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/sandyup/comfyui-mcp/video-extendnpx skills add sandyup/comfyui-mcp --skill video-extendgit clone --depth 1 https://github.com/sandyup/comfyui-mcpWrote 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/sandyup/comfyui-mcp/video-extend)<a href="https://agentmods.dev/skills/sandyup/comfyui-mcp/video-extend"><img src="https://agentmods.dev/badge/skills/sandyup/comfyui-mcp/video-extend.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 | $0.00146 | $0.08029 |
| Opus 5 | $0.00073 | $0.04015 |
| Sonnet 5 | $0.00029 | $0.01606 |
| Haiku 4.5 | $0.00015 | $0.00803 |
Grade A, and why
video-extend 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.
This is a copy
89% identical to video-extend — 340 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 522 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Video Extension (Pusa 2.2 — temporal flowmatching)
Overview
Pusa extends a video temporally — it continues / lengthens an existing clip
rather than regenerating it from scratch. It does this on the
ComfyUI-WanVideoWrapper stack (kijai) using the WAN 2.2 T2V A14B dual
HIGH/LOW models you already have for wan-t2v-video, plus the small Pusa V1
LoRAs and a Pusa-specific sampling path: the flowmatch_pusa scheduler and
the WanVideoAddPusaNoise node. The input clip is encoded with
WanVideoEncode and injected as the first latents of the generation — that
is what carries the existing motion/content into the continuation.
The official reference graph is kijai's
wanvideo_2_2_14B_Pusa_extension_example_01.json (in
ComfyUI-WanVideoWrapper/example_workflows/). This skill is built directly from
that workflow plus the live node schemas.
Relationship to
wan-t2v-video: Pusa rides on the exact same WanVideoWrapper stack — same T2V A14B HIGH/LOW fp8 models, same UMT5 text encoder, same WAN VAE, same block-swap/torch-compile machinery. The only new downloads are the two Pusa V1 LoRAs (~1.9 GB total). Readwan-t2v-videofirst for the base stack; this skill is the temporal-extension delta on top of it.
⚠️ Verification note: every node, model, LoRA filename and setting below was confirmed against the live ComfyUI
/object_info(WanVideoWrapper installed) and against kijai's example workflow JSON + HF repo (June 2026). Where a value is a starting recommendation rather than a hard requirement it's flagged. Don't substitute a node you can't confirm withlist_installed_nodes/get_node_info.
What "temporal flowmatching" means here (why it extends, not regenerates)
WAN is a flow-matching video model: sampling integrates a velocity field from noise to a clean latent, and every frame normally shares the same denoising timestep. Pusa's contribution (Vectorized Timestep Adaptation) is to make the timestep per-frame: the frames you already have can be held at (or near) t = 0 (clean) while the new frames start from t = 1 (noise), and the model flow-matches the noisy tail conditioned on the clean head.
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 · 522 lines · 146 tokens per session scan A c75d92293701
video-extend is a skill published in the GitHub repository sandyup/comfyui-mcp (1 stars, last pushed 1mo ago), licensed MIT. It adds 146 tokens to every session and 8,029 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to video-extend, differing in 340 lines, and is treated as a copy.
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