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 doany-ai/skills --skill ai-video-generationgit clone --depth 1 https://github.com/doany-ai/skillsWrote 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/doany-ai/skills/ai-video-generation)<a href="https://agentmods.dev/skills/doany-ai/skills/ai-video-generation"><img src="https://agentmods.dev/badge/skills/doany-ai/skills/ai-video-generation/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/doany-ai/skills/ai-video-generation"><img src="https://agentmods.dev/badge/skills/doany-ai/skills/ai-video-generation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
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 | $0.00276 | $0.06802 |
| Opus 5.5 | $0.00110 | $0.02721 |
| Sonnet 5.5 | $0.00055 | $0.01360 |
| Haiku 4.5 | $0.00028 | $0.00680 |
Grade A, and why
ai-video-generation 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 2mo 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 ai-video-generation — 0 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 — 425 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Video Generation
Generate videos with the full RunComfy video-model catalog through one CLI — text-to-video, image-to-video, and Veo's video-extend. This skill picks the right model for the user's intent and ships the documented prompt patterns + the exact runcomfy run invoke for each.
runcomfy.com · Video models · CLI docs
Powered by the RunComfy CLI
# 1. Install (see runcomfy-cli skill for details)
npm i -g @runcomfy/cli # or: npx -y @runcomfy/cli --version
# 2. Sign in
runcomfy login # or in CI: export RUNCOMFY_TOKEN=<token>
# 3. Generate
runcomfy run <vendor>/<model>/<endpoint> \
--input '{"prompt": "..."}' \
--output-dir ./out
CLI deep dive: runcomfy-cli skill.
Install this skill
npx skills add agentspace-so/runcomfy-agent-skills --skill ai-video-generation -g
Pick the right model for the user's intent
Text-to-video (t2v) — newest first
HappyHorse 1.0 — happyhorse/happyhorse-1-0/text-to-video (default)
Currently #1 on Artificial Analysis Video Arena. Native synchronized audio generated in-pass (no separate Foley step). Native 1080p, up to ~15s, strong multi-shot character consistency. Pick for: general-purpose t2v, ad creative with audio, social-media clips, multi-shot narratives. Avoid for: audio-driven lip-sync to a specific voiceover MP3 — use Wan 2-7.
Kling 3.0 4K — kling/kling-3.0/4k/text-to-video
Kling's latest, 4K output, strong multi-shot character identity, premium camera language. Pick for: hero shots, final-delivery 4K cuts, multi-shot character narratives. Avoid for: cost-sensitive iteration — drop to Kling 2-6 Pro or Standard i2v.
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.
- 2mo ago First seen · 425 lines · 276 tokens per session scan A 76511e833124
ai-video-generation is a skill published in the GitHub repository doany-ai/skills (5 stars, last pushed 5mo ago), licensed MIT. It adds 276 tokens to every session and 6,802 once invoked, about $0.0011 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to ai-video-generation, differing in 0 lines, and is treated as a copy.
ai-video-generation compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| ai-video-generationdoany-ai/skills | Skill | 5 | 5mo ago | MIT | A | 276 | Claude Code |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | yesterday | MIT | A | 200 | Claude Code, Codex |
| playwright-climicrosoft/playwright | Skill | 100k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| browser-automationopenclaw/openclaw | Skill | 394k | today | MIT | A | 36 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 314k | 4d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |