nlm-skill

分类: 内容与多媒体 | 上传者: jacob-bd | 下载: 0 | 版本: v1.0（最新）
NotebookLM CLI (`nlm`) 和 MCP 服务器的专家指南 - Google NotebookLM 的接口。当用户想要以编程方式与 NotebookLM 交互时，请使用此技能，包括：创建/管理笔记本、添加源（URL、YouTube、文本、Google Drive）、生成内容（播客、报告、测验、抽认卡、思维导图、幻灯片、信息图表、视频、数据表）、进行研究、与源聊天或自动化 NotebookLM 工作流程。在提及“nlm”、“notebooklm”、“notebook lm”、“播客生成”、“音频概述”或任何与 NotebookLM 相关的自动化任务时触发。
更新日志: Source: GitHub https://github.com/jacob-bd/notebooklm-mcp-cli
目录结构

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📁 references/
- 📄 command_reference.md 17.9 KB
- 📄 troubleshooting.md 7.9 KB
- 📄 workflows.md 12.0 KB
📄 AGENTS_SECTION.md 2.7 KB
📄 SKILL.md 27.3 KB
SKILL.md

---
name: nlm-skill
version: "0.5.11"
description: "Expert guide for the NotebookLM CLI (`nlm`) and MCP server - interfaces for Google NotebookLM. Use this skill when users want to interact with NotebookLM programmatically, including: creating/managing notebooks, adding sources (URLs, YouTube, text, Google Drive), generating content (podcasts, reports, quizzes, flashcards, mind maps, slides, infographics, videos, data tables), conducting research, chatting with sources, or automating NotebookLM workflows. Triggers on mentions of \"nlm\", \"notebooklm\", \"notebook lm\", \"podcast generation\", \"audio overview\", or any NotebookLM-related automation task."
---

# NotebookLM CLI & MCP Expert

This skill provides comprehensive guidance for using NotebookLM via both the `nlm` CLI and MCP tools.

## Tool Detection (CRITICAL - Read First!)

**ALWAYS check which tools are available before proceeding:**

1. **Check for MCP tools**: Look for tools starting with `mcp__notebooklm-mcp__*` or `mcp_notebooklm_*`
2. **If BOTH MCP tools AND CLI are available**: **ASK the user** which they prefer to use before proceeding
3. **If only MCP tools are available**: Use them directly (refer to tool docstrings for parameters)
4. **If only CLI is available**: Use `nlm` CLI commands via Bash

**Decision Logic:**
```
has_mcp_tools = check_available_tools()  # Look for mcp__notebooklm-mcp__* or mcp_notebooklm_*
has_cli = check_bash_available()  # Can run nlm commands

if has_mcp_tools and has_cli:
    # ASK USER: "I can use either MCP tools or the nlm CLI. Which do you prefer?"
    user_preference = ask_user()
else if has_mcp_tools:
    # Use MCP tools directly
    mcp__notebooklm-mcp__notebook_list()
else:
    # Use CLI via Bash
    bash("nlm notebook list")
```

This skill documents BOTH approaches. Choose the appropriate one based on tool availability and **user preference**.

## Quick Reference

**Run `nlm --ai` to get comprehensive AI-optimized documentation** - this provides a complete view of all CLI capabilities.

```bash
nlm --help              # List all commands
nlm <command> --help    # Help for specific command
nlm --ai                # Full AI-optimized documentation (RECOMMENDED)
nlm --version           # Check installed version
```

