# Verify it's 3.10+
$PYTHON -c "import sys; assert sys.version_info >= (3,10), f'Python {sys.version} is too old — need 3.10+'; print(f'Using Python {sys.version}')"

# Create venv and install
$PYTHON -m venv ~/.notebooklm-venv
source ~/.notebooklm-venv/bin/activate
pip install "notebooklm-py[browser]"
playwright install chromium

Then symlink so it's always on PATH:

mkdir -p ~/bin
ln -sf ~/.notebooklm-venv/bin/notebooklm ~/bin/notebooklm
export PATH="$HOME/bin:$PATH"

Verify the CLI works:

notebooklm --help

Authenticate

Tell the user:

I'm going to open a browser window — just sign into your Google account and navigate to notebooklm.google.com. Take your time, I'll wait for you to confirm before closing it.

Then write and run this login script:

cat > /tmp/nlm_login.py << 'PYEOF'
import json, os, time
from pathlib import Path
from playwright.sync_api import sync_playwright

STORAGE_PATH = Path.home() / ".notebooklm" / "storage_state.json"
PROFILE_PATH = Path.home() / ".notebooklm" / "browser_profile"
SIGNAL_FILE = Path("/tmp/nlm_save_signal")

SIGNAL_FILE.unlink(missing_ok=True)
STORAGE_PATH.parent.mkdir(parents=True, exist_ok=True)

print("Opening browser for Google login...")
print("Sign in to Google and navigate to notebooklm.google.com")

with sync_playwright() as p:
    browser = p.chromium.launch_persistent_context(
        user_data_dir=str(PROFILE_PATH),
        headless=False,
        args=["--disable-blink-features=AutomationControlled"],
    )
    page = browser.pages[0] if browser.pages else browser.new_page()
    page.goto("https://notebooklm.google.com/")

    print("Browser is open. Waiting for save signal...")
    while not SIGNAL_FILE.exists():
        time.sleep(1)

    print("Save signal received! Capturing session...")
    storage = browser.storage_state()
    with open(STORAGE_PATH, "w") as f:
        json.dump(storage, f)

    cookie_names = [c["name"] for c in storage.get("cookies", [])]
    print(f"Saved {len(cookie_names)} cookies: {cookie_names}")
    browser.close()

SIGNAL_FILE.unlink(missing_ok=True)
print(f"Authentication saved to: {STORAGE_PATH}")
PYEOF

# Run the login script in the background
source ~/.notebooklm-venv/bin/activate
python3 /tmp/nlm_login.py > /tmp/nlm_login_output.txt 2>&1 &
echo "Login started (PID=$!). Browser should open in a few seconds..."

Wait ~10 seconds for the browser to open, then ask the user if they can see the browser and are signed in.

Once the user confirms they are on the NotebookLM homepage, save the session:

touch /tmp/nlm_save_signal
sleep 8
cat /tmp/nlm_login_output.txt

Then verify authentication:

export PATH="$HOME/bin:$PATH"
notebooklm auth check
notebooklm list

If auth passes (SID cookie present), confirm to the user that NotebookLM is set up and ready. Clean up the temp script:

rm -f /tmp/nlm_login.py /tmp/nlm_login_output.txt /tmp/nlm_save_signal

If auth fails (SID cookie missing), the user may not have fully signed in. Delete the browser profile and retry:

rm -rf ~/.notebooklm/browser_profile ~/.notebooklm/storage_state.json

Then run the login script again from the top.

Adding NotebookLM to Co-work

When the user asks to "add this to Co-work", "use this in Co-work", or "make this work in Co-work":

Step 1: Check auth exists

cat ~/.notebooklm/storage_state.json > /dev/null 2>&1

If it doesn't exist, run the install and authenticate steps above first.

Step 2: Generate the Co-work skill file

Read the contents of this skill file you are currently using. Then read the contents of ~/.notebooklm/storage_state.json.

Create a MODIFIED copy of this skill file where you replace the entire "Step 0: Setup" section and "Adding NotebookLM to Co-work" section with this:

## Auto-Authentication (Co-work)

This skill runs in a sandboxed Co-work environment. Before running ANY notebooklm command, run these setup commands:

\`\`\`bash
pip install notebooklm-py 2>/dev/null
export NOTEBOOKLM_AUTH_JSON='<CONTENTS OF storage_state.json MINIFIED INTO A SINGLE LINE>'
\`\`\`

Then verify:
\`\`\`bash
notebooklm auth check
notebooklm list
\`\`\`

If auth fails, the cookies may have expired. Ask the user to re-run `notebooklm login` in Claude Code and regenerate this file.

To minify the JSON, use:

python3 -c "import json; print(json.dumps(json.load(open('$HOME/.notebooklm/storage_state.json')), separators=(',',':')))"

Step 3: Save and instruct

Save the file to the user's Desktop as NotebookLMSkill-Cowork.md.

Tell the user:

Done! I've saved the Co-work skill to your Desktop as NotebookLMSkill-Cowork.md. Upload it as a skill in Claude Co-work and you'll have full NotebookLM access there too.

Heads up: the cookies in that file will expire eventually. When they do, just come back to Claude Code and say "regenerate my Co-work NotebookLM skill" and I'll make a fresh one.

