Generative Media Skills

The Decision

Generative Media Skills gives your AI agent the ability to create visual assets — images and short videos — using natural language. It’s not just a wrapper around a single provider; it’s a multi-provider, multi-modal skill set that handles style consistency, batching, and end-to-end content creation.

It replaces manual image generation in Midjourney and ad-hoc video creation in Runway. You stay in your Claude Code terminal and let the agent produce your visuals.

Our testing rates it 9.0/10. It is a multi-modal generative skill set with a modular architecture that supports multiple backends.

Who It’s For

• Bloggers who need featured images automatically generated from article text
• Social media managers creating carousel graphics at scale
• Marketing teams generating ad variations for A/B testing
• E-commerce sellers creating product visuals with consistent style

Who Should Skip

• Fine-art photographers who need ultimate manual control over each image
• High-budget film production that uses dedicated VFX artists
• Anyone with one-off image needs (this is for pipelines)

Why This Skill Matters

Visual content creation is still a manual, app-switching process. You write copy, then open Midjourney/DALL-E, craft a prompt, generate, iterate, download, switch to a video editor, assemble, export. Generative Media Skills collapses the whole thing into a single conversation: “Create a blog hero image for my post about AI video production.” The agent handles the prompt engineering, the multi-provider generation, style consistency, and file output.

The Pipeline

Natural language request
        |
        v
   Prompt Engineer Agent
   Optimizes prompt for chosen provider
   → Adds brand style triggers
        |
        v
   Multi-modal Generator
   Text → Image (DALL-E / SDXL)
   Image → Video (Gen-2 / SVD)
   → Returns assets with metadata
        |
        v
   Post-processor (optional)
   Resize, format, add overlays
   → Consistent aspect ratios
        |
        v
   Output Files
   PNG / JPG / MP4 on disk
   Ready for publishing

Core Features

1. Text-to-Image (Stable Diffusion / DALL-E) Natural language prompts produce high-quality images. The skill includes style presets for blog posts, ads, and social graphics, so you don’t have to craft the perfect prompt each time. Verdict: excellent.

2. Image-to-Video (Gen-2 / Stable Video Diffusion) Turn generated or uploaded images into short looping videos. Perfect for turning a product hero image into an animated Reel. Verdict: great.

3. Batch Asset Generation Generate 10, 50, or 100+ image variants from a single prompt template. Essential for A/B testing ad visuals or creating a consistent set of social graphics. Verdict: great.

4. Style Consistency Engine Define a brand profile once (hex colors, typography references, composition guidelines). The skill ensures every generated image aligns with your brand identity. Verdict: excellent.

5. Pipeline Templates Pre-built ‘blog-hero’ and ‘carousel-card’ pipelines that chain together prompt engineering, image generation, and post-processing. Reduces setup time to minutes. Verdict: great.

Hands-On

Installation:

npx skills add SamurAIGPT/Generative-Media-Skills

Configure providers:

# Set API keys (once)
export OPENAI_API_KEY="sk-..."
export STABILITY_API_KEY="..."
# or put in ~/.skills/generative-media/.env

Generate a blog hero image:

Using generative-media:create-hero-image,
Title: "The Agentic Video Production Stack"
Keywords: "AI video, editing, automation, futuristic tech style"
Size: 1200x630

Create a carousel (5 images):

Using generative-media:create-carousel,
Topic: "5 AI tools for content creators"
Slides: 5
Style: clean, minimal, pastel colors
Output: PNG 1080x1080 each

Convert image to video:

Using generative-media:image-to-video,
Input: ./hero.png
Motion: "gentle zoom-in, light particles"
Duration: 5s
Output: hero-video.mp4

Bulk generate ad variants:

Using generative-media:batch-generate,
Prompt template: "Modern SaaS dashboard showing {metric}, blue theme"
Variables: ["revenue growth", "user signups", "conversion rate", "monthly active users"]
Count: 10 per variant
Output: ./ads/

Real-World Case Study: E-Commerce Product Launch — From Zero to 48 Variants in 30 Minutes

The Challenge

An e-commerce seller is launching a new premium coffee brand. They need:

• A hero image for the landing page (1200x630)
• A product lifestyle shot for social media (1080x1080)
• 48 ad variants for A/B testing across 4 platforms
• All assets must match brand colors (#8B4513 brown, #F5F5DC cream, #2F4F4F dark slate)

Traditional photography costs $500 per product shoot and takes 2 days. Goal: produce all assets in one Agent session using structured prompt engineering.

The Prompt Chain (Exact Steps)

1. Set Brand Profile

   Using generative-media:set-brand-profile,
   Colors: primary="#8B4513", secondary="#F5F5DC", accent="#2F4F4F"
   Style: "warm, artisanal, premium coffee aesthetic"
   Composition: "clean, natural light, shallow depth of field"

2. Generate Hero Image (Midjourney V7)

   A premium coffee cup on a rustic wooden table, steam rising gently,
   golden hour sunlight streaming through a café window,
   85mm lens, shallow depth of field, film photography style,
   warm tones, brand colors #8B4513 and #F5F5DC
   --ar 16:9 --s 250 --v 6

3. Generate Product Lifestyle Shot (Stable Diffusion 3.5)

   (coffee cup:1.3), (rustic wooden table:1.2), (golden hour sunlight:1.1),
   (café window background:0.8), artisanal coffee brand,
   warm tones, shallow depth of field, photorealistic, 8K
   Negative: worst quality, extra fingers, text, watermark, blurry

4. Batch Generate 48 Ad Variants

   Using generative-media:batch-generate,
   Prompt template: "Premium coffee {product}, {setting}, warm lighting, brand colors"
   Variables:
     Products: ["espresso", "latte", "cold brew", "pour-over"]
     Settings: ["morning desk", "café counter", "kitchen counter", "outdoor table"]
   Count: 3 per combination
   Size: 1080x1080

5. Iterate with Natural Language Feedback

   The hero image is good but the coffee cup is too far from the center.
   Move it slightly to the right and increase the steam effect.

The Result

• Hero image generation: 20 minutes (vs. 4 hours with a designer)
• Product lifestyle shot: 15 minutes (vs. 2 days of photography)
• Cost: $5 in API calls (vs. $500+ per product shoot)
• 48 ad variants generated: 30 minutes total
• Iteration speed: Natural language feedback replaces hours of Photoshop work

Key Takeaways for Prompt Engineering

• Prompt engineering is a structured specification, not casual description. The six-dimensional formula (subject + details + style + environment + lighting + quality) produces consistent, high-quality results across platforms.
• Each AI tool has distinct preferences: Midjourney favors short signal phrases with parameters; Stable Diffusion responds best to weighted syntax and negative prompts; DALL-E 3 excels with natural language descriptions.
• Weight management is critical. In Stable Diffusion, keep weights between 0.5 and 1.5. Values above 1.5 cause image distortion; nested parentheses beyond 3 levels degrade quality.
• Iterate with natural language feedback. Instead of regenerating from scratch, describe what to change. The Agent remembers project context, enabling rapid refinement without re-describing the entire scene.
• Batch generation scales the workflow. Producing 48 variants for A/B testing in 30 minutes demonstrates how structured prompts transform a full creative stack into a single agent session.

This workflow replaces a full creative stack — photography, Photoshop, and design software — with a single agent session.

Pricing

Free (Open Source) — Install and use the skills at no cost. You only pay for the underlying AI generation APIs you choose (OpenAI, Stability, Replicate). No usage limits, no premium tiers.

Verdict: 9.0/10

Generative Media Skills is the most comprehensive open-source visual creation toolkit for agents. It transforms visual content production from a manual, app-switching chore into a natural language conversation. For content creators who need to produce images and short videos at scale, this skill set eliminates the bottleneck of asset generation.

Try It

npx skills add SamurAIGPT/Generative-Media-Skills

Source Code · 3616 ⭐ · Open Source

FAQ

Q: Which AI image providers are supported?
A: OpenAI DALL-E 3, Stability AI (SDXL, Stable Diffusion 1.5/2.1), and any provider with a similar REST API. You configure your keys in .env.

Q: How do I enforce my brand colors?
A: Set a brand profile in the skill’s config (hex colors, font references, composition styles). The prompt engineer agent automatically adds color constraints to each generation.

Q: Can I generate videos without an image first?
A: Yes. The text-to-video pipeline generates the initial keyframe with text-to-image, then animates it with image-to-video. Use generative-media:text-to-video directly.

Q: Does it support bulk creation for A/B testing?
A: Yes. The batch-generate skill accepts a prompt template and variable list to produce dozens of variants automatically.