lightflow-video-auto-edit

name	LightFlow Video Auto Edit
description	Use this skill to run or modify the end-to-end lightflow.video_auto_edit package-owned workflow that plans and renders videos.
version	0.4.0

LightFlow Video Auto Edit

Use lightflow.video_auto_edit only after lightflow.video_highlights has returned its HMAC-verified clips output. Pass that output unchanged as sources. The workflow renders a normalized MP4 from explicit verified ranges; it never creates segments from silence, scene changes, or filename metadata.

Runtime

The published workflow crate contains a Rust-native runner.v1 binary. No repository-relative script or global command runner is required. FFmpeg and FFprobe are the only host media dependencies and missing tools fail closed.

Contract

• Required sources: JSON array of clip objects with VideoScore provenance.
• Required brief: editing goal used for deterministic ranking.
• Required output_path: destination MP4.
• Optional style: defaults to clean social edit.
• Optional constraints: supports aspect_ratio, max_duration_seconds, fps, width, and height.
• Outputs: edit_plan, video, video_path, and summary.

Set LIGHTFLOW_VIDEOSCORE_EVIDENCE_KEY in the runtime environment for both the highlight and auto-edit workflows. Each clip requires path and a highlight object. Preserve an explicit start / end range when supplied; the highlight's source_path must resolve to the same source, its start_seconds / end_seconds must match that range within 0.001 seconds, its numeric score must be 1 through 4, and both model and reason must be non-empty. Require workflow:"lightflow.video_highlights", model:"TIGER-Lab/VideoScore-v1.1", and an evidence lowercase-hex HMAC tag generated by the highlight workflow. String-only sources and missing or mismatched evidence are rejected.

CLI Usage

From this project root:

lfw run lightflow.video_auto_edit \
  --input sources='[{"id":"intro","path":"media/intro.mp4","start":0,"end":8,"highlight":{"workflow":"lightflow.video_highlights","source_path":"media/intro.mp4","start_seconds":0,"end_seconds":8,"score":3.7,"model":"TIGER-Lab/VideoScore-v1.1","reason":"Strong full-vehicle opening.","evidence":"<generated-by-lightflow.video_highlights>"}}]' \
  --input brief='"Create a concise product recap with a strong hook."' \
  --input output_path='"output/recap.mp4"' \
  --input constraints='{"aspect_ratio":"9:16","max_duration_seconds":30}'

When lfw is not installed, replace lfw with cargo run --manifest-path ../../Cargo.toml --bin lfw --.

API Usage

Start lfw serve, then use the shared HTTP workflow contract:

curl -sS -X POST http://127.0.0.1:5174/workflows/lightflow.video_auto_edit/run \
  -H 'content-type: application/json' \
  -d '{"inputs":{"sources":[{"path":"media/intro.mp4","start":0,"end":8,"highlight":{"workflow":"lightflow.video_highlights","source_path":"media/intro.mp4","start_seconds":0,"end_seconds":8,"score":3.7,"model":"TIGER-Lab/VideoScore-v1.1","reason":"Strong full-vehicle opening.","evidence":"<generated-by-lightflow.video_highlights>"}}],"brief":"Create a concise product recap with a strong hook.","output_path":"output/recap.mp4","constraints":{"aspect_ratio":"9:16","max_duration_seconds":30}}}'

Run the crate's Rust tests and Clippy after changing the runner, planner, edit-plan schema, or FFmpeg behavior. Update this skill whenever the workflow contract or common command changes.