How do I install the Video 4k Normalization skill?

Run npx skillmds@latest add godot-fun/video-4k-normalization in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Video 4k Normalization safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: docs only. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Video 4k Normalization?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Video 4k Normalization free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Video 4k Normalization?

godot-fun (@godot-fun) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Video 4k Normalization by godot-fun

Name: Video 4k Normalization
Rating: 4.2 (5 reviews)
Author: godot-fun

Video 4k Normalization

Normalizes a single video clip to unified 3840×2160 60FPS H.265 Main10 40Mbps + AAC 320kbps BT.709 SDR MP4 4K master (FFmpeg re-encode, HDR tone-mapped). Use before hard-cut merge when 4K (or near-4K) clips differ in color space, HDR/SDR, fps, or size. Triggers: video-4k-normalization, 4K normalization, video normalization, media conform, unify encode, color conform, tone map HDR, prepare for video-merge, mixed HDR/SDR.

godot-fun Updated Sep 22, 2026

File contents

Video 4K Normalization

Re-encode a clip to one merge-safe 4K master (same delivery specs as video-to-4k, plus unified BT.709 SDR color):

Spec	Value
Resolution	3840×2160
Frame rate	60 FPS
Video	H.265 Main10 (`libx265`, `yuv420p10le`)
Video bitrate	40 Mbps
Audio	AAC 320 kbps
Color	BT.709 / bt709 / tv (HDR → tone-mapped SDR)
Container	MP4 (`.mp4`, `hvc1` tag)

Not AI upscaling — use video-to-4k first when SD/HD needs Real-ESRGAN quality. This skill uses FFmpeg scale + encode only.

Why

Hard-cut video-merge is stream-copy. Mixed HDR (BT.2020 + PQ) and SDR (BT.709) clips look fine alone, but after concat the player often applies the first clip's HDR tags to later SDR → oversaturated cuts. Normalization unifies pixels and color tags first.

Rules

When this skill applies, read and follow skill-dependency-manager — run scripts as documented, install missing tools into .dependency/.

Run normalize.py through .dependency/python/python. Never use host python / ffmpeg.
Never overwrite sources. Outputs go under video-4k-normalization/.
Use the bundled script — do not hand-write equivalent FFmpeg commands.
One file per run — pass --video with a single file; repeat for each clip in a batch.

Quick Start

.dependency/python/python .ai/video-4k-normalization/normalize.py --video path/to/clip.mp4

Example:

assets/shots/01.mp4   (HDR)
→ assets/shots/video-4k-normalization/01.mp4

assets/shots/10.mp4   (SDR)
→ assets/shots/video-4k-normalization/10.mp4

Then hard-cut merge the video-4k-normalization/ folder:

.dependency/python/python .ai/video-merge/merge.py --folder path/to/clips/video-4k-normalization

Defaults

Setting	Default	Notes
Target color	BT.709 SDR limited (`tv`)	HDR (PQ/HLG/BT.2020) → `hable` tone map
Scale	FFmpeg lanczos to 3840×2160	No Video2X
FPS	Forced 60	Frame dup/drop, not RIFE

Common Flags

--video · -o / --output

.dependency/python/python .ai/video-4k-normalization/normalize.py --video clip.mp4
.dependency/python/python .ai/video-4k-normalization/normalize.py --video clip.mp4 -o out/masters/clip.mp4

Never overwrite source files. Input must be a single video file (--video), not a directory. Supported inputs: .mp4, .mkv, .mov, .avi, .webm, .wmv, .flv, .m4v, .mpeg, .mpg, .ts, .mts, .m2ts, .3gp, .ogv.

Agent Notes

Use the bundled script only.
Missing Python / FFmpeg → populate .dependency/, set populated: true, retry.
Tell the user video-4k-normalization/ paths; they run video-merge on that folder when stitching.
For low-res quality upscale → video-to-4k, then optionally re-normalize if color still mixed.
Pipeline / filter details: reference.md

Tests

From repo root:

.dependency/python/python .ai/video-4k-normalization/test_normalize.py

Manual CLI examples: cli/video-4k-normalization.md

---name: video-4k-normalizationdescription: Normalizes a single video clip to unified 3840×2160 60FPS H.265 Main10 40Mbps + AAC 320kbps BT.709 SDR MP4 4K master (FFmpeg re-encode, HDR tone-mapped). Use before hard-cut merge when 4K (or near-4K) clips differ in color space, HDR/SDR, fps, or size. Triggers: video-4k-normalization, 4K normalization, video normalization, media conform, unify encode, color conform, tone map HDR, prepare for video-merge, mixed HDR/SDR.---# Video 4K NormalizationRe-encode a clip to one **merge-safe 4K master** (same delivery specs as`video-to-4k`, plus **unified BT.709 SDR color**):| Spec | Value ||------|-------|| Resolution | 3840×2160 || Frame rate | 60 FPS || Video | H.265 Main10 (`libx265`, `yuv420p10le`) || Video bitrate | 40 Mbps || Audio | AAC 320 kbps || Color | **BT.709 / bt709 / tv** (HDR → tone-mapped SDR) || Container | MP4 (`.mp4`, `hvc1` tag) |**Not** AI upscaling — use [`video-to-4k`](../video-to-4k/SKILL.md) first whenSD/HD needs Real-ESRGAN quality. This skill uses FFmpeg `scale` + encode only.## WhyHard-cut [`video-merge`](../video-merge/SKILL.md) is stream-copy. Mixed**HDR (BT.2020 + PQ)** and **SDR (BT.709)** clips look fine alone, but afterconcat the player often applies the first clip's HDR tags to later SDR →oversaturated cuts. Normalization unifies pixels **and** color tags first.## RulesWhen this skill applies, read and follow [skill-dependency-manager](../skill-dependency-manager.md) — run scripts as documented, install missing tools into `.dependency/`.- Run `normalize.py` through **`.dependency/python/python`**. Never use host `python` / `ffmpeg`.- **Never overwrite sources.** Outputs go under `video-4k-normalization/`.- Use the bundled script — do not hand-write equivalent FFmpeg commands.- **One file per run** — pass `--video` with a single file; repeat for each clip in a batch.## Quick Start```bash.dependency/python/python .ai/video-4k-normalization/normalize.py --video path/to/clip.mp4```Example:```assets/shots/01.mp4 (HDR)→ assets/shots/video-4k-normalization/01.mp4assets/shots/10.mp4 (SDR)→ assets/shots/video-4k-normalization/10.mp4```Then hard-cut merge the `video-4k-normalization/` folder:```bash.dependency/python/python .ai/video-merge/merge.py --folder path/to/clips/video-4k-normalization```## Defaults| Setting | Default | Notes ||---------|---------|-------|| Target color | BT.709 SDR limited (`tv`) | HDR (PQ/HLG/BT.2020) → `hable` tone map || Scale | FFmpeg lanczos to 3840×2160 | No Video2X || FPS | Forced 60 | Frame dup/drop, not RIFE |## Common Flags`--video` · `-o` / `--output````bash.dependency/python/python .ai/video-4k-normalization/normalize.py --video clip.mp4.dependency/python/python .ai/video-4k-normalization/normalize.py --video clip.mp4 -o out/masters/clip.mp4```**Never overwrite source files.** Input must be a single video file (`--video`), not a directory. Supported inputs: `.mp4`, `.mkv`, `.mov`, `.avi`, `.webm`, `.wmv`, `.flv`, `.m4v`, `.mpeg`, `.mpg`, `.ts`, `.mts`, `.m2ts`, `.3gp`, `.ogv`.## Agent Notes1. Use the bundled script only.2. Missing Python / FFmpeg → populate `.dependency/`, set `populated: true`, retry.3. Tell the user `video-4k-normalization/` paths; they run `video-merge` on that folder when stitching.4. For low-res quality upscale → `video-to-4k`, then optionally re-normalize if color still mixed.5. Pipeline / filter details: [reference.md](reference.md)## TestsFrom repo root:```bash.dependency/python/python .ai/video-4k-normalization/test_normalize.py```Manual CLI examples: [cli/video-4k-normalization.md](../../../cli/video-4k-normalization.md)

Frequently asked questions