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-09-pipeline/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-09-pipeline)<a href="https://agentmods.dev/skills/hao-ai-lab/fastvideo/add-model-09-pipeline"><img src="https://agentmods.dev/badge/skills/hao-ai-lab/fastvideo/add-model-09-pipeline/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-09-pipeline"><img src="https://agentmods.dev/badge/skills/hao-ai-lab/fastvideo/add-model-09-pipeline.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 | $0.00046 | $0.02945 |
| Opus 5 | $0.00023 | $0.01473 |
| Sonnet 5 | $0.00009 | $0.00589 |
| Haiku 4.5 | $0.00005 | $0.00295 |
Grade A, and why
add-model-09-pipeline 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 — 256 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Add Model Pipeline
Goal
Implement and verify the end-to-end FastVideo pipeline after the native components and converted weights have passed non-skip component parity. This skill owns pipeline class/stage wiring, pipeline configs, presets, registry entries, examples, smoke tests, and pipeline parity-debug.
FastVideo has one pipeline architecture: stage-based composition through
ComposedPipelineBase. Add or specialize stages only when existing stages cannot
represent the official behavior safely.
Hard Gate
Do not start pipeline work until every required component, including reused components, has a non-skip local parity PASS.
If any component row is missing, skipped, red, or blocked, return to /add-model
Phase 6. Pipeline parity cannot distinguish stage wiring mistakes from broken
component numerics when component parity is still unresolved.
Inputs
Follow ../add-model/shared/common_rules.md for token/auth safety, state files,
escape hatches, production boundaries, and skip/pass semantics.
Require a complete packet matching
../add-model/contracts/pipeline_context.md.
The packet must include:
- official pipeline files and official call/default sources;
- workload types, input/output modalities, and output contract;
- converted or source
model_index.jsonpath; - component parity rows, all
non_skip_pass; - target FastVideo pipeline/config/preset/registry/example/test paths;
local_tests_readmeandport_state_filepaths.
Outputs
- Pipeline package under
fastvideo/pipelines/basic/<family>/. - Pipeline config under
fastvideo/configs/pipelines/<family>.pyor a documented family-local config file when that matches existing project style. - Presets under
fastvideo/pipelines/basic/<family>/presets.py. - Registry updates in
fastvideo/registry.py. - Basic example under
examples/inference/basic/basic_<family>*.py. - Local smoke and parity tests under
tests/local_tests/pipelines/. - Updated
tests/local_tests/<model_family>/README.md. - Updated
tests/local_tests/<model_family>/PORT_STATUS.md. - Handoff matching
../add-model/contracts/pipeline_handoff.md.
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.
- 12d ago First seen · 256 lines · 46 tokens per session scan A 4406de3a2613
add-model-09-pipeline is a skill published in the GitHub repository hao-ai-lab/FastVideo (4,368 stars, last pushed 2d ago), licensed Apache-2.0. It adds 46 tokens to every session and 2,945 once invoked, about $0.0002 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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