Ensure AI Brain Notebook Exists

Whenever this skill activates in a project context, ensure the project's AI Brain notebook exists. This is the same notebook used by /wrapup to store session summaries.

Detect the repo name:

basename "$(git rev-parse --show-toplevel 2>/dev/null || basename "$PWD")"

The brain notebook is named <repo-name> AI Brain (e.g. my-project AI Brain)
Check for a saved notebook ID in memory (look for brain_notebook_id in the memory index)
If no ID saved, list notebooks: notebooklm list --json and look for a match
If not found, create it: notebooklm create "<repo-name> AI Brain" --json
Save the notebook ID to memory (reference_brain_notebook.md) and update MEMORY.md

Rule: Before exploring the codebase for any research task, first check the AI Brain for existing context:

notebooklm use <BRAIN_NOTEBOOK_ID>
notebooklm ask "What do we know about <topic>?" --json

Only fall back to codebase exploration if the Brain doesn't have relevant context.

When This Skill Activates

Explicit: User says "/notebooklm", "use notebooklm", "install notebooklm", or mentions the tool by name

Intent detection: Recognize requests like:

"Create a podcast about [topic]"
"Summarize these URLs/documents"
"Generate a quiz from my research"
"Turn this into an audio overview"
"Create flashcards for studying"
"Generate a video explainer"
"Make an infographic"
"Create a mind map of the concepts"
"Download the quiz as markdown"
"Add these sources to NotebookLM"
"Add this to Co-work" / "Make this work in Co-work"

Autonomy Rules

Run automatically (no confirmation):

notebooklm status - check context
notebooklm auth check - diagnose auth issues
notebooklm list - list notebooks
notebooklm source list - list sources
notebooklm artifact list - list artifacts
notebooklm language list - list supported languages
notebooklm language get - get current language
notebooklm language set - set language (global setting)
notebooklm artifact wait - wait for artifact completion
notebooklm source wait - wait for source processing
notebooklm research status - check research status
notebooklm research wait - wait for research
notebooklm use <id> - set context
notebooklm create - create notebook
notebooklm ask "..." - chat queries (without --save-as-note)
notebooklm history - display conversation history (read-only)
notebooklm source add - add sources

Ask before running:

notebooklm delete - destructive
notebooklm generate * - long-running, may fail
notebooklm download * - writes to filesystem
notebooklm ask "..." --save-as-note - writes a note
notebooklm history --save - writes a note

Quick Reference

Generation Types

All generate commands support:

-s, --source to use specific source(s) instead of all sources
--language to set output language (defaults to 'en')
--json for machine-readable output
--retry N to automatically retry on rate limits

Common Workflows

Research to Podcast

notebooklm create "Research: [topic]"
notebooklm source add for each URL/document
Wait for sources: notebooklm source list --json until all status=READY
notebooklm generate audio "Focus on [specific angle]"
Check notebooklm artifact list for status
notebooklm download audio ./podcast.mp3 when complete

Document Analysis

notebooklm create "Analysis: [project]"
notebooklm source add ./doc.pdf (or URLs)
notebooklm ask "Summarize the key points"
Continue chatting as needed

Output Formats (--json)

// notebooklm list --json
{"notebooks": [{"id": "...", "title": "...", "created_at": "..."}]}

// notebooklm source list --json
{"sources": [{"id": "...", "title": "...", "status": "ready|processing|error"}]}

// notebooklm artifact list --json
{"artifacts": [{"id": "...", "title": "...", "type": "Audio Overview", "status": "in_progress|pending|completed|unknown"}]}

Error Handling

Known Limitations

Audio, video, quiz, flashcard, infographic, and slide deck generation may fail due to Google rate limits
Generation times: audio 10-20 min, video 15-45 min, quiz/flashcards 5-15 min
This is an unofficial API — Google can change things without warning

Adoption

bereniketech/notebooklm

$ install --global

Security Scan Results

SKILL.md

NotebookLM Automation

Step 0: Setup (Run Automatically on First Use)

Pre-flight: Check Python Version

Install the CLI

Authenticate

Adding NotebookLM to Co-work

Step 1: Check auth exists

Step 2: Generate the Co-work skill file

Step 3: Save and instruct

Ensure AI Brain Notebook Exists

When This Skill Activates

Autonomy Rules

Quick Reference

Generation Types

Common Workflows

Research to Podcast

Document Analysis

Output Formats (--json)

Error Handling

Known Limitations

Related Skills

bereniketech/anti-reversing-techniques

bereniketech/active-directory-attacks

bereniketech/zeroize-audit

bereniketech/wcag-audit-patterns

bereniketech/notebooklm

$ install --global

Security Scan Results

SKILL.md

NotebookLM Automation

Step 0: Setup (Run Automatically on First Use)

Pre-flight: Check Python Version

Install the CLI

Authenticate

Adding NotebookLM to Co-work

Step 1: Check auth exists

Step 2: Generate the Co-work skill file

Step 3: Save and instruct

Ensure AI Brain Notebook Exists

When This Skill Activates

Autonomy Rules

Quick Reference

Generation Types

Common Workflows

Research to Podcast

Document Analysis

Output Formats (--json)

Error Handling

Known Limitations

Related Skills

bereniketech/anti-reversing-techniques

bereniketech/active-directory-attacks

bereniketech/zeroize-audit

bereniketech/wcag-audit-patterns