## Critical Rules (Read First!)

1. **Always authenticate first**: Run `nlm login` before any operations
2. **Sessions expire in ~20 minutes**: Re-run `nlm login` if commands start failing
3. **⚠️ ALWAYS ASK USER BEFORE DELETE**: Before executing ANY delete command, ask the user for explicit confirmation. Deletions are **irreversible**. Show what will be deleted and warn about permanent data loss.
4. **`--confirm` is REQUIRED**: All generation and delete commands need `--confirm` or `-y` (CLI) or `confirm=True` (MCP)
5. **Research requires `--notebook-id`**: The flag is mandatory, not positional
6. **Capture IDs from output**: Create/start commands return IDs needed for subsequent operations
7. **Use aliases**: Simplify long UUIDs with `nlm alias set <name> <uuid>`
8. **Check aliases before creating**: Run `nlm alias list` before creating a new alias to avoid conflicts with existing names.
9. **DO NOT launch REPL**: Never use `nlm chat start` - it opens an interactive REPL that AI tools cannot control. Use `nlm notebook query` for one-shot Q&A instead.
10. **Choose output format wisely**: Default output (no flags) is compact and token-efficient—use it for status checks. Use `--quiet` to capture IDs for piping. Only use `--json` when you need to parse specific fields programmatically.
11. **Use `--help` when unsure**: Run `nlm <command> --help` to see available options and flags for any command.

## Workflow Decision Tree

Use this to determine the right sequence of commands:

```
User wants to...
│
├─► Work with NotebookLM for the first time
│   └─► nlm login → nlm notebook create "Title"
│
├─► Add content to a notebook
│   ├─► From a URL/webpage → nlm source add <nb-id> --url "https://..."
│   ├─► From YouTube → nlm source add <nb-id> --url "https://youtube.com/..."
│   ├─► From pasted text → nlm source add <nb-id> --text "content" --title "Title"
│   ├─► From Google Drive → nlm source add <nb-id> --drive <doc-id> --type doc
│   └─► Discover new sources → nlm research start "query" --notebook-id <nb-id>
│
├─► Generate content from sources
│   ├─► Podcast/Audio → nlm audio create <nb-id> --confirm
│   ├─► Written summary → nlm report create <nb-id> --confirm
│   ├─► Study materials → nlm quiz/flashcards create <nb-id> --confirm
│   ├─► Visual content → nlm mindmap/slides/infographic create <nb-id> --confirm
│   ├─► Video → nlm video create <nb-id> --confirm
│   └─► Extract data → nlm data-table create <nb-id> "description" --confirm
│
├─► Ask questions about sources
│   └─► nlm notebook query <nb-id> "question"
│       (Use --conversation-id for follow-ups)
│       ⚠️ Do NOT use `nlm chat start` - it's a REPL for humans only
│
├─► Check generation status
│   └─► nlm studio status <nb-id>
│
└─► Manage/cleanup
    ├─► List notebooks → nlm notebook list
    ├─► List sources → nlm source list <nb-id>
    ├─► Delete source → nlm source delete <source-id> --confirm
    └─► Delete notebook → nlm notebook delete <nb-id> --confirm
```

## Command Categories

### 1. Authentication

#### MCP Authentication

If using MCP tools and encountering authentication errors:

```bash
# Run the CLI authentication (works for both CLI and MCP)
nlm login

# Then reload tokens in MCP
mcp__notebooklm-mcp__refresh_auth()
```

Or manually save cookies via MCP (fallback):
```python
# Extract cookies from Chrome DevTools and save
mcp__notebooklm-mcp__save_auth_tokens(cookies="<cookie_header>")
```
```

#### CLI Authentication

