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godot-fungodot-fun/gai/.agents/skills/video-4k-normalization/SKILL.md

video-4k-normalization

Skill202 starsChanged 14 days agoMITView on GitHub

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.

1 other project uses a version of this.

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The file

We split this skill into the rules it gives an agent

4 rules. About 0 are common, 2 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

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

    line 40
  2. Very specific:

    Run normalize.py through .dependency/python/python.

    line 42
  3. Distinctive:

    Use the bundled script — do not hand-write equivalent FFmpeg commands.

    line 44
  4. Distinctive:

    Use the bundled script only.

    line 90

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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):

SpecValue
Resolution3840×2160
Frame rate60 FPS
VideoH.265 Main10 (libx265, yuv420p10le)
Video bitrate40 Mbps
AudioAAC 320 kbps
ColorBT.709 / bt709 / tv (HDR → tone-mapped SDR)
ContainerMP4 (.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 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

SettingDefaultNotes
Target colorBT.709 SDR limited (tv)HDR (PQ/HLG/BT.2020) → hable tone map
ScaleFFmpeg lanczos to 3840×2160No Video2X
FPSForced 60Frame 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

  1. 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

Tests

From repo root:

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

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

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