Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/TTflysky/sirenhuisuo --skill youtube-content명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
统一的 IMA OpenAPI 技能,支持笔记管理和知识库操作。 当用户提到知识库、资料库、笔记、备忘录、记事,或者想要上传文件、添加网页到知识库、 搜索知识库内容、搜索/浏览/创建/编辑笔记时,使用此 skill。 即使用户没有明确说"知识库"或"笔记",只要意图涉及文件上传到知识库、网页收藏、 知识搜索、个人文档存取(如"帮我记一下"、"搜一下知识库里有没有XX"),也应触发此 skill。
Manage Apple Notes via memo CLI: create, search, edit.
Apple Reminders via remindctl: add, list, complete.
SOC 직업 분류 기준
SKILL.md 표시 중
| name | youtube-content |
| description | YouTube transcripts to summaries, threads, blogs. |
| platforms | ["linux","macos","windows"] |
Use when the user shares a YouTube URL or video link, asks to summarize a video, requests a transcript, or wants to extract and reformat content from any YouTube video. Transforms transcripts into structured content (chapters, summaries, threads, blog posts).
Extract transcripts from YouTube videos and convert them into useful formats.
Use uv so the dependency is installed into the same Hermes-managed environment
that runs the helper script:
uv pip install youtube-transcript-api
SKILL_DIR is the directory containing this SKILL.md file. The script accepts any standard YouTube URL format, short links (youtu.be), shorts, embeds, live links, or a raw 11-character video ID.
# JSON output with metadata
uv run python3 SKILL_DIR/scripts/fetch_transcript.py "https://youtube.com/watch?v=VIDEO_ID"
# Plain text (good for piping into further processing)
uv run python3 SKILL_DIR/scripts/fetch_transcript.py "URL" --text-only
# With timestamps
uv run python3 SKILL_DIR/scripts/fetch_transcript.py "URL" --timestamps
# Specific language with fallback chain
uv run python3 SKILL_DIR/scripts/fetch_transcript.py "URL" --language tr,en
After fetching the transcript, format it based on what the user asks for:
00:00 Introduction — host opens with the problem statement
03:45 Background — prior work and why existing solutions fall short
12:20 Core method — walkthrough of the proposed approach
24:10 Results — benchmark comparisons and key takeaways
31:55 Q&A — audience questions on scalability and next steps
--text-only --timestamps via uv run python3.--language to get any available transcript. If still empty, tell the user the video likely has transcripts disabled.--language to fetch any available transcript, then note the actual language to the user.uv pip install youtube-transcript-api and retry.