summarize
Summarize or extract text/transcripts from URLs, podcasts, and local files (great fallback for “transcribe this YouTube/video”).
다음 행동
/summarize기술 README 원문 보기
설치 옵션, 예시 코드, 세부 사용법을 영어 README 원문 그대로 확인합니다.
Summarize
Fast CLI to summarize URLs, local files, and YouTube links.
When to use (trigger phrases)
Use this skill immediately when the user asks any of:
- “use summarize.sh”
- “what’s this link/video about?”
- “summarize this URL/article”
- “transcribe this YouTube/video” (best-effort transcript extraction; no
yt-dlpneeded)
Quick start
summarize "https://example.com" --model google/gemini-3-flash-preview summarize "/path/to/file.pdf" --model google/gemini-3-flash-preview summarize "https://youtu.be/dQw4w9WgXcQ" --youtube auto
YouTube: summary vs transcript
Best-effort transcript (URLs only):
summarize "https://youtu.be/dQw4w9WgXcQ" --youtube auto --extract-only
If the user asked for a transcript but it’s huge, return a tight summary first, then ask which section/time range to expand.
Model + keys
Set the API key for your chosen provider:
- OpenAI:
OPENAI_API_KEY - Anthropic:
ANTHROPIC_API_KEY - xAI:
XAI_API_KEY - Google:
GEMINI_API_KEY(aliases:GOOGLE_GENERATIVE_AI_API_KEY,GOOGLE_API_KEY)
Default model is google/gemini-3-flash-preview if none is set.
Useful flags
--length short|medium|long|xl|xxl|<chars>--max-output-tokens <count>--extract-only(URLs only)--json(machine readable)--firecrawl auto|off|always(fallback extraction)--youtube auto(Apify fallback ifAPIFY_API_TOKENset)
Config
Optional config file: ~/.summarize/config.json
{ "model": "openai/gpt-5.2" }Optional services:
FIRECRAWL_API_KEYfor blocked sitesAPIFY_API_TOKENfor YouTube fallback
이것도 같이 보면 좋다
같은 업무 태그와 카테고리가 겹치는 항목부터 보여줍니다.

beauty-reel
퍼스널컬러별 디즈니 공주 변신 릴스(9:16)를 Higgsfield + ffmpeg로 제작하는 파이프라인. "같은 얼굴 한 명이 봄웜/여쿨/가을웜/겨쿨 공주로 변신" 컨셉의 인스타 릴스를 만든다. 베이스 가상얼굴 1장 고정 → 4톤 실사 공주 생성 → Kling 무빙 클립 → Noto 다국어 자막 → 빛번짐 전환으로 합성. "퍼스널컬러 공주 릴스", "디즈니 공주 변신 영상", "퍼스널컬러 릴스 만들어", "공주 메이크업 릴스", "봄웜 여쿨 공주" 류 요청에 사용. "뷰티릴스", "뷰티 릴스 만들어", "메이크업 변신 영상", "비포애프터 릴스" 등 인물 일관성이 필요한 변신·비포애프터 뷰티 릴스 전반에 응용 가능(베이스 얼굴 고정 → 룩 N개 → 무빙 → 자막 → 합성 파이프라인 그대로). 발행(업로드)은 포함 안 함 — 컨펌 게이트.

embedded-captions
Add captions to a talking-head video. ONE catalog (CATALOG.md) of 32 visual identities behind two engines: column-flow (captions composited INTO the scene — matte occlusion + mix-blend; cream/ink/editorial/keynote/documentary/loud/neon/glitch/chrome/velocity) and themed constitutions (anchor/ordnance/terminal/neonsign/stardust/stomp/scoreboard/transit/vhs/arcade/dossier/laser/thunder/hologram/biolume/aurora/spectrum/papercut/popup/chalkboard/graffiti/brush/inkwater/ransom/lastpage/nightcity — e.g. a glyph-decode climax, a neon sign WRITTEN stroke by stroke, or the quiet `anchor` rail default). Route by identity, never by mode. Trigger on "captions/subtitles", "embed/cinematic captions", "VFX captions", "炸/特效/酷炫字幕", a named identity, or top-tier motion-graphics asks. Embedding every word is wrong for most talking-head content — `anchor` is the verbatim default. Pipeline: transcription → hyperframes remove-background matting → HTML render → ffmpeg overlay. Requires hyperframes and a single-subject clip.

faceless-explainer
faceless-explainer video workflow - arbitrary text (article / notes / topic / brief) -> narrator_scripts.json + audio (voice + BGM) + section_plan.md -> typography / abstract-graphics / diagram / data-viz video. Typical length up to ~3 min (sweet spot ~30-90s); a genuinely longer piece is general-video, not this workflow. Generates its OWN narration (TTS) — it does not sync to a user-supplied / pre-recorded voiceover (that is general-video). No website capture, no real product screenshots. If the text names a product / its site to promote, that is /product-launch-video; when product-vs-topic is unclear, start at /hyperframes-read-first.