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openakita%2fskills%40youtube-summarizer(openakita%2fskills%40youtube 摘要)

openakita%2fskills%40youtube-summarizer 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。

openakita%2fskills%40youtube-summarizer 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,暂无第三方扫描结果,按安装量在研究检索类的 73,674 个 Skill 里排第 59,803。

总安装 376周安装 16GitHub Stars 1,672下载 132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
unknown

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:openakita%2fskills%40youtube-summarizer(openakita%2fskills%40youtube 摘要)
来源仓库:https://github.com/openakita/openakita
仓库路径:skills/openakita%2Fskills%40youtube-summarizer
安装命令:
npx skills add https://github.com/openakita/openakita --skill openakita/skills@youtube-summarizer
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/openakita/openakita --skill openakita/skills@youtube-summarizer

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选相关信息。适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词快速定位候选结果。通过 npx skills add 命令从 GitHub 安装使用。安装前需确认权限范围和维护状态,注意是否触发联网或文件读写。

openakita%2fskills%40youtube-summarizer 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/openakita%2Fskills%40youtube-summarizer

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 Codex、Claude、Cursor、Gemini CLI;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 npx skills add https://github.com/openakita/openakita --skill openakita/skills@y…;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

    它需要需要联网,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

openakita%2fskills%40youtube-summarizer 怎么安装?

在终端执行 npx skills add https://github.com/openakita/openakita --skill openakita/skills@youtube-sum…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

openakita%2fskills%40youtube-summarizer 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。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。

openakita%2fskills%40youtube-summarizer 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

openakita%2fskills%40youtube-summarizer 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

openakita%2fskills%40youtube-summarizer 用的人多吗?

公开数据是累计安装 376 次,近一周安装 16 次,下载 132 次,GitHub 1,672 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。

openakita%2fskills%40youtube-summarizer 安全吗?

没有查到第三方扫描结果,安全性无法从公开资料判断,安装前请自行审查源码、依赖和命令行为。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 来源仓库有 1,672 星,维护活跃度相对可查。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 没有第三方扫描结果,安全性只能靠自己读源码判断。
  • 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 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 要求有安全扫描结论才肯安装的团队。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
openakita%2fskills%40youtube-summarizer

openakita%2fskills%40youtube 摘要 · 本页

3761,672需要联网未明确未收录

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

YouTube Video Summarizer

Extract transcripts from YouTube videos and generate structured, actionable summaries using the STAR + R-I-S-E framework.

When to Use This Skill

  • User shares a YouTube link and asks "summarize this" or "what's this video about"
  • User wants key takeaways or study notes from a lecture/talk
  • User needs timestamped highlights from a long video
  • User wants a structured breakdown of a tutorial or presentation
  • User asks to compare content across multiple YouTube videos
  • User wants to extract quotes or specific segments from a video

Prerequisites

Install Required Package

pip install youtube-transcript-api

If pip is not available, try:

pip3 install youtube-transcript-api

Verify installation:

from youtube_transcript_api import YouTubeTranscriptApi
print("youtube-transcript-api is ready")

Supported Python Versions

  • Python 3.8+
  • No additional system dependencies required

Instructions

Step 1: Extract the Video ID

YouTube URLs come in many formats. Parse all of them to extract the 11-character video ID:

URL FormatExampleExtraction
Standardhttps://www.youtube.com/watch?v=dQw4w9WgXcQQuery param v
Shorthttps://youtu.be/dQw4w9WgXcQPath segment
Embedhttps://www.youtube.com/embed/dQw4w9WgXcQPath after /embed/
Livehttps://www.youtube.com/live/dQw4w9WgXcQPath after /live/
Shortshttps://www.youtube.com/shorts/dQw4w9WgXcQPath after /shorts/
With timestamphttps://youtu.be/dQw4w9WgXcQ?t=120Ignore query params
With playlisthttps://www.youtube.com/watch?v=dQw4w9WgXcQ&list=PLxxUse only v param
Mobilehttps://m.youtube.com/watch?v=dQw4w9WgXcQSame as standard
Bare IDdQw4w9WgXcQUse directly
import re
from urllib.parse import urlparse, parse_qs

def extract_video_id(url_or_id: str) -> str:
    """Extract YouTube video ID from various URL formats."""
    url_or_id = url_or_id.strip()

    # Bare video ID (11 chars, alphanumeric + dash + underscore)
    if re.match(r'^[A-Za-z0-9_-]{11}$', url_or_id):
        return url_or_id

    parsed = urlparse(url_or_id)

    # youtu.be short links
    if parsed.hostname in ('youtu.be',):
        return parsed.path.lstrip('/')

    # Standard, mobile, embed, live, shorts
    if parsed.hostname in ('www.youtube.com', 'youtube.com', 'm.youtube.com'):
        if parsed.path == '/watch':
            qs = parse_qs(parsed.query)
            return qs.get('v', [None])[0]
        for prefix in ('/embed/', '/live/', '/shorts/', '/v/'):
            if parsed.path.startswith(prefix):
                return parsed.path[len(prefix):].split('/')[0]

    raise ValueError(f"Cannot extract video ID from: {url_or_id}")

Step 2: Fetch the Transcript

from youtube_transcript_api import YouTubeTranscriptApi

def fetch_transcript(video_id: str, preferred_langs=None):
    """
    Fetch transcript with language fallback.

