Bendervintimilla Skills AI Marketing Tool Ads Generate

Ads Generate: AI Ad Image Generator

Generates platform-sized ad creative images from your campaign brief and brand profile. Uses Google Gemini / Imagen 4 via scripts/generate_image.py.

Quick Reference

Environment Setup

Required before running:

• GOOGLE_API_KEY environment variable set (get a key at https://aistudio.google.com/app/apikey)
• google-genai>=1.16.0 installed (included in the skill's requirements.txt)

If GOOGLE_API_KEY is not set, this skill will display setup instructions and stop. It will never fail silently.

Optional alternative providers (OpenAI, Stability AI, Replicate) are documented in ~/.claude/skills/ads/references/image-providers.md. Switch via ADS_IMAGE_PROVIDER env var.

Quality Presets

The --quality flag controls which Google model is used:

Process

Step 1: Verify Prerequisites

Check that GOOGLE_API_KEY is set. If not, display setup instructions:

export GOOGLE_API_KEY="your-key"
# Get a key at https://aistudio.google.com/app/apikey

Step 2: Locate Source Files

Check for:

• campaign-brief.md → primary source for prompts and dimensions
• brand-profile.json → brand color/style injection (optional but recommended)

If campaign-brief.md is found: Use ## Image Generation Briefs section as the generation job list.

If no campaign-brief.md: Enter standalone mode (Step 2b).

Step 2b: Standalone Mode

Ask the user:

1. Generation prompt (what should the image show?)
2. Target platform (to set correct dimensions)
3. Quality preset (pro/high/flash/fast, default: pro)
4. Output filename (optional)

Then skip to Step 5.

Step 3: Read Provider Config

Load ~/.claude/skills/ads/references/image-providers.md to confirm:

• Current model pricing (show user the cost estimate)
• Rate limits for current tier
• Aspect ratio support per model

Step 4: Read Platform Specs

For each platform in the campaign brief, load the relevant spec reference:

• ~/.claude/skills/ads/references/meta-creative-specs.md
• ~/.claude/skills/ads/references/google-creative-specs.md
• ~/.claude/skills/ads/references/tiktok-creative-specs.md
• ~/.claude/skills/ads/references/linkedin-creative-specs.md
• ~/.claude/skills/ads/references/youtube-creative-specs.md
• ~/.claude/skills/ads/references/microsoft-creative-specs.md

Step 5: Select Quality Per Asset

Map each brief entry to the right --quality preset based on its purpose:

Step 6: Spawn Visual Designer Agent

Spawn the visual-designer agent using the Task tool with context: fork, passing the selected quality preset and brand profile.

The agent will:

• Parse the image generation briefs from campaign-brief.md
• Inject brand colors and mood from brand-profile.json into each prompt
• Invoke python ~/.claude/skills/ads/scripts/generate_image.py per asset
• Save to ./ad-assets/[platform]/[concept]/ directory structure
• Write generation-manifest.json

Example call the agent runs:

python ~/.claude/skills/ads/scripts/generate_image.py \
    "Minimalist SaaS dashboard screenshot, dark UI with teal accents, clean data viz" \
    --ratio 16:9 \
    --quality pro \
    --output ./ad-assets/linkedin/concept-1/hero-1920x1080.png \
    --json

Step 7: Validate with Format Adapter

After the visual-designer completes, spawn the format-adapter agent with context: fork to validate dimensions and report missing formats.

Step 8: Quality Gate

Use Claude vision to assess each generated image against the brief (score 1 to 10 on brand alignment, composition, platform fit). If any image scores below 6, regenerate once with an adjusted prompt.

Quality Gate Rubric:

• 9-10: Professional quality, brand-aligned, platform-optimized, no issues
• 7-8: Good quality, minor composition or brand alignment improvements possible
• 5-6: Acceptable but needs regeneration. Text readability issues, poor composition, or brand mismatch
• Below 5: Reject. Regenerate with adjusted prompt

Step 9: Aggregate Costs

Sum costs from each generation's JSON output (script emits quality and model per image). Compute total using the pricing table in image-providers.md and include in generation-manifest.json.

Step 10: Report Results

Present a summary:

Generation complete:

  Generated assets:
    ✓ ./ad-assets/meta/concept-1/feed-1080x1350.png       [quality: pro, $0.134]
    ✓ ./ad-assets/tiktok/concept-1/vertical-1080x1920.png [quality: fast, $0.039]
    ✗ ./ad-assets/google/concept-1/landscape-1200x628.png [error: SAFETY]

  Format validation: See format-report.md

  Cost: $[N] total creative spend (X images)

  Next steps:
    1. Review assets in ./ad-assets/
    2. Check format-report.md for any missing formats
    3. Upload to your ad platform managers

Cost Transparency

Before generating, estimate and show the cost:

• Count the number of image briefs in campaign-brief.md
• Multiply by the per-image cost of the chosen preset
• If total >$1.00, ask for confirmation before proceeding
• Suggest dropping non-hero assets to --quality fast to reduce spend

Standalone Mode (No campaign-brief.md)

When running without a campaign brief:

Platform target → dimensions used:
  meta-feed     → 1080×1350 (4:5)
  meta-reels    → 1080×1920 (9:16)
  tiktok        → 1080×1920 (9:16)
  google-pmax   → 1200×628 (1.91:1)
  linkedin      → 1080×1080 (1:1)
  youtube       → 1280×720 (16:9)
  youtube-short → 1080×1920 (9:16)

Invoke the script directly:

python ~/.claude/skills/ads/scripts/generate_image.py \
    "<prompt>" --ratio <ratio> --quality <preset> --output <file>

Reference Files

• ~/.claude/skills/ads/references/image-providers.md: model config, pricing, limits, presets
• ~/.claude/skills/ads/references/[platform]-creative-specs.md: per-platform specs
• ~/.claude/skills/ads/references/brand-dna-template.md: brand injection schema

Source: bendervintimilla/skills-AI-marketing-tool — distributed by TomeVault.