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 agentmods add skills/mxslr/mlcraft/domain-videonpx skills add mxslr/mlcraft --skill domain-videogit clone --depth 1 https://github.com/mxslr/mlcraftWrote 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/mxslr/mlcraft/domain-video)<a href="https://agentmods.dev/skills/mxslr/mlcraft/domain-video"><img src="https://agentmods.dev/badge/skills/mxslr/mlcraft/domain-video.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00086 | $0.00430 |
| Opus 5 | $0.00043 | $0.00215 |
| Sonnet 5 | $0.00017 | $0.00086 |
| Haiku 4.5 | $0.00009 | $0.00043 |
Grade A, and why
domain-video 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 5d 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.
What it actually says
Video Understanding - Method Selection
Prefer models pretrained on large video datasets (Kinetics). Video is compute-heavy, so use mixed precision and clip-based training.
Decision table
| Task | Recommended (recent, 2021-2025) | Notes |
|---|---|---|
| Action or video classification | VideoMAE or VideoMAEv2 (self-supervised pretrain, then fine-tune), Video Swin, UniFormerV2 | Kinetics-pretrained. Metric is top-1 and top-5 accuracy. |
| Efficient or low-budget | adapt a strong image backbone with temporal modules (AIM), or a small MoViNet | cheaper than a full video transformer. |
| Temporal action detection (localize actions in long untrimmed video) | ActionFormer, TadTR | metric is mAP at temporal IoU. |
| General-purpose video features | InternVideo family | strong for many downstream tasks. |
Cross-cutting practice
- Sample frames (uniform or dense), train on short clips, and average multiple clips at test time.
- Augment with temporal cropping, per-frame flip and light photometric jitter. Keep flips label-safe.
- Leakage: split by VIDEO or subject, never by frame or by clips taken from the same video.
- Metrics: top-1 and top-5 accuracy for trimmed classification; mAP at temporal IoU for detection. Not frame accuracy.
- Explainability: per-frame Grad-CAM or spatiotemporal attention; show which frames the model attended to.
- Improve accuracy: use
accuracy-improvement-loop; evaluate withrigorous-evaluation.
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.
- 5d ago First seen · 25 lines · 86 tokens per session scan A 52bbf2e76bb0
domain-video is a skill published in the GitHub repository mxslr/mlcraft (8 stars, last pushed 1mo ago), licensed MIT. It adds 86 tokens to every session and 430 once invoked, about $0.0004 per session on Opus 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 2026-08-31.
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