```bash
nlm login                           # Launch browser, extract cookies (primary method)
nlm login --check                   # Validate current session
nlm login --profile work            # Use named profile for multiple accounts
nlm login --provider openclaw --cdp-url http://127.0.0.1:18800  # External CDP provider
nlm login switch <profile>          # Switch the default profile
nlm login profile list              # List all profiles with email addresses
nlm login profile delete <name>     # Delete a profile
nlm login profile rename <old> <new> # Rename a profile
```

**Multi-Profile Support**: Each profile gets its own isolated browser session (supports Chrome, Arc, Brave, Edge, Chromium, and more), so you can be logged into multiple Google accounts simultaneously.

**Session lifetime**: ~20 minutes. Re-authenticate when commands fail with auth errors.

**Switching MCP Accounts**: The MCP server always uses the active default profile. If you need to switch which Google account the MCP server is communicating with, you MUST use the CLI: run `nlm login switch <name>`. Your next MCP tool call will instantly use the new account.

**Note**: Both MCP and CLI share the same authentication backend, so authenticating with one works for both.

### 2. Notebook Management

#### MCP Tools

Use tools: `notebook_list`, `notebook_create`, `notebook_get`, `notebook_describe`, `notebook_query`, `notebook_rename`, `notebook_delete`. All accept `notebook_id` parameter. Delete requires `confirm=True`.

#### CLI Commands
```bash
nlm notebook list                      # List all notebooks
nlm notebook list --json               # JSON output for parsing
nlm notebook list --quiet              # IDs only (for scripting)
nlm notebook create "Title"            # Create notebook, returns ID
nlm notebook get <id>                  # Get notebook details
nlm notebook describe <id>             # AI-generated summary + suggested topics
nlm notebook query <id> "question"     # One-shot Q&A with sources
nlm notebook rename <id> "New Title"   # Rename notebook
nlm notebook delete <id> --confirm     # PERMANENT deletion
```

### 3. Source Management

#### MCP Tools

Use `source_add` with these `source_type` values:
- `url` - Web page or YouTube URL (`url` param)
- `text` - Pasted content (`text` + `title` params)
- `file` - Local file upload (`file_path` param)
- `drive` - Google Drive doc (`document_id` + `doc_type` params)

Other tools: `source_list_drive`, `source_describe`, `source_get_content`, `source_rename`, `source_sync_drive` (requires `confirm=True`), `source_delete` (requires `confirm=True`).

#### CLI Commands
```bash
# Adding sources
nlm source add <nb-id> --url "https://..."           # Web page
nlm source add <nb-id> --url "https://youtube.com/..." # YouTube video
nlm source add <nb-id> --text "content" --title "X"  # Pasted text
nlm source add <nb-id> --drive <doc-id>              # Drive doc (auto-detect type)
nlm source add <nb-id> --drive <doc-id> --type slides # Explicit type

# Listing and viewing
nlm source list <nb-id>                # Table of sources
nlm source list <nb-id> --drive        # Show Drive sources with freshness
nlm source list <nb-id> --drive -S     # Skip freshness checks (faster)
nlm source get <source-id>             # Source metadata
nlm source describe <source-id>        # AI summary + keywords
nlm source content <source-id>         # Raw text content
nlm source content <source-id> -o file.txt  # Export to file

# Drive sync (for stale sources)
nlm source stale <nb-id>               # List outdated Drive sources
nlm source sync <nb-id> --confirm      # Sync all stale sources
nlm source sync <nb-id> --source-ids <ids> --confirm  # Sync specific

# Rename
nlm source rename <source-id> "New Title" --notebook <nb-id>
nlm rename source <source-id> "New Title" --notebook <nb-id>  # verb-first

# Deletion
nlm source delete <source-id> --confirm
```

**Drive types**: `doc`, `slides`, `sheets`, `pdf`

### 4. Research (Source Discovery)

Research finds NEW sources from the web or Google Drive.

#### MCP Tools

Use `research_start` with:
- `source`: `web` or `drive`
- `mode`: `fast` (~30s) or `deep` (~5min, web only)

Workflow: `research_start` → poll `research_status` → `research_import`

#### CLI Commands
```bash
# Start research (--notebook-id is REQUIRED)
nlm research start "query" --notebook-id <id>              # Fast web (~30s)
nlm research start "query" --notebook-id <id> --mode deep  # Deep web (~5min)
nlm research start "query" --notebook-id <id> --source drive  # Drive search

# Check progress
nlm research status <nb-id>                   # Poll until done (5min max)
nlm research status <nb-id> --max-wait 0      # Single check, no waiting
nlm research status <nb-id> --task-id <tid>   # Check specific task
nlm research status <nb-id> --full            # Full details

