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Agent Skill · 开发

notebooklm-content-creation(NotebookLM 内容 creation)

用于辅助文档、README、Markdown、说明文和内容稿件的整理与改写。它适合让 Agent 提炼结构、补齐章节、统一术语、检查链接或把零散材料整理成可读文档。使用时应保留项目已有事实、命令和路径,不要把未确认的信息写成确定结论;涉及对外文案时,还需要控制语气,避免过度营销或夸大能力。

notebooklm-content-creation 是开发类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为调用外部服务;许可证为 MIT-0,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 6,494。

总安装 4,633周安装 199GitHub Stars 1下载 1,624核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:notebooklm-content-creation(NotebookLM 内容 creation)
来源仓库:https://github.com/skywalker-lili/notebooklm-content-creation
安装命令:
openclaw skills install notebooklm-content-creation
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install notebooklm-content-creation

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

创建和管理 NotebookLM Studio 内容的生产工具。支持音频概述、信息图表和幻灯片生成。监控内容创建进度并输出结构化结果。notebooklm-content-creation 属于开发类 Skill,可作为该场景下的辅助能力补充。依赖 notebooklm-mcp-cli 运行环境。

输出前应核对事实准确性,避免虚构信息。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install notebooklm-content-creation;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

notebooklm-content-creation 怎么安装?

在终端执行 openclaw skills install notebooklm-content-creation。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

notebooklm-content-creation 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

notebooklm-content-creation 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

notebooklm-content-creation 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

notebooklm-content-creation 用的人多吗?

公开数据是累计安装 4,633 次,近一周安装 199 次,下载 1,624 次,GitHub 1 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

notebooklm-content-creation 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
notebooklm-content-creation

NotebookLM 内容 creation · 本页

4,6331调用外部服务MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
notebooklm-content-creation
description
Create and monitor NotebookLM Studio content — Audio Overview, Video Overview, Infographics, and Slides — via the notebooklm-mcp-cli. Use when user wants to generate a podcast, video, infographic, or slide deck from a NotebookLM notebook. Triggers on: create audio, create video, create infographic, create slides, generate podcast from notebook, make a video overview, notebooklm studio create, download notebook audio, notebooklm content creation. Requires notebooklm-mcp-cli installed and authenticated.

NotebookLM Content Creation

Creates NotebookLM Studio content (Audio Overview, Video Overview, Infographics, Slides) and monitors it to completion using a background polling loop.

Requires:

  • notebooklm-mcp-cli installed: uv tool install notebooklm-mcp-cli
  • Authenticated: nlm login (done on the server already)

Studio Types

TypeCommandFormatsLengths
Audio Overviewnlm audio createdeep_dive, brief, critique, debateshort, default, long
Video Overviewnlm studio create --type videodeep_dive, brief, critique, debateshort, default, long
Infographicsnlm studio create --type infographic(default)—
Slidesnlm studio create --type slidesdeep_dive—

Workflow

Step 1 — Notebook Selection

List all notebooks:

nlm notebook list

Parse the JSON output for id and title. Match against the user's keyword (case-insensitive substring match). If multiple match, present options with numbers.

If no notebook matches:

  • Ask user: "No notebook found matching '[keyword]'. Create a new one or add more sources to an existing notebook?"
  • If user confirms new notebook: create with nlm notebook create "<name>"
  • Then add sources: nlm source add <notebook_id> --url <url> --wait

Step 2 — Check Existing Artifacts

Before creating new content, check if the notebook already has generated artifacts:

nlm studio status <notebook_id>

If artifacts with status: completed exist, show them to the user and ask:

"This notebook already has completed content. Download existing [type] or generate new content?"
  • Download existing: go directly to download step
  • Generate new: proceed to Step 3

Step 3 — Pre-Flight Confirmation (One Message, All Parameters)

Ask all parameters at once. Write in the user's current session language.

Creating [Audio/Video/Infographic/Slides] Overview from "[notebook name]"

Please confirm:

① Content type: [Audio Overview / Video Overview / Infographics / Slides]
② Format: [deep_dive / brief] (default: deep_dive)
③ Length: [short / default / long] (default: default) — not available for Infographics/Slides
④ Language: [BCP-47 code, e.g., en, zh-CN] (default: notebook's detected language or en)
⑤ Output path: [path] (default: ~/ObsidianVault/Default/NotebookLM/<notebook-name>/)

Reply with any changes, or "ok" to proceed with defaults.

Step 4 — Create Content

Based on user's confirmed parameters:

Audio or Video:

nlm [audio|studio] create <notebook_id> --[format] --[length] --language <lang> --confirm

Capture the returned Artifact ID.

Infographics or Slides:

nlm studio create <notebook_id> --type [infographic|slides] --confirm

Capture the returned Artifact ID.

Step 5 — Set Up Task Directory

Create a temp directory following the polling best practices pattern:

/tmp/notebooklm-studio/
  <YYMMDD-HHmm>_<sanitized-notebook-name>_<studio-type>/
    task.json          ← full task metadata
    progress.json      ← poll count, artifact id, last status
    poll.log           ← each poll attempt
    error.log          ← errors
    done.flag          ← created on success
    <output file>      ← downloaded artifact

Write task.json:

{
  "notebook_id": "<id>",
  "notebook_name": "<name>",
  "artifact_id": "<id>",
  "studio_type": "audio",
  "output_path": "~/ObsidianVault/Default/NotebookLM/<notebook-name>/<output_filename>",
  "poll_interval_seconds": 300,
  "max_polls": 8,
  "created_at": "<ISO timestamp>"
}

Step 6 — Notify User and Launch Background Polling

Notify the user (in current session language):

"Content generation started. I'll monitor it in the background and notify you when it's ready (typically 2–5 minutes). Poll every 5 minutes, max 40 minutes."

Launch the polling script in the background:

cd /tmp/notebooklm-studio/<task-dir>/
nohup bash /tmp/notebooklm-studio/poll.sh > /dev/null 2>&1 &

Step 7 — Polling Script

Write this script to <task-dir>/poll.sh:

#!/bin/bash
set -euo pipefail

TASK_DIR="/tmp/notebooklm-studio/<task-dir>"
cd "$TASK_DIR"

[[ -f done.flag ]] && echo "Already done." && exit 0

POLL_COUNT=$(grep '"poll_count"' progress.json 2>/dev/null | sed 's/[^0-9]//g') || POLL_COUNT=0
MAX_POLLS=8
INTERVAL=300

log() { echo "[$(date '+%Y-%m-%d %H:%M:%S')] $*" | tee -a poll.log; }

while true; do
  POLL_COUNT=$((POLL_COUNT + 1))

  if [[ $POLL_COUNT -gt $MAX_POLLS ]]; then
    log "TIMEOUT after $MAX_POLLS polls"
    echo "Timeout" >> error.log
    exit 1
  fi

  log "[Poll $POLL_COUNT/$MAX_POLLS] Checking status..."
  RESULT=$(nlm studio status "$(grep '"notebook_id"' task.json | sed 's/.*: *"\([^"]*\)".*/\1/') 2>&1) || true
  echo "$RESULT" >> poll.log

  # Check if our artifact is completed
  ARTIFACT_STATUS=$(echo "$RESULT" | grep -A5 "\"id\": \"$(grep '"artifact_id"' task.json | sed 's/.*: *"\([^"]*\)".*/\1/')\"" | grep '"status"' | sed 's/.*: *"\([^"]*\)".*/\1/' | head -1)
  log "Artifact status: '$ARTIFACT_STATUS'"

  if [[ "$ARTIFACT_STATUS" == "completed" ]]; then
    log "Completed. Downloading..."
    OUTPUT_PATH=$(grep '"output_path"' task.json | sed 's/.*: *"\([^"]*\)".*/\1/')
    nlm download audio "$(grep '"notebook_id"' task.json | sed 's/.*: *"\([^"]*\)".*/\1/')" --id "$(grep '"artifact_id"' task.json | sed 's/.*: *"\([^"]*\)".*/\1/')" -o "$OUTPUT_PATH" >> poll.log 2>&1 || true
    if [[ -s "$OUTPUT_PATH" ]]; then
      log "Downloaded: $OUTPUT_PATH ($(du -h "$OUTPUT_PATH" | cut -f1))"
      touch done.flag
    else
      log "Downloaded file is empty"
      echo "Empty output" >> error.log
    fi
    exit 0
  fi

  if [[ "$ARTIFACT_STATUS" == "failed" ]]; then
    log "Generation failed"
    echo "Failed" >> error.log
    exit 1
  fi

  # Save progress
  sed -i "s/\"poll_count\": [0-9]*/\"poll_count\": $POLL_COUNT/" progress.json
  log "Still in_progress. Sleeping ${INTERVAL}s..."
  sleep "$INTERVAL"
done

Initialize progress.json:

{
  "poll_count": 0,
  "last_poll_at": null,
  "last_poll_result": null
}

Step 8 — Completion

When polling exits (success or failure):

On success:

  • Verify file exists and has content
  • Move file to confirmed output path if not already there
  • Notify user in current session language:

> "✅ [Content type] ready!\ \ Notebook: [name]\ Saved to: [path]\ Size: [size]\ Polls: [N] (~[X] minutes)"

  • Leave temp folder for manual inspection

On failure/timeout:

  • Notify user:

> "❌ [Content type] generation did not complete.\ \ Notebook: [name]\ Reason: [timeout / auth error / generation failed]\ \ Options:\

  1. Re-run with same parameters\
  2. Check NotebookLM web UI manually\
  3. Clean up temp folder"
  • Do NOT auto-retry or delete temp folder

Quick Reference

# List notebooks
nlm notebook list

# Check status
nlm studio status <notebook_id>

# Create audio
nlm audio create <notebook_id> --format deep_dive --length default --confirm

# Create video
nlm studio create <notebook_id> --type video --format brief --confirm

# Create infographic
nlm studio create <notebook_id> --type infographic --confirm

# Create slides
nlm studio create <notebook_id> --type slides --confirm

# Download (after getting artifact ID)
nlm download [audio|video|infographic|slides] <notebook_id> --id <artifact_id> -o <path>

平台分布

OpenClaw

71.69%
按下载量换算1,164

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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