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 skills add wolfenazz/YzPzCode --skill video-shortformgit clone --depth 1 https://github.com/wolfenazz/YzPzCodeWrote 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/wolfenazz/yzpzcode/video-shortform)<a href="https://agentmods.dev/skills/wolfenazz/yzpzcode/video-shortform"><img src="https://agentmods.dev/badge/skills/wolfenazz/yzpzcode/video-shortform/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/wolfenazz/yzpzcode/video-shortform"><img src="https://agentmods.dev/badge/skills/wolfenazz/yzpzcode/video-shortform.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00102 | $0.01106 |
| Opus 5.5 | $0.00041 | $0.00442 |
| Sonnet 5.5 | $0.00020 | $0.00221 |
| Haiku 4.5 | $0.00010 | $0.00111 |
Grade A, and why
video-shortform 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 1mo 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
100% identical to video-shortform — 4 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 — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Video Shortform Skill
Short-form (≤ 10s) is the sweet spot for current text-to-video models — they're great at one shot with one idea, weaker at multi-cut narratives. Plan one shot per call.
Special case: hyperframes-html is not a photoreal text-to-video
model. It's a local HTML-to-MP4 renderer. For that model, do not roleplay
cinematography or "real-world" camera physics. Treat the brief as a motion
design card / title-frame / product interstitial, ask at most one
clarifying question, then dispatch immediately.
Resource map
video-shortform/
├── SKILL.md
└── example.html
Workflow
Step 0 — Read the project metadata
videoModel, videoLength (seconds), videoAspect. These are
hard-locks — clamp the prompt to whatever the chosen model supports
(Seedance 2 caps at 10s; Kling 4 supports up to 10s + image-to-video;
Veo 3 supports 8s with audio).
Step 1 — Plan the shot
Write the shotlist BEFORE calling the model:
| Slot | Content |
|---|---|
| Subject | What's in frame? |
| Camera | Static / pan / push-in / orbit? |
| Lighting | Key direction + temperature |
| Motion | What moves, at what pace? Subject motion vs camera motion. |
| Sound | Ambient bed? (only if the model supports audio) |
Normally, show this to the user as a one-sentence plan before dispatching — they can redirect cheaply.
For hyperframes-html, skip the extra pre-dispatch narration once the
user has answered the discovery form. Collapse the plan into the actual
generation prompt and dispatch immediately.
Step 2 — Compose the prompt
Use the format the upstream model prefers (Seedance: motion + camera +
mood; Kling: subject + camera + style; Veo: subject + cinematography +
sound). Bind the project's videoAspect and videoLength directly to
the API parameters; never put them in prose.
For hyperframes-html, write a concise motion-design brief instead of a
camera-realism prompt. Focus on subject, layout, palette, motion
character, and overall tone. Do not spend turns narrating environment
checks, missing side files, or "I am about to dispatch" status updates.
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.
- 1mo ago First seen · 129 lines · 102 tokens per session scan A a14393165bd3
video-shortform is a skill published in the GitHub repository wolfenazz/YzPzCode (20 stars, last pushed yesterday), licensed Apache-2.0. It adds 102 tokens to every session and 1,106 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to video-shortform, differing in 4 lines, and is treated as a copy.
Other skills, from other repositories
antv-x6-editor
A skill for creating and troubleshooting interactive diagrams with AntV X6, a JavaScript engine for editors made of connected nodes and lines. It supports diagram types such as flowcharts, dependency graphs, entity-relationship diagrams, and organization charts.
gpt-vis
A chart-generation tool that recommends visual formats for data and produces either chart settings or runnable code. It uses GPT-Vis, a library for rendering data visualisations.
antv-infographic
Create beautiful infographics based on given text content. Use when users request to create infographics.
alive-health
Flag walnuts past their rhythm -- health check for the world.
a-share-swing-sniper
A rule-based method for selecting Chinese stocks near the market close and deciding whether to trade or sell on the following day.
ai-image-to-pptx
A workflow that creates a set of related images with AI and places them into a real PowerPoint file. The resulting .pptx file can be opened and edited in PowerPoint, Keynote, or WPS.