FastVideo is a framework for training and running accelerated video-generation models, including real-time inference and post-training workflows. It is for researchers and developers building or deploying diffusion-based systems that generate video.
Borrowing it
Nothing to install: this file belongs to hao-ai-lab/FastVideo. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/hao-ai-lab/FastVideo/main/.agents/skills/reseed-ssim-references/SKILL.mdgit clone --depth 1 https://github.com/hao-ai-lab/FastVideoWrote 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/hao-ai-lab/fastvideo/reseed-ssim-references)<a href="https://agentmods.dev/skills/hao-ai-lab/fastvideo/reseed-ssim-references"><img src="https://agentmods.dev/badge/skills/hao-ai-lab/fastvideo/reseed-ssim-references/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/hao-ai-lab/fastvideo/reseed-ssim-references"><img src="https://agentmods.dev/badge/skills/hao-ai-lab/fastvideo/reseed-ssim-references.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 327 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00130 | $0.03855 |
| Opus 5 | $0.00065 | $0.01928 |
| Sonnet 5 | $0.00026 | $0.00771 |
| Haiku 4.5 | $0.00013 | $0.00385 |
Grade A, and why
reseed-ssim-references 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 12d 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 — 345 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Re-seed SSIM Reference Videos
Purpose
Replace the existing SSIM reference videos for a single (test_file, model_id)
pair on the HF dataset (FastVideo/ssim-reference-videos). This is destructive
on HF — the old refs are overwritten — so the skill always:
- Confirms intent with a one-liner the user has to type.
- Downloads the existing refs as a local, timestamped backup.
- Regenerates through the manual legacy Modal L40S maintenance path.
- Pauses for a side-by-side eyeball of backup vs new mp4s.
- Uploads with
--force, scoped to the single--model-id. - Reminds the user to keep the backup until the PR lands.
Pairs with seed-ssim-references, which is the inverse (first-time seeding
only, refuses to overwrite). Re-seeding is intentionally a separate, more
ceremonial operation because mistakenly clobbering production refs is much
harder to recover from than failing closed.
When to use
- An intentional code change (model port fix, kernel upgrade, attention backend swap, hyperparameter change in the test itself) has shifted the expected SSIM output and the existing refs no longer represent the new ground truth.
- A test is failing in CI for the right reason (the new code is correct, the old refs are stale).
When not to use
- A test is failing for the wrong reason (the port is buggy, not the refs). Fix the port; re-seeding hides the bug.
- A brand-new test that has no refs on HF yet. Use
seed-ssim-references. - "Just to clean up drift" without a concrete code change to point at. The PR description has to justify why refs changed; without a concrete change, there's nothing to write.
Inputs
| Parameter | Required | Description |
|---|---|---|
test_file |
Yes | Path to the SSIM test, e.g. fastvideo/tests/ssim/test_matrixgame_similarity.py. Validated against fastvideo/tests/ssim/test_*_similarity.py. |
model_id |
Yes | Single model id from the test's *_MODEL_TO_PARAMS, e.g. Matrix-Game-2.0-Diffusers-Base. Re-seed runs are per model. For multi-model tests, invoke the skill once per model. |
intent_rationale |
Yes | One-line explanation of why refs are being regenerated (e.g. "Relax FA-2 head_size whitelist to include 80 — matrix_game now uses FLASH_ATTN instead of TORCH_SDPA"). Recorded in the backup directory and reused in the PR description. |
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.
- 12d ago First seen · 345 lines · 130 tokens per session scan A 7656707577fb
reseed-ssim-references is a skill published in the GitHub repository hao-ai-lab/FastVideo (4,368 stars, last pushed 3d ago), licensed Apache-2.0. It adds 130 tokens to every session and 3,855 once invoked, about $0.0006 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 2026-08-30.
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