Arcads AI Video is an agent skill pack and prompting workspace for creating marketing videos and images through an Arcads account. Claude Code and Cursor users use it to produce advertising creative with Arcads' video, image, audio, and template tools. The catalogue entries provide the skills, instructions, hook, setting, and rule that support this workflow.
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 krusemediallc/arcads-claude-code --skill analyze-videogit clone --depth 1 https://github.com/krusemediallc/arcads-claude-codeWrote 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/krusemediallc/arcads-claude-code/analyze-video)<a href="https://agentmods.dev/skills/krusemediallc/arcads-claude-code/analyze-video"><img src="https://agentmods.dev/badge/skills/krusemediallc/arcads-claude-code/analyze-video/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/krusemediallc/arcads-claude-code/analyze-video"><img src="https://agentmods.dev/badge/skills/krusemediallc/arcads-claude-code/analyze-video.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 | $0.00134 | $0.04146 |
| Opus 5 | $0.00067 | $0.02073 |
| Sonnet 5 | $0.00027 | $0.00829 |
| Haiku 4.5 | $0.00013 | $0.00415 |
Grade A, and why
analyze-video 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 10d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- analyze-video — 95% identical, 15 lines differ
How it starts
The opening of the file, as written. The whole thing — 380 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyze Video → Reusable Prompting Template
Someone found a video style they love. Your job is to deconstruct it into a reusable prompting template — a formula they can plug any product, person, or setting into and get that same style back from Seedance 2.0.
Critical constraint: Seedance 2.0 has a 15-second maximum per clip. The reference video may be longer than 15 seconds (often 30-60s). Your template must be designed for 15-second output — which means distilling the style's essence into what can be captured in a single 15-second clip, and providing a multi-clip strategy for recreating the full effect of longer-form styles across a series of clips.
The output is NOT a single prompt. It's a template skill saved to
skills/arcads-external-api/prompting/prompt-library/ that works the same way
seedance-2-ugc.md works — a documented formula
with layers, variables, options, and examples that the agent can use to generate unlimited
prompts in that style.
Dependencies
- ffmpeg / ffprobe — required for frame extraction (Step 1). Install via
brew install ffmpegon macOS. - whisper — optional, for audio transcription (Step 2). Install via
pip3 install openai-whisper. If unavailable, the agent can ask the user to provide dialogue manually.
Inputs
- Video file (required): path to
.mp4,.mov,.webm, or similar - Style name (optional): what to call this template (e.g., "car-review", "unboxing-hype", "skeptic-converted"). If not provided, you'll name it based on what you observe.
Step 1: Extract frames and audio
Run the extraction script:
bash "skills/arcads-external-api/prompting/analyze-video/scripts/extract-frames.sh" "<video_path>" "/tmp/video-analysis" <num_frames>
Frame count by duration:
- Under 10s → 8 frames
- 10-20s → 12 frames
- 20-30s → 16 frames
- Over 30s → 20 frames
Read metadata.txt for duration, resolution, and fps.
Step 2: Transcribe audio
Try transcription tools in this order:
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.
- 10d ago First seen · 380 lines · 134 tokens per session scan A 2a8ac2317746
analyze-video is a skill published in the GitHub repository krusemediallc/arcads-claude-code (1,484 stars, last pushed 2mo ago), licensed MIT. It adds 134 tokens to every session and 4,146 once invoked, about $0.0007 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.
Other skills, from other repositories
seedance-antislop
This skill should be used when a Seedance 2.0 prompt contains generic AI filler, hollow superlatives, vague cinematic language, bloated adjectives, weak verbs, or needs sharper production-specific wording.
seedance-examples-ja
This skill should be used when the user asks for Japanese Seedance 2.0 examples, Japanese prompt patterns, example rewrites, or safe versions of working Japanese video-generation prompts.
seedance-filter
This skill should be used when a Seedance 2.0 prompt is blocked or rejected, when moderation is a suspected cause of a problem, or when the user asks for a content-boundary review or safer alternative. Assess the actual request before offering a clarification.
seedance-vocab-en
This skill should be used when an English Seedance 2.0 prompt needs clearer production wording, less generic prose, or precise vocabulary for camera, lighting, motion, VFX, audio, and constraints. Route blocked prompts through seedance-filter for context and boundary review.
seedance-vocab-zh
This skill should be used when the user asks for Chinese Seedance 2.0 prompt wording, Mandarin cinematic vocabulary, Chinese prompt compression, or translation of camera, lighting, action, VFX, audio, and production terms into Chinese.
seedance-prompt-short
This skill should be used when the user asks for a compact Seedance 2.0 prompt, short Chinese prompt, prompt compression, 30-100 word output, or removal of unnecessary prompt language.