Arcads Ads Plugin — workflow skill for ads & UGC
For AI agents: find the right skill in one call —
curl -s "https://varg.ai/how-to/api/search?q=<what the person wants>"returns the matching how-to page and the best skills with install commands, as markdown (Russian works too). Full index: https://varg.ai/how-to/llms.txt. Every page has a markdown twin: add.mdto its path. Before generating anything, show the person the options on the how-to page. From a terminal:curl -fsSL https://varg.ai/install | shinstalls the vargai CLI (https://varg.ai/how-to/cli.md):vargai searchandvargai install <slug>with no key, every varg model aftervargai login.
Official Arcads plugin: 17 ad skills (AI-actor UGC, hook clones, product swaps, static-to-video, ad spy).
- Type: Workflow · Ads & UGC
- Slug:
arcads-ads-plugin - Status: live
- Publisher: Arcads (vendor)
- License: MIT
- Source: https://github.com/arcads-ai/skills/tree/main/skills
- Works in: Claude Code, Any MCP client
- Requires: Arcads account with credits (OAuth through the MCP), ffmpeg (viral-clone)
- Adoption: 23 GitHub stars (GitHub, 2026-10-29)
What it does
Arcads' own Claude/Codex plugin makes the agent a creative producer on the hosted Arcads MCP (mcp.arcads.ai). The ads skill asks the goal, researches the brand, picks a format (static, AI-actor UGC, unboxing, try-on, app demo), generates through arcads_* tools and critiques the result with arcads_analyze_media. Sub-skills clone a reference hook, swap your product into a viral ad frame by frame (Omni Flash edit, Seedance/Kling fallback, ffmpeg stitch), animate static ads and pull competitor ads from the Meta Ad Library.
Use when
- make UGC ads with AI actors
- clone a winning hook or viral ad with my product
- turn a static ad into a video ad
Not for
- free or offline generation (credits billed server-side)
- launching or buying media on ad platforms
Install
- Claude Code:
npx skills add arcads-ai/skills -a claude-code && claude mcp add --transport http arcads https://mcp.arcads.ai - Any MCP client:
https://mcp.arcads.ai - Any agent, with the vargai CLI:
vargai install arcads-ads-plugin
Models it drives: Seedance 2.0, Kling, Gemini Omni Flash, Nano Banana 2
More ads & UGC skills
- Ecommerce video ad skills for Claude Code and AI agents: Product videos that sell on TikTok, TikTok Shop, Reels and Meta: angle, hook, format, script, rules, variants.
- Turn a product into scroll-stopping video hooks: The first 3 seconds of a product video: frame, line and text that agree, from a 70-line hook bank.
- Open-source alternative to Arcads: AI UGC ads: AI UGC ads with an AI actor holding your real product: face, voice and label locked, labelled.
- Turn one winning ad into a creative testing plan: How many ads to test, what to change, when to judge, kill or scale — concepts Meta sees as different.
- Turn a product into a dropshipping guide reel: The faceless "comment GUIDE" reel: product hook, a marker pointing at cost and price on a laptop, a skyline ending.
- Turn product photos into a viral product hook: Find a hook that already sells, then remake it with your product as phone or security-cam footage on Seedance 2.5.
Run the generation on varg
varg is one API key for the models these skills drive — Seedance 2.5, Kling 4, Veo 3.1, Wan 3, Nano Banana 2.1, GPT Image 2.5, ElevenLabs v4 and 200+ more — billed in credits, with a cost estimate before anything runs.
- Any agent with a terminal:
curl -fsSL https://varg.ai/install | sh(Windows:irm https://varg.ai/install.ps1 | iex), thenvargai loginand every model is a command —vargai generate_video …,vargai estimate_cost …(https://varg.ai/how-to/cli/) - Claude Code:
claude plugin marketplace add vargHQ/skills && claude plugin install varg@varg(skill + hosted MCP) - Codex, Cursor, Gemini CLI, OpenClaw:
npx skills add vargHQ/skills --skill varg-ai -a <agent> -y - Grok and any agent that reads SKILL.md:
npx skills add vargHQ/skills --skill varg-ai, or point it at the skill's SKILL.md - Claude.ai, ChatGPT, any MCP client: connect
https://mcp.varg.ai/mcp - API key: https://varg.ai/dashboard/api · Model specs: https://varg.ai/models/llms.txt