# Import discovered sources
nlm research import <nb-id> <task-id>            # Import all
nlm research import <nb-id> <task-id> --indices 0,2,5  # Import specific
nlm research import <nb-id> <task-id> --timeout 600    # Custom timeout (default: 300s)
```

**Modes**: `fast` (~30s, ~10 sources) | `deep` (~5min, ~40+ sources, web only)

### 5. Content Generation (Studio)

#### MCP Tools (Unified Creation)

Use `studio_create` with `artifact_type` and type-specific options. All require `confirm=True`.

| artifact_type | Key Options |
|--------------|-------------|
| `audio` | `audio_format`: deep_dive/brief/critique/debate, `audio_length`: short/default/long |
| `video` | `video_format`: explainer/brief, `visual_style`: auto_select/classic/whiteboard/kawaii/anime/watercolor/retro_print/heritage/paper_craft |
| `report` | `report_format`: Briefing Doc/Study Guide/Blog Post/Create Your Own, `custom_prompt` |
| `quiz` | `question_count`, `difficulty`: easy/medium/hard |
| `flashcards` | `difficulty`: easy/medium/hard |
| `mind_map` | `title` |
| `slide_deck` | `slide_format`: detailed_deck/presenter_slides, `slide_length`: short/default |
| `infographic` | `orientation`: landscape/portrait/square, `detail_level`: concise/standard/detailed, `infographic_style`: auto_select/sketch_note/professional/bento_grid/editorial/instructional/bricks/clay/anime/kawaii/scientific |
| `data_table` | `description` (REQUIRED) |

**Common options**: `source_ids`, `language` (BCP-47 code), `focus_prompt`

**Revise Slides:** Use `studio_revise` to revise individual slides in an existing slide deck.
- Requires `artifact_id` (from `studio_status`) and `slide_instructions`
- Creates a NEW artifact — the original is not modified
- Slide numbers are 1-based (slide 1 = first slide)
- Poll `studio_status` after calling to check when the new deck is ready

#### CLI Commands

All generation commands share these flags:
- `--confirm` or `-y`: **REQUIRED** to execute
- `--source-ids <id1,id2>`: Limit to specific sources
- `--language <code>`: BCP-47 code (en, es, fr, de, ja)

```bash
# Audio (Podcast)
nlm audio create <id> --confirm
nlm audio create <id> --format deep_dive --length default --confirm
nlm audio create <id> --format brief --focus "key topic" --confirm
# Formats: deep_dive, brief, critique, debate
# Lengths: short, default, long

# Report
nlm report create <id> --confirm
nlm report create <id> --format "Study Guide" --confirm
nlm report create <id> --format "Create Your Own" --prompt "Custom..." --confirm
# Formats: "Briefing Doc", "Study Guide", "Blog Post", "Create Your Own"

# Quiz
nlm quiz create <id> --confirm
nlm quiz create <id> --count 5 --difficulty 3 --confirm
nlm quiz create <id> --count 10 --difficulty 3 --focus "Focus on key concepts" --confirm
# Count: number of questions (default: 2)
# Difficulty: 1-5 (1=easy, 5=hard)
# Focus: optional text to guide quiz generation

# Flashcards
nlm flashcards create <id> --confirm
nlm flashcards create <id> --difficulty hard --confirm
nlm flashcards create <id> --difficulty medium --focus "Focus on definitions" --confirm
# Difficulty: easy, medium, hard
# Focus: optional text to guide flashcard generation

# Mind Map
nlm mindmap create <id> --confirm
nlm mindmap create <id> --title "Topic Overview" --confirm
nlm mindmap list <id>  # List existing mind maps

# Slides
nlm slides create <id> --confirm
nlm slides create <id> --format presenter --length short --confirm
# Formats: detailed, presenter | Lengths: short, default
nlm slides revise <artifact-id> --slide '1 Make the title larger' --confirm
# Creates a NEW deck with revisions. Original unchanged.

# Infographic
nlm infographic create <id> --confirm
nlm infographic create <id> --orientation portrait --detail detailed --style professional --confirm
# Orientations: landscape, portrait, square
# Detail: concise, standard, detailed
# Styles: auto_select, sketch_note, professional, bento_grid, editorial, instructional, bricks, clay, anime, kawaii, scientific

# Video
nlm video create <id> --confirm
nlm video create <id> --format brief --style whiteboard --confirm
# Formats: explainer, brief
# Styles: auto_select, classic, whiteboard, kawaii, anime, watercolor, retro_print, heritage, paper_craft

