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/add-model-10-pr-review/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/add-model-10-pr-review)<a href="https://agentmods.dev/skills/hao-ai-lab/fastvideo/add-model-10-pr-review"><img src="https://agentmods.dev/badge/skills/hao-ai-lab/fastvideo/add-model-10-pr-review/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/add-model-10-pr-review"><img src="https://agentmods.dev/badge/skills/hao-ai-lab/fastvideo/add-model-10-pr-review.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 | $0.00104 | $0.01514 |
| Opus 5 | $0.00052 | $0.00757 |
| Sonnet 5 | $0.00021 | $0.00303 |
| Haiku 4.5 | $0.00010 | $0.00151 |
Grade A, and why
add-model-10-pr-review 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 — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Add-Model PR Review
Use this skill when a reviewed PR appears to add, port, or substantially modify a FastVideo model family, model variant, first-class model component, checkpoint conversion, model pipeline, or local parity coverage.
This is a review skill, not an implementation workflow. Do not run /add-model
or start writing missing port code during review. Use the add-model skill stack
as a rubric for findings.
Trigger Paths
Trigger this skill if git diff --name-only <base>...HEAD includes any of:
fastvideo/models/dits/,fastvideo/configs/models/dits/fastvideo/models/vaes/,fastvideo/configs/models/vaes/fastvideo/models/encoders/,fastvideo/configs/models/encoders/fastvideo/models/schedulers/,fastvideo/configs/models/schedulers/fastvideo/models/upsamplers/,fastvideo/configs/models/upsamplers/fastvideo/models/audio/,fastvideo/configs/models/audio/fastvideo/pipelines/basic/,fastvideo/configs/pipelines/fastvideo/registry.py,fastvideo/api/sampling_param.pyscripts/checkpoint_conversion/examples/inference/basic/tests/local_tests/, especially component or pipeline parity testsfastvideo/tests/ssim/or other quality-regression tests for generated media
Also trigger when the PR title/body claims a new model, model variant, VAE, encoder, scheduler, conditioner, pipeline, conversion script, or generated-media quality baseline even if the path list is incomplete.
Review Inputs
Read these add-model references as review checklists:
../add-model/SKILL.md: phase gates and final handoff requirements.../add-model/shared/common_rules.md: token/auth safety, production import boundaries, state files, and skip/pass semantics.../add-model/contracts/final_handoff.md: final evidence expected from a complete port.../add-model/contracts/component_context.mdand../add-model/contracts/component_skill_handoff.md: component evidence and parity-debug expectations.../add-model/contracts/conversion_request.mdand../add-model/contracts/conversion_handoff.md: conversion evidence, strict-load status, config validation, and retry context.../add-model/contracts/pipeline_context.mdand../add-model/contracts/pipeline_handoff.md: pipeline class/stage/config/ preset/registry/example evidence.
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 · 142 lines · 104 tokens per session scan A e7e8be643dd0
add-model-10-pr-review 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 104 tokens to every session and 1,514 once invoked, about $0.0005 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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