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 chadixearth/graphyloop --skill video-ai-automationgit clone --depth 1 https://github.com/chadixearth/graphyloopWrote 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/chadixearth/graphyloop/video-ai-automation)<a href="https://agentmods.dev/skills/chadixearth/graphyloop/video-ai-automation"><img src="https://agentmods.dev/badge/skills/chadixearth/graphyloop/video-ai-automation/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/chadixearth/graphyloop/video-ai-automation"><img src="https://agentmods.dev/badge/skills/chadixearth/graphyloop/video-ai-automation.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 | $0.00057 | $0.00810 |
| Opus 5 | $0.00028 | $0.00405 |
| Sonnet 5 | $0.00011 | $0.00162 |
| Haiku 4.5 | $0.00006 | $0.00081 |
Grade A, and why
video-ai-automation 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 6d 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 — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Video AI Automation
1. Overview
Faceless AI video pipeline: script → AI voiceover → AI clips/stills → captions → music → export 9:16.
Niche beats production quality: "YouTube doesn't care who is talking, it only cares whether people keep watching."
2. Winning Niches
| Niche | Why it works | Notes |
|---|---|---|
| History / boring-history documentaries | Older affluent audience, high RPM | Videos from ~$60 cost, margins 85-89%, AdSense long-form |
| Space / science news | Evergreen search | e.g. "what did the James Webb telescope find" |
| Unsolved mysteries / cold cases | Watch-time loyalty | Avoid oversaturated cases; use historical/uncovered cases |
| Odd facts / "worth more than you think" | Beginner entry | Production quality barely matters |
| Survival myths / frontier history | Strong repeat audience | Steady view pattern |
| Niche hobby / collector (aircraft, ships, tools) | Consistent growth | Audience buys, good affiliate fit |
| AI-narrated character / storytelling | Highest ceiling via recognizable brand | Most setup, brand compounds |
3. Monetization Ladder
- AdSense — long-form, multiple ad breaks, high RPM
- Affiliates / reviews — commission per video
- Sponsors — only at scale
4. Growth Patterns
- Volume + consistency: algorithm needs data points; 2-3 weeks of consistent posting can break through
- Double-down on outliers: find the video beating your sub count, repeat that angle
- Real photos beat AI images for thumbnails
- Evaluate niche on: RPM, view velocity, saturation risk, format simplicity
5. Tool Stack (2026)
| Stage | Tool | Notes |
|---|---|---|
| Script | LLM + story-engineering skill | structure via story-engineering |
| Voiceover | ElevenLabs | quality leader |
| Voiceover | MiniMax TTS | cheapest volume |
| Voiceover | OpenAI gpt-4o-mini-tts | budget option |
| Video clips | Veo 3.1 | native audio, camera controls |
| Video clips | Kling 3.0 | cheap, native 4K |
| Video clips | Seedance | budget |
| Video clips | Runway / Pika / Luma | alternatives |
| Video clips | Sora | DISCONTINUED (app Apr 2026, API Sep 2026) — do not recommend |
| Images | Midjourney V7 | hero stills |
| Images | Flux | Ken Burns fallback |
| Captions | CapCut auto-captions, Whisper | word-sync |
| Edit | CapCut, Descript | assembly + cleanup |
| Music | Suno, YouTube Audio Library | library is safe for monetization |
| Rendering | HyperFrames | HTML/CSS-keyframe, local, deterministic, no per-clip API cost — strong for text/data-driven channels |
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.
- 6d ago First seen · 75 lines · 57 tokens per session scan A 6980710b0c30
video-ai-automation is a skill published in the GitHub repository chadixearth/graphyloop (2 stars, last pushed 24d ago), licensed MIT. It adds 57 tokens to every session and 810 once invoked, about $0.0003 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 2026-09-03.
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