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youtube-catchupYouTube 追赶

Agent Skill

youtube-catchup 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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

275

周安装

11

GitHub Stars

42

下载量

89
CodexClaudeCursorGemini CLI

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

unknown

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-catchup(YouTube 追赶)
来源仓库:https://github.com/taylorhuston/local-life-manager
仓库路径:skills/youtube-catchup
安装命令:
npx skills add https://github.com/taylorhuston/local-life-manager --skill youtube-catchup
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/taylorhuston/local-life-manager --skill youtube-catchup

简介

用于查找、检索和筛选相关信息。

  • 适合根据关键词或任务场景快速定位候选结果。
  • 可结合来源仓库和 README 核验具体用法。
  • 安装命令:npx skills add https://github.com/taylorhuston/local-life-manager --skill youtube-catchup。
  • 安装前建议确认权限范围和维护状态。

SKILL.md

Catch up on YouTube channels by auto-summarizing new videos.

Architecture

This skill uses a coordinator + subagent pattern:

  • Coordinator (Sonnet): Fetches video lists, filters new videos, spawns summarization agents, updates state
  • Summarizer (Haiku subagents): Each video gets its own agent with fresh context to ensure quality

Prerequisites

Requires yt-dlp:

pip install yt-dlp

Helper Script

Use scripts/youtube_helper.py for fetching data:

# Get NEW videos uploaded since a date (default operation)
python3 scripts/youtube_helper.py new @handle YYYY-MM-DD [processed_ids]

# Backfill: get all unprocessed videos regardless of date (explicit request only)
python3 scripts/youtube_helper.py backfill @handle [limit] [processed_ids]

# Fast channel list (no date info - rarely needed)
python3 scripts/youtube_helper.py channel @handle [limit]

# Get video metadata
python3 scripts/youtube_helper.py video VIDEO_ID

# Get transcript only
python3 scripts/youtube_helper.py transcript VIDEO_ID

# Get metadata + transcript (for summarization)
python3 scripts/youtube_helper.py full VIDEO_ID

Important: The new command checks upload dates to avoid backfilling old content. Use backfill only when explicitly requested.

Workflow

Phase 1: Discovery (Coordinator)

  1. Load configuration

- Read channel list from references/channels.json - Read processed videos list from references/state.json - Note the last_run date for filtering

  1. For each enabled channel:

- Run: python3 scripts/youtube_helper.py new @handle {last_run} {processed_ids} - This returns ONLY videos uploaded since last_run that aren't in processed list - Skip videos under 5 minutes (likely promotional/announcement fluff) - Collect list of new videos needing summarization

  1. Deduplicate against existing notes:

- Before processing, check if a note with that video URL already exists: grep -rl "youtube.com/watch?v={video_id}" "my-vault/07 Knowledge Base/Capture/Videos/" - If a note exists: skip that video (already processed, just missing from state) - This prevents duplicates even if state.json is out of sync

  1. Report findings to user:

- Show count of new videos per channel - Ask user how to proceed (all, select channels, limit count)

Backfill mode: If user explicitly requests backfilling old videos, use backfill command instead of new.

Phase 2: Summarization (Haiku Subagents)

  1. Spawn subagents for summarization:

- Use Task tool with model: haiku and subagent_type: general-purpose - Process 4-6 videos in parallel (multiple Task calls in single message) - Each subagent handles ONE video with fresh context - Wait for batch to complete before starting next batch

  1. Subagent prompt template:
Summarize this YouTube video and create a note.

VIDEO_ID: {video_id}
CHANNEL: {channel_name}
TAGS: {tags}
OUTPUT_PATH: {output_path}

IMPORTANT: Use the OUTPUT_PATH exactly as given with literal spaces (e.g., "my-vault/07 Knowledge Base/...").
Do NOT escape spaces with backslashes - this creates directories with literal backslash characters in the name.

STEPS:
1. Run: cd /home/taylor/my-life/.claude/skills/youtube-catchup && python3 scripts/youtube_helper.py full {video_id}
2. If NO_TRANSCRIPT_AVAILABLE, create note with that notice (see format below)
3. Otherwise, summarize the transcript into detailed bullet points
4. Identify any discoveries (tools, products, frameworks worth exploring)
5. Write the note file to the output path
6. Return: SUCCESS or FAILURE with brief reason

SUMMARY GUIDELINES:
- 5-15 bullet points depending on video length/density
- Each bullet should capture a complete idea with specific details
- Include names, numbers, tools, key arguments mentioned
- For tutorials: use step-by-step format with code snippets

NO TRANSCRIPT FORMAT:
## Summary

NO TRANSCRIPT AVAILABLE - REWATCH VIDEO TO CREATE PROPER SUMMARY

- Main topic: {title}

NOTE TEMPLATE:
---
class: Video
aliases:
tags: {tags}
lastReviewedDate:
reviewFrequency:
review:
created: {date}
modified: {date}
media: https://www.youtube.com/watch?v={video_id}
publishDate: {publish_date}
status: Summarized
duration: {duration}
cssclasses:
archived:
---
Related:

## Summary

- Main topic: [one sentence]
- [Key points with specific details...]

## Discoveries

- [[Product Name]] - brief context
- (or "None")

## Why Watch?

[One sentence on whether worth actually watching]

Phase 3: Completion (Coordinator)

  1. Collect results:

- Track which videos succeeded/failed - Report any failures to user

  1. Update state:

- Add successfully processed video IDs to references/state.json - Report summary of what was processed

Tagging

Use tags from the canonical list in my-vault/09 System/Tag Index.md.

Each channel in references/channels.json has a tags array specifying default tags. Format: tags: ["tag1", "tag2"]

Output Paths

Video notes: my-vault/07 Knowledge Base/Capture/Videos/{channel_folder}/{title}.md Discovery notes: my-vault/01 Inbox/{name}.md

CRITICAL - Path Handling:

  • NEVER escape spaces with backslashes in paths passed to subagents or the Write tool
  • Use paths exactly as shown: my-vault/07 Knowledge Base/... (with literal spaces)
  • The Write tool handles spaces correctly - backslash escaping creates literal \ characters in directory names
  • When using Bash commands, wrap paths in double quotes: "my-vault/07 Knowledge Base/..."

Channel Config

Edit references/channels.json:

{
  "channels": [
    {
      "name": "Channel Name",
      "handle": "@YouTubeHandle",
      "folder": "Folder Name",
      "tags": ["tag1", "tag2"],
      "priority": "high",
      "enabled": true
    }
  ]
}

Tutorial Videos - Special Handling

If the video is a tutorial, the subagent should use step-by-step format:

## Summary

Tutorial: [What you'll build/learn]

### Prerequisites
- Required software/tools
- Prior knowledge needed

### Steps

#### 1. [First major step]
- Specific action
- Code snippet if applicable
- Expected result

#### 2. [Continue for all steps...]

### Final Result
- What you should have
- How to verify it works

### Troubleshooting
- Common issues and solutions

Tutorial goals: Someone should be able to follow WITHOUT watching the video.

Discovery Notes

Subagents should identify products, services, frameworks, tools worth exploring.

Create notes for: New tools, interesting frameworks, notable projects Skip: Well-known things (Python, AWS, React), generic concepts

Discovery note format:

---
class: Note
tags: ["tag1"]
---
Related: [[Video Title]]

## What is it?
[One sentence description]

## Why look into it?
[Why it seemed interesting]

## Links
- [URL if mentioned]

Error Handling

  • If subagent fails, log the video ID and continue with others
  • If transcript unavailable, create note with NO TRANSCRIPT notice
  • Report all failures at the end for manual review

Example Coordinator Flow

1. Load channels.json, state.json (last_run: 2026-01-16)
2. Fetch NEW videos (uploaded since last_run):
   python3 youtube_helper.py new @t3dotgg 2026-01-16 id1,id2,...
   - Theo: 2 new videos
   - HealthyGamerGG: 1 new video
   - LangChain: 0 new videos
3. User confirms: "Process all"
4. Batch 1 - spawn 3 Haiku agents:
   - Task(video_1, theo, ...)
   - Task(video_2, theo, ...)
   - Task(video_3, healthygamer, ...)
5. Wait for batch completion
6. Update state.json with successful IDs
7. Update last_run to today's date
8. Report: "Processed 3 videos, 0 failures"

For explicit backfill:

User: "backfill Gamers Nexus videos"
1. Use: python3 youtube_helper.py backfill @GamersNexus 50 id1,id2,...
2. This returns ALL unprocessed videos regardless of upload date
3. Proceed with normal summarization workflow

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

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

Codex

34.89%
按下载量换算31

Claude

32.38%
按下载量换算29

Cursor

19.87%
按下载量换算18

Gemini CLI

10.21%
按下载量换算9

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/taylorhuston/local-life-manager --skill youtube-catchup 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。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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