ugc-editing

Assembles, trims, lays out, and captions UGC-style vertical video from raw footage.

Updated Aug 6, 2026
One-click install
npx skills add https://github.com/ferrarifankid04/ai-skills-public --skill ugc-editing-ferrarifankid04
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ugc-editing
Source: https://github.com/ferrarifankid04/ai-skills-public/tree/main/claude-code/skills/palmier-ugc-editing
Command: npx skills add https://github.com/ferrarifankid04/ai-skills-public --skill ugc-editing-ferrarifankid04

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Turning raw talking-head footage and b-roll into a finished vertical UGC post requires many error-prone editing steps — cutting retakes and filler, choosing a layout, syncing b-roll, and placing captions — where small mistakes (wrong track index, unscoped captions, wrong aspect ratio) destroy the timeline. ## Core Features & Use Cases - Transcript-driven cutting: Reads the full word list and removes retakes, filler words, false starts, and dead air in a single pass. - Layout selection and application: Chooses between straight intercut, stacked split (b-roll top or bottom), or floating overlay, and applies it via apply_layout with fallback transforms. - Scoped captioning: Generates styled captions (highlightPop/wordPop) scoped to A-roll only, placed at the seam or lower third depending on format. - Use Case: A creator has a 69-second phone recording plus product demo clips and wants a 30-second TikTok ad — the skill sets 9:16, cuts bad takes, tiles muted b-roll on a new track, applies a stacked split, and adds gold-highlight captions. ## Quick Start Edit my raw talking-head footage and b-roll clips into a captioned 9:16 UGC video with a stacked split layout.

Frequently Asked Questions about ugc-editing

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I edit UGC video with talking head and b-roll?

Place the A-roll first, cut retakes and filler from the transcript, then add b-roll on a new auto-created track and apply a stacked split layout with apply_layout. Finish with captions scoped to the A-roll clips and verify with inspect_timeline.

How to remove filler words and bad takes from video automatically?

Read the full transcript first, mark every retake, filler word, and false start, then call remove_words once with all indices at once. Multiple sequential calls fail because indices shift after each cut.

Why does my b-roll overwrite the talking head footage?

This happens when trackIndex: 0 is specified on b-roll add_clips calls, overwriting the A-roll on V1. Omit trackIndex entirely so a new top video track is auto-created for the b-roll.

Why do captions show b-roll dialogue instead of the speaker?

add_captions was called without clipIds, so it transcribed all timeline audio including b-roll. Remove the caption track and regenerate with clipIds scoped to the A-roll video clips only.

Can I use this editing workflow with AI-generated footage?

Yes, the pipeline is footage-source-agnostic and works identically for AI-generated clips or real phone footage. For AI talking heads, keep segments to 2-3 seconds and lean heavily on b-roll to avoid viewer skepticism.

What are the limitations of the floating talking head layout?

The full-bleed b-roll with floating head format is not cleanly supported by apply_layout and requires chroma key via apply_effect plus manual set_clip_properties. It should be skipped unless specifically requested.