    Args:
        video_id: The 11-character YouTube video ID
        preferred_langs: Ordered list of language codes, e.g. ['zh-Hans', 'zh', 'en']
                        Defaults to ['en'] if not specified

    Returns:
        List of transcript segments with 'text', 'start', 'duration' keys
    """
    if preferred_langs is None:
        preferred_langs = ['en']

    try:
        transcript_list = YouTubeTranscriptApi.list_transcripts(video_id)

        # Try manually created transcripts first (more accurate)
        for lang in preferred_langs:
            try:
                transcript = transcript_list.find_manually_created_transcript([lang])
                return transcript.fetch()
            except Exception:
                continue

        # Fall back to auto-generated transcripts
        for lang in preferred_langs:
            try:
                transcript = transcript_list.find_generated_transcript([lang])
                return transcript.fetch()
            except Exception:
                continue

        # Last resort: get any available transcript and translate
        for transcript in transcript_list:
            try:
                if 'en' in preferred_langs:
                    return transcript.translate('en').fetch()
                return transcript.fetch()
            except Exception:
                continue

        raise RuntimeError("No transcript available in any language")

    except Exception as e:
        raise RuntimeError(f"Failed to fetch transcript for {video_id}: {e}")

Step 3: Generate the Summary

Use the STAR + R-I-S-E combined framework for maximum clarity:

STAR Framework (for factual/process content)
  • Situation — What context does the video establish?
  • Task — What problem or question is being addressed?
  • Action — What steps, methods, or arguments are presented?
  • Result — What conclusions, outcomes, or calls to action are given?
R-I-S-E Framework (for opinion/analysis content)
  • Reference — What sources, data, or authorities are cited?
  • Insight — What unique perspectives or non-obvious points are made?
  • Summary — What are the essential takeaways?
  • Evaluation — What are the strengths and weaknesses of the arguments?

Prompt Template for Summary Generation

When generating the summary from the transcript, use this structure:

You are summarizing a YouTube video transcript. Follow these rules strictly:

1. TITLE & METADATA
   - Video title (if known)
   - Estimated duration from timestamps
   - Primary topic/category

2. EXECUTIVE SUMMARY (2-3 sentences)
   - The single most important takeaway
   - Who should watch this and why

3. KEY POINTS (bulleted, with timestamps)
   - [MM:SS] Point description
   - Maximum 10 key points
   - Each point should be self-contained and actionable

4. DETAILED NOTES (organized by topic/section)
   - Group related content under headers
   - Include specific examples, numbers, quotes
   - Preserve technical accuracy

5. STAR ANALYSIS
   - Situation: ...
   - Task: ...
   - Action: ...
   - Result: ...

6. ACTIONABLE TAKEAWAYS
   - What the viewer should do after watching
   - Resources mentioned in the video

Workflows

Workflow 1: Quick Summary

User says: "Summarize this video: https://youtube.com/watch?v=..."

  1. Extract video ID from URL
  2. Fetch English transcript (fall back to auto-generated)
  3. Generate executive summary + key points with timestamps
  4. Present in clean markdown format

Workflow 2: Deep Dive Notes

User says: "I need detailed study notes from this lecture"

  1. Extract video ID
  2. Fetch transcript in preferred language
  3. Generate full STAR + R-I-S-E analysis
  4. Include all timestamps, quotes, and specific data points
  5. Add a "Review Questions" section at the end

Workflow 3: Multi-Language Summary

User says: "Summarize this Chinese/Japanese/Korean video in English"

  1. Extract video ID
  2. List available transcript languages
  3. Fetch best available transcript
  4. Translate content if needed (use transcript API's built-in translation)
  5. Generate summary in the user's preferred language

Workflow 4: Batch Processing

User provides multiple URLs:

  1. Extract all video IDs
  2. Fetch transcripts sequentially (respect rate limits)
  3. Generate individual summaries
  4. Create a comparison table if videos are related
  5. Highlight common themes and unique points

Workflow 5: Timestamp Navigation

User says: "Find where they talk about X in this video"

  1. Fetch full transcript
  2. Search for relevant keywords/concepts
  3. Return matching segments with precise timestamps
  4. Format as clickable timestamp links: [MM:SS](https://youtu.be/ID?t=SECONDS)

Output Format

Standard Summary Output

# 📺 Video Summary: [Title]

**Duration**: ~XX minutes | **Language**: English | **Category**: Technology

## Executive Summary
[2-3 sentence overview]

## Key Points
- **[0:00]** Introduction and context setting
- **[2:15]** First major point with supporting evidence
- **[8:30]** Key technical concept explained
- **[15:00]** Practical demonstration
- **[22:45]** Conclusion and call to action

## Detailed Notes

### Section 1: [Topic] (0:00 - 5:30)
[Detailed notes with specific information]

### Section 2: [Topic] (5:30 - 12:00)
[Detailed notes with specific information]

## STAR Analysis
- **Situation**: [Context]
- **Task**: [Problem/Question]
- **Action**: [Methods/Steps]
- **Result**: [Outcomes/Conclusions]

## Actionable Takeaways
1. [First action item]
2. [Second action item]
3. [Third action item]

## Resources Mentioned
- [Resource 1](url)
- [Resource 2](url)

Common Pitfalls

1. Transcript Unavailable

Problem: Some videos have no transcript (auto-generated or manual).

Solutions:

  • Check if the video is a music video, live stream, or very short clip — these often lack transcripts
  • Try different language codes: ['en', 'en-US', 'en-GB']
  • If auto-generated is disabled by the uploader, there's no workaround via this API

Error handling:

try:
    transcript = fetch_transcript(video_id)
except RuntimeError as e:
    if "disabled" in str(e).lower():
        print("Subtitles are disabled for this video by the uploader.")
    elif "no transcript" in str(e).lower():
        print("No transcript available. Try a different video.")
    else:
        print(f"Unexpected error: {e}")

2. Age-Restricted or Private Videos

Problem: Age-restricted videos require authentication; private videos are inaccessible.

Solution: Inform the user that these videos cannot be processed without authentication cookies. The youtube-transcript-api does not support cookie-based auth natively.

3. Rate Limiting

Problem: Fetching many transcripts in quick succession may trigger rate limits.

Solutions:

  • Add a 1-2 second delay between requests when batch processing
  • Cache transcripts locally to avoid re-fetching
  • Handle HTTP 429 errors with exponential backoff
import time

def fetch_with_retry(video_id, max_retries=3):
    for attempt in range(max_retries):
        try:
            return fetch_transcript(video_id)
        except Exception as e:
            if '429' in str(e) and attempt < max_retries - 1:
                wait = 2 ** (attempt + 1)
                time.sleep(wait)
                continue
            raise

4. Transcript Quality Issues

Problem: Auto-generated transcripts may contain errors, especially for technical terms, proper nouns, or non-English content.

Solutions:

  • Prefer manually created transcripts when available
  • Flag to the user that auto-generated transcripts may have inaccuracies
  • Use context clues to correct obvious errors in the summary

5. Very Long Videos

Problem: Videos over 2 hours may produce extremely long transcripts that exceed context limits.

Solutions:

  • Chunk the transcript into segments (e.g., 15-minute blocks)
  • Summarize each chunk independently, then create an overall summary
  • Let the user specify a time range to focus on
def chunk_transcript(transcript, chunk_minutes=15):
    """Split transcript into time-based chunks."""
    chunks = []
    current_chunk = []
    chunk_end = chunk_minutes * 60

    for segment in transcript:
        if segment['start'] >= chunk_end and current_chunk:
            chunks.append(current_chunk)
            current_chunk = []
            chunk_end += chunk_minutes * 60
        current_chunk.append(segment)

    if current_chunk:
        chunks.append(current_chunk)

    return chunks

6. Invalid or Expired URLs

Problem: Shortened URLs, expired links, or non-YouTube URLs.

Solution: Validate the extracted video ID format (11 characters, [A-Za-z0-9_-]) before making API calls. Return a clear error message for invalid inputs.


Advanced: Combining with Video Metadata

For richer summaries, consider fetching video metadata (title, channel, description) using the YouTube Data API v3 or by parsing the video page. This adds context but requires either an API key or HTML parsing.

The transcript-only approach used here is intentionally lightweight — no API key needed, no OAuth, minimal dependencies.


Language Support

The youtube-transcript-api supports all languages that YouTube provides transcripts for. Common language codes:

LanguageCodeAuto-generated
EnglishenYes
Chinese (Simplified)zh-HansYes
Chinese (Traditional)zh-HantYes
JapanesejaYes
KoreankoYes
SpanishesYes
FrenchfrYes
GermandeYes
PortugueseptYes
RussianruYes

To get all available languages for a video:

transcript_list = YouTubeTranscriptApi.list_transcripts(video_id)
for t in transcript_list:
    print(f"{t.language} ({t.language_code}) - {'manual' if not t.is_generated else 'auto'}")

平台分布

Codex

34.74%
按下载量换算46

Claude

27.4%
按下载量换算36

Cursor

18.91%
按下载量换算25

Gemini CLI

9.68%
按下载量换算13

安全审计

暂无安全审计结果可展示。

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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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