# Data Table
nlm data-table create <id> "Extract all dates and events" --confirm
# DESCRIPTION is required as second argument
```

### 6. Studio (Artifact Management)

#### MCP Tools

Use `studio_status` to check progress (or rename with `action="rename"`). Use `download_artifact` with `artifact_type` and `output_path`. Use `export_artifact` with `export_type`: docs/sheets. Delete with `studio_delete` (requires `confirm=True`).

#### CLI Commands
```bash
# Check status
nlm studio status <nb-id>                          # List all artifacts
nlm studio status <nb-id> --full                   # Show full details (including custom prompts)
nlm studio status <nb-id> --json                   # JSON output

# Download artifacts
nlm download audio <nb-id> --output podcast.mp3
nlm download video <nb-id> --output video.mp4
nlm download report <nb-id> --output report.md
nlm download slide-deck <nb-id> --output slides.pdf           # PDF (default)
nlm download slide-deck <nb-id> --output slides.pptx --format pptx  # PPTX
nlm download quiz <nb-id> --output quiz.json --format json

# Export to Google Docs/Sheets
nlm export sheets <nb-id> <artifact-id> --title "My Data Table"
nlm export docs <nb-id> <artifact-id> --title "My Report"

# Delete artifact
nlm studio delete <nb-id> <artifact-id> --confirm
```

**Status values**: `completed` (✓), `in_progress` (●), `failed` (✗)

**Prompt Extraction**: The `studio_status` tool returns a `custom_instructions` field for each artifact. This contains the original focus prompt or custom instructions used to generate that artifact (e.g., the prompt for a "Create Your Own" report, or the focus topic for an Audio Overview). This is useful for retrieving the exact prompt that generated a successful artifact.

### Renaming Resources

#### Rename a Source

**MCP Tool:** `source_rename(notebook_id, source_id, new_title)`

**CLI:**
```bash
nlm source rename <source-id> "New Title" --notebook <notebook-id>
nlm rename source <source-id> "New Title" --notebook <notebook-id>  # verb-first
```

#### Rename a Studio Artifact

#### MCP Tools

Use `studio_status` with `action="rename"`, `artifact_id`, and `new_title`.

#### CLI Commands
```bash
nlm studio rename <artifact-id> "New Title"
nlm rename studio <artifact-id> "New Title"  # verb-first alternative
```

### Server Info (Version Check)

#### MCP Tools

Use `server_info` to get version and check for updates:

```python
mcp__notebooklm-mcp__server_info()
# Returns: version, latest_version, update_available, update_command
```

#### CLI Commands
```bash
nlm --version  # Shows version and update availability
```

### 7. Chat Configuration and Notes

#### MCP Tools

Use `chat_configure` with `goal`: default/learning_guide/custom. Use `note` with `action`: create/list/update/delete. Delete requires `confirm=True`.

#### CLI Commands

> ⚠️ **AI TOOLS: DO NOT USE `nlm chat start`** - It launches an interactive REPL that cannot be controlled programmatically. Use `nlm notebook query` for one-shot Q&A instead.

For human users at a terminal:

```bash
nlm chat start <nb-id>  # Launch interactive REPL
```

**REPL Commands**:
- `/sources` - List available sources
- `/clear` - Reset conversation context
- `/help` - Show commands
- `/exit` - Exit REPL

**Configure chat behavior** (works for both REPL and query):
```bash
nlm chat configure <id> --goal default
nlm chat configure <id> --goal learning_guide
nlm chat configure <id> --goal custom --prompt "Act as a tutor..."
nlm chat configure <id> --response-length longer  # longer, default, shorter
```

**Notes management**:
```bash
nlm note create <nb-id> "Content" --title "Title"
nlm note list <nb-id>
nlm note update <nb-id> <note-id> --content "New content"
nlm note delete <nb-id> <note-id> --confirm
```

### 8. Notebook Sharing

#### MCP Tools

Use `notebook_share_status` to check, `notebook_share_public` to enable/disable public link, `notebook_share_invite` with `email` and `role`: viewer/editor.

#### CLI Commands
```bash
# Check sharing status
nlm share status <nb-id>

# Enable/disable public link
nlm share public <nb-id>          # Enable
nlm share public <nb-id> --off    # Disable

# Invite collaborator
nlm share invite <nb-id> user@example.com
nlm share invite <nb-id> user@example.com --role editor
```

### 9. Aliases (UUID Shortcuts)

Simplify long UUIDs:

