tutorial · 1 min read

Langes Video → mehrere untertitelte Clips, mit einem einzigen Befehl

Zerlege jedes lange Video in N untertitelte, kürzere Clips. Einmal transkribieren, die Momente automatisch per KI auswählen, jeden Clip parallel zuschneiden + untertiteln. Optional ins Hochformat (9:16) für TikTok / Reels / Shorts, ins Quadrat (1:1) für Instagram oder ins Porträtformat (4:5) umformatieren — der Untertitel-Anker passt sich automatisch an.

Du hast ein langes Video und willst ein Dutzend kürzere daraus machen? Transkribiere das Ganze einmal, lass die KI die besten Momente auswählen und schneide und untertitle dann jeden Clip in einer Schleife. Mit --reformat wird für TikTok oder Reels ins Hochformat zugeschnitten; ohne die Flagge bleibt das Seitenverhältnis der Quelle erhalten — ideal für YouTube-Cards oder Instagram-Feeds.

#cli#claude-code#captions#transcription#highlights#video-trim#video-reframe#shorts#vertical-video#tiktok#reels#instagram#youtube-shorts#agent-loop
Run it

Two ways, same result

Either paste the prompt into your AI agent, or run a single command in your terminal: both invoke the same recipe.

est. cost ≈ 11.6 credits needs PIPE2_TOKEN runs 6 pipelines
prompt · paste into agent
Claude Code, Codex, any shell-agent: conventions in AGENT.md
Run the pipe2 clip-factory recipe: one long video → N captioned, watermarked clips. Picks moments automatically.

Dispatch: pipe2 recipe run clip-factory --input <video-url-or-local-path> --reformat 9:16

Tune the picker with --highlights-count N and --highlights-style "the funniest moments". Power-user override: --clips path/to/clips.json (JSON array of {"context","start_sec","end_sec"}).

Returns a JSON array of clip URLs.
The agent reports the final hosted video URL when the chain completes.
command · run in shell
Needs pipe2 CLI + PIPE2_TOKEN; fetches the recipe from GitHub
pipe2 recipe run clip-factory --input https://www.youtube.com/watch?v=4uzGDAoNOZc --reformat 9:16
Prints the hosted video URL to stdout when the chain finishes.
Walkthrough

6 pipelines transform one input into one output

What each step takes in, and what it spits out. The artifact glyph on the right shows the output kind.

total ≈ 11.6 credits steps 6 pipelines flow

Estimated at recipe defaults. Final cost may vary: metered models bill by actual token usage, and optional steps add to the total when their inputs are supplied.

  1. transcription 0.8 cr

    ElevenLabs Scribe transcribes the full source once: cached on the source hash, so re-runs and every clip after the first are free. The trim reads these words to find each moment.

    input source OpenClaw Creator, Why 80% of Apps Will Disappear www.youtube.com/watch?v=4uzGDAoNOZc Demo previews are five clips cut from this interview. Drop in any long-form video to make your own.
    text
    00:00:00,180  Today, I'm sitting down with Peter Steinberger, the creator of OpenClaw, the open source personal AI agent that has completely taken over the internet.
    00:00:09,060  The GitHub repo exploded to over 160,000 stars practically overnight.
    00:00:14,130  The community has built countless projects, like Malt Book, where bots talk among themselves.
    00:00:19,560  And now, the bots are even renting humans to do tasks in the real world.
    00:00:24,220  In our conversation, we discuss his aha moment, his contrarian development philosophies, and what this means for builders in 2026.
    00:00:32,740  Let's dive in.
    00:00:38,980  So good to see you, man.
    00:00:39,960  Hey, what's up?
    00:00:40,760  Um, so you've made something people want.
    …
  2. highlights 10 cr

    Reads the transcript and picks N editorial moments: the auto-pick path. Skipped when --clips supplies a manual JSON list.

    json
    [{"context":"Peter explains OpenClaw's core differentiator: local execution gives it access to everything the user can do, unlike cloud-based AI.","desired_seconds":32,"start_sec":95.24000000000001,"end_sec":127.64},{"context":"The vivid moment Peter realized OpenClaw's creative problem-solving: it autonomously transcribed a voice message using ffmpeg and OpenAI's API without being explicitly programmed to do so.","desired_seconds":106,"start_sec":515.182,"end_sec":621.252},{"context":"Peter's contrarian prediction: 80% of apps disappear because personal AI agents manage data and tasks more naturally than purpose-built applications.","desired_seconds":55,"start_sec":641.792,"end_sec":696.312},{"context":"Peter's philosophy on building: minimize friction by using Unix tools and CLIs instead of inventing new abstractions, letting the model handle creative problem-solving.","desired_seconds":54,"start_sec":1178.264,"end_sec":1232.584},{"context":"Peter articulates why swarm intelligence mirrors human society: individuals alone can't build iPhones or go to space, but groups specializing together achieve anything.","desired_seconds":46,"start_sec":258,"end_sec":303.5}]
  3. video-trim 0.1 cr

    Per clip: deterministic SRT-slice + ffmpeg-cut to the window highlights picked, snapped to sentence boundaries. Returns the windowed transcript rebased to the clip for the captions step.

    video
  4. video-reframe +2 cr only if --reformat

    Per clip (only when --reformat is set): reframes to the requested aspect ratio with the lock-and-cut camera director: it frames the active speaker in every shot (from the windowed transcript + CV faces) and cuts cleanly at shot boundaries, never drifting or panning. Skipped by default: the source's native aspect is preserved.

    video
  5. captions 0.2 cr

    Per clip: burns the windowed transcript onto the clip in your chosen preset, at the anchor --position picks.

    video
  6. watermark 0.5 cr

    Overlays the Pipe2 logo (or your own --watermark-url) at the top-left corner so the clip carries attribution across reposts. Pass --no-watermark to skip.

    video

Click any slug to see full pipeline pricing tiers.

Stuck on a chain that won't compose? Drop into our Discord and paste the JSON output of the failing step.