Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add godot-fun/godot-framework --skill video-4k-normalizationgit clone --depth 1 https://github.com/godot-fun/godot-frameworkWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/godot-fun/godot-framework/video-4k-normalization)<a href="https://agentmods.dev/skills/godot-fun/godot-framework/video-4k-normalization"><img src="https://agentmods.dev/badge/skills/godot-fun/godot-framework/video-4k-normalization/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/godot-fun/godot-framework/video-4k-normalization"><img src="https://agentmods.dev/badge/skills/godot-fun/godot-framework/video-4k-normalization.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00136 | $0.01118 |
| Opus 5.5 | $0.00054 | $0.00447 |
| Sonnet 5.5 | $0.00027 | $0.00224 |
| Haiku 4.5 | $0.00014 | $0.00112 |
Grade A, and why
video-4k-normalization scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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.pythrough.dependency/python/python. Never use hostpython/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
--videowith 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 |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 104 lines · 136 tokens per session scan A d30444c54d57
video-4k-normalization is a skill published in the GitHub repository godot-fun/godot-framework (116 stars, last pushed 1mo ago), licensed MIT. It adds 136 tokens to every session and 1,118 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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