```bash
nlm alias set myproject abc123-def456...  # Create alias (auto-detects type)
nlm alias get myproject                    # Resolve to UUID
nlm alias list                             # List all aliases
nlm alias delete myproject                 # Remove alias

# Use aliases anywhere
nlm notebook get myproject
nlm source list myproject
nlm audio create myproject --confirm
```

### 10. Configuration

CLI-only commands for managing settings:

```bash
nlm config show                              # Show current config
nlm config get <key>                         # Get specific setting
nlm config set <key> <value>                 # Update setting
nlm config set output.format json            # Change default output

# For switching profiles, prefer the simpler command:
nlm login switch work                        # Switch default profile
```

**Available Settings:**

| Key | Default | Description |
|-----|---------|-------------|
| `output.format` | `table` | Default output format (table, json) |
| `output.color` | `true` | Enable colored output |
| `output.short_ids` | `true` | Show shortened IDs |
| `auth.browser` | `auto` | Preferred browser for login (auto, chrome, arc, brave, edge, chromium, vivaldi, opera) |
| `auth.default_profile` | `default` | Profile to use when `--profile` not specified |

### 11. Skill Management

Manage the NotebookLM skill installation for various AI assistants:

```bash
nlm skill list                              # Show installation status
nlm skill update                            # Update all outdated skills
nlm skill update <tool>                     # Update specific skill (e.g., claude-code)
nlm skill install <tool>                    # Install skill
nlm skill uninstall <tool>                  # Uninstall skill
```

**Verb-first aliases**: `nlm update skill`, `nlm list skills`, `nlm install skill`

## Output Formats

Most list commands support multiple formats:

| Flag | Description |
|------|-------------|
| (none) | Rich table (human-readable) |
| `--json` | JSON output (for parsing) |
| `--quiet` | IDs only (for piping) |
| `--title` | "ID: Title" format |
| `--url` | "ID: URL" format (sources only) |
| `--full` | All columns/details |

### 12. Batch Operations

Perform the same action across multiple notebooks at once.

#### MCP Tools

Use `batch` with `action` parameter. Select notebooks by `notebook_names`, `tags`, or `all=True`.

```python
batch(action="query", query="What are the key findings?", notebook_names="AI Research, Dev Tools")
batch(action="add_source", source_url="https://example.com", tags="ai,research")
batch(action="create", titles="Project A, Project B, Project C")
batch(action="delete", notebook_names="Old Project", confirm=True)
batch(action="studio", artifact_type="audio", tags="research", confirm=True)
```

#### CLI Commands
```bash
nlm batch query "What are the key takeaways?" --notebooks "id1,id2"
nlm batch query "Summarize" --tags "ai,research"      # Query by tag
nlm batch query "Summarize" --all                      # Query ALL notebooks
nlm batch add-source --url "https://..." --notebooks "id1,id2"
nlm batch create "Project A, Project B, Project C"     # Create multiple
nlm batch delete --notebooks "id1,id2" --confirm       # Delete multiple
nlm batch studio --type audio --tags "research" --confirm  # Generate across notebooks
```

### 13. Cross-Notebook Query

Query multiple notebooks and get **aggregated answers with per-notebook citations**.

#### MCP Tools

```python
cross_notebook_query(query="Compare approaches", notebook_names="Notebook A, Notebook B")
cross_notebook_query(query="Summarize", tags="ai,research")
cross_notebook_query(query="Everything", all=True)
```

#### CLI Commands
```bash
nlm cross query "What features are discussed?" --notebooks "id1,id2"
nlm cross query "Compare approaches" --tags "ai,research"
nlm cross query "Summarize everything" --all
```

### 14. Pipelines

Define and execute multi-step notebook workflows. Three built-in pipelines plus support for custom YAML pipelines.

#### MCP Tools

```python
pipeline(action="list")  # List available pipelines
pipeline(action="run", notebook_id="...", pipeline_name="ingest-and-podcast", input_url="https://...")
```

#### CLI Commands
```bash
nlm pipeline list                                         # List available pipelines
nlm pipeline run <notebook> ingest-and-podcast --url "https://..."
nlm pipeline run <notebook> research-and-report --url "https://..."
nlm pipeline run <notebook> multi-format                  # Audio + report + flashcards
```

**Built-in pipelines:** `ingest-and-podcast`, `research-and-report`, `multi-format`

Create custom pipelines: add YAML files to `~/.notebooklm-mcp-cli/pipelines/`

### 15. Tags & Smart Select

Tag notebooks for organization and use tags to target batch operations.

#### MCP Tools

```python
tag(action="add", notebook_id="...", tags="ai,research,llm")
tag(action="remove", notebook_id="...", tags="ai")
tag(action="list")                           # List all tagged notebooks
tag(action="select", query="ai research")    # Find notebooks by tag match
```

#### CLI Commands
```bash
nlm tag add <notebook> --tags "ai,research,llm"           # Add tags
nlm tag add <notebook> --tags "ai" --title "My Notebook"  # With display title
nlm tag remove <notebook> --tags "ai"                     # Remove tags
nlm tag list                                              # List all tagged notebooks
nlm tag select "ai research"                              # Find notebooks by tag match
```

## Common Patterns

### Pattern 1: Research → Podcast Pipeline

```bash
nlm notebook create "AI Research 2026"   # Capture ID
nlm alias set ai <notebook-id>
nlm research start "agentic AI trends" --notebook-id ai --mode deep
nlm research status ai --max-wait 300    # Wait up to 5 min
nlm research import ai <task-id>         # Import all sources
nlm audio create ai --format deep_dive --confirm
nlm studio status ai                     # Check generation progress
```

### Pattern 2: Quick Content Ingestion

```bash
nlm source add <id> --url "https://example1.com"
nlm source add <id> --url "https://example2.com"
nlm source add <id> --text "My notes..." --title "Notes"
nlm source list <id>
```

### Pattern 3: Study Materials Generation

```bash
nlm report create <id> --format "Study Guide" --confirm
nlm quiz create <id> --count 10 --difficulty 3 --focus "Exam prep" --confirm
nlm flashcards create <id> --difficulty medium --focus "Core terms" --confirm
```

### Pattern 4: Drive Document Workflow

```bash
nlm source add <id> --drive 1KQH3eW0hMBp7WK... --type slides
# ... time passes, document is edited ...
nlm source stale <id>                    # Check freshness
nlm source sync <id> --confirm           # Sync if stale
```

### Pattern 5: Batch & Cross-Notebook Workflow

```bash
# Tag notebooks for organization
nlm tag add <id1> --tags "ai,research"
nlm tag add <id2> --tags "ai,product"

# Query across tagged notebooks
nlm cross query "What are the main conclusions?" --tags "ai"

# Batch generate podcasts for all tagged notebooks
nlm batch studio --type audio --tags "ai" --confirm

# Run a pipeline on a single notebook
nlm pipeline run <id> ingest-and-podcast --url "https://example.com"
```

## Error Recovery

| Error | Cause | Solution |
|-------|-------|----------|
| "Cookies have expired" | Session timeout | `nlm login` |
| "authentication may have expired" | Session timeout | `nlm login` |
| "Notebook not found" | Invalid ID | `nlm notebook list` |
| "Source not found" | Invalid ID | `nlm source list <nb-id>` |
| "Rate limit exceeded" | Too many calls | Wait 30s, retry |
| "Research already in progress" | Pending research | Use `--force` or import first |
| "Import timed out" | Too many sources | Use `--timeout 600` for larger notebooks |
| "Google API error code 3" | Transient deep research error | Retry in a few minutes, or use `--mode fast` |
| Browser doesn't launch | Port conflict | Close browser, retry |

## Rate Limiting

Wait between operations to avoid rate limits:
- Source operations: 2 seconds
- Content generation: 5 seconds
- Research operations: 2 seconds
- Query operations: 2 seconds

## Advanced Reference

For detailed information, see:
- **[references/command_reference.md](references/command_reference.md)**: Complete command signatures
- **[references/troubleshooting.md](references/troubleshooting.md)**: Detailed error handling
- **[references/workflows.md](references/workflows.md)**: End-to-end task sequences
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