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youtube-archiverYouTube 存档器

Agent Skill

youtube-archiver 用于整理文档、README、Markdown 和说明材料,适合在 OpenClaw 中需要把零散信息整理成结构清晰的文档时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

10,234

周安装

410

GitHub Stars

1

下载量

3,313
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:youtube-archiver(YouTube 存档器)
来源仓库:https://github.com/benmillerat/youtube-archiver
安装命令:
openclaw skills install youtube-archiver
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 youtube-archiver

简介

youtube-archiver 将播放列表存档为 Markdown 笔记,包含元数据、文字记录与 AI 摘要。

  • 适合在 OpenClaw 中建立知识库、同步学习资源或归档视听材料时使用。
  • 自动打标签与结构化存储,便于后续检索与回顾。
  • 安装命令:openclaw skills install youtube-archiver;需播放列表 ID 或链接。
  • 注意存储空间管理,定期清理冗余条目以免占用过多资源。

SKILL.md

name
youtube-archiver
description
Archive YouTube playlists into markdown notes with metadata, transcripts, AI summaries, and tags. Use when a user asks to import/sync YouTube playlists, archive Watch Later or Liked videos, enrich YouTube notes, batch process video notes, or automate recurring YouTube-to-markdown sync jobs with cron.

YouTube Archiver

Use this skill to import YouTube playlists into markdown files and optionally enrich notes with transcript, summary, and tagging.

Requirements

  • Python 3.7+
  • yt-dlp (pip install yt-dlp or brew install yt-dlp)
  • A browser signed into YouTube (for private playlists like Liked/Watch Later)
  • macOS: terminal needs Full Disk Access to read browser cookies
  • Windows: browser cookie extraction can be flaky; cookies_file export is the safer path
  • Linux: works on desktop installs; headless servers need cookies_file

First-run setup flow (interactive)

If no config exists at <output>/.config.json, ask these questions before running scripts.

Required questions

  1. Where should archived notes be stored?

- Default: ./YouTube-Archive

  1. Which playlists should be archived?

- Accept playlist IDs or URLs - Default: LL (Liked Videos), WL (Watch Later)

  1. Which browser is signed into YouTube for cookie auth?

- Default: chrome

Optional enrichment questions

Ask only if the user wants summaries/tags.

  1. Generate AI summaries? (yes/no)
  2. Summary provider? (openai, gemini, anthropic, openrouter, ollama, none)
  3. Summary model name?
  4. API key env var name?
  5. Enable auto-tagging? (yes/no)
  6. Tagging provider/model/env var?
  7. Keep default tags or define custom vocabulary?

First-run execution sequence

  1. Run init:

- python3 <skill>/scripts/yt-import.py --output <output-dir> --init

  1. Edit <output-dir>/.config.json from the user’s answers.
  2. Verify auth with dry run:

- python3 <skill>/scripts/yt-import.py --output <output-dir> --dry-run

  1. Run real import.
  2. Run enrichment (optional):

- python3 <skill>/scripts/yt-enrich.py --output <output-dir> --limit 10

One-shot quick start

Use this for immediate manual sync:

python3 <skill>/scripts/yt-import.py --output <output-dir>
python3 <skill>/scripts/yt-enrich.py --output <output-dir> --limit 10

Useful import flags:

  • --dry-run
  • --playlist <ID> (repeatable)
  • --no-summary
  • --no-tags
  • --cookies <path/to/cookies.txt>
  • --browser <name>

Useful enrich flags:

  • --dry-run
  • --limit <N>
  • --strict-config

Idempotency and safety behavior

  • Import skips already archived videos by video_id.
  • Filenames include video ID: Title [video_id].md.
  • Enrichment skips notes where frontmatter has enriched: true.
  • Lockfile prevents concurrent runs: <output-dir>/.yt-archiver.lock.

Automation with cron (single-agent default)

Offer cron only after one successful manual run.

Example schedule (daily 11:00):

  1. Import new videos
  2. Enrich a bounded batch

Example task text:

  • Run yt-import.py for <output-dir>, then run yt-enrich.py --limit 10 for the same output.

Keep it single-agent by default. Do not assume multi-agent routing.

Troubleshooting and provider details

Read these references when needed:

  • Provider setup, model suggestions, cost: references/providers.md
  • Common failures and fixes: references/troubleshooting.md
  • Default summary prompt template: references/default-summary-prompt.md

适合场景

01

调用多模型

02

代码和文本生成

03

Agent 推理流程

04

OpenRouter 模型接入

能力概览

能力 1

统一调用多种 LLM

能力 2

支持 Claude、Gemini、Kimi 等模型

能力 3

适合聊天、代码和推理任务

能力 4

可作为 Agent 模型调用入口

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

83.16%
按下载量换算2,755

安全审计

ClawScan

通过

Static analysis

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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