banner-maker

Distinct from flyer-maker:

• Smaller aspect ratios (mostly horizontal, often extreme like 728×90 or 1456×180)
• Dense text + CTA conventions (ad copy, not editorial)
• Per-preset standard sizes (no custom aspects in v1)
• "Ad feel" aesthetic — direct, conversion-focused, brand-loud

Distinct from cover-maker / thumbnail-maker:

• No artist / author / title-as-subject
• Standard ad-platform sizes (presets, not "medium")
• Includes explicit CTA element
• Very small visual zones in some presets (300×250 has ~80% text)

This skill does NOT:

• Generate animated banners (HTML5 / GIF) — static PNGs only
• A/B test variants for click-through — generate options, you measure
• Place actual brand logo file in pixel-perfect position — model approximates; for exact placement use a vector design tool
• Match exact platform ad-creative spec (file size, character limits) — that's downstream QA

ROLE

Read headline + CTA + brand + style + presets → pick text-strong model → assemble per-preset prompts with composition zones (headline / subhead / CTA / brand mark zone) → batch execute → save PNGs.

PIPELINE

1. Resolve content:

   • Required: --headline "<text>" (the dominant text — 3-7 words ideal)
   • Required: --cta "<text>" (e.g., "Start free trial", "Learn more", "Get the demo")
   • Strongly recommended: --brand "<name>"
   • Optional: --subhead "<text>", --logo <path-or-url>

2. Resolve presets — multi-preset batch:

   • --presets og,linkedin-ad,leaderboard — comma list (default og,linkedin-ad)
   • Available presets:
     • og — 1200×630 (OG image / Twitter card preview / blog header)
     • linkedin-ad — 1200×627 (LinkedIn Sponsored Content)
     • facebook-ad — 1200×628 (Facebook News Feed ad)
     • twitter-card — 1500×500 (Twitter profile header / large card)
     • leaderboard — 1456×180 (Google Display 728×90 scaled 2× for retina)
     • medium-rectangle — 600×500 (Google Display 300×250 scaled 2×)
     • mobile-banner — 640×200 (Google Display 320×100 scaled 2×)
     • wide-skyscraper — 320×1200 (Google Display 160×600 scaled 2×)

3. Resolve style — see references/style-presets.md:

   • --style auto: picks vibrant + text-friendly carousel style
   • --style swiss-grid-poster — clean editorial
   • --style gradient-mesh-modern — vibrant tech
   • --style brutalist-grid — high-contrast / bold

4. Pick model:

   • Default: ideogram-3-quality — best embedded text
   • Alt: gpt-image-2 (better for illustrated visual element)
   • With logo reference: nano-banana-pro (preserves brand mark)

5. Compose ONE LLM call — load common/visual-prompt-library/system-prompt.md (shared SYSTEM_PROMPT) and buildUserMessage(opts) