Transcript-Driven Video Edit Pipeline (HyperFrames)

Turn raw talking footage into a finished cut: word-timed rough cut, branded graphics, synced captions, and fast segment re-renders.

Creator / Videovideo-editingrough-cut
by AgentVoltv1.0.0
Free to sign up · every skill included with AgentVolt Pro

Before & after

Same prompt, same agent — the only difference is the skill.

Prompt“Edit this raw footage into a finished video with captions and graphics.”
Beforegeneric AI agent
Editing raw footage is a detailed process. You'd need to rough-cut the video, sync audio, add captions, color-correct, layer graphics, adjust pacing, and export. Do you have specific software in mind? What's the video for? How long is the footage? Are there particular graphics or style elements you want? Do you want burned-in captions or separate subtitle files?
Afterwith Transcript-Driven Video Edit Pipeline (HyperFrames)
Automates a FULL EDITING PIPELINE: rough-cut via word-level timestamps from speech-to-text, motion graphics with saved brand presets: fonts, colors, logo placement, auto-captions with speaker labels, partial re-rendering for fast iteration, and final export. Orchestrated by Claude Code. You provide raw footage and optional brand presets from previous sessions. Outputs finished video with graphics, captions, and music selection. Re-render only changed segments to accelerate edits across multiple passes. Best for content creators automating video production. Open-source toolkit.

About this skill

Your automated edit "works", but the result still has problems. Captions drift out of sync after minute three. Every cut makes a tiny click. The lower third shows up two seconds late. And changing one title means waiting through a full re-render. This skill makes Claude Code run the edit the way a technical editor would. It builds one edit decision list that every later step follows, and it remaps every timestamp to the new timeline. It re-renders only the parts you changed.

What it does

  • Builds a rough cut from word-level timestamps plus silence detection. It cuts dead air and repeated takes, and catches the "um"s that transcripts tend to leave out.
  • Keeps a single JSON edit decision list as the source of truth, so captions, graphics, and re-renders all stay in sync
  • Remaps caption and graphic timing from the raw footage to the cut timeline, with a correction dictionary for brand names and jargon
  • Places branded graphics (lower thirds, titles, callouts) on the exact words they belong to, using brand preset tokens and HTML compositions
  • Splits the timeline into cached segments so a revision re-renders only what changed. Audio is rendered as one continuous pass, so the joins don't gap.
  • Produces a cut report you can review as text: every removal, its reason, and the words removed

What you get

A working pipeline in your project: normalize, transcribe, edit list, rough cut, graphics, captions, loudness-matched export. You also get the exact commands and a cut report you can check before you render the final.

Best for

Creators and small teams who edit talking-head, interview, tutorial, or podcast-video footage with Claude Code and want repeatable edits on brand without scrubbing a timeline.

SKILL.md preview

SKILL.md
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name: transcript-driven-video-edit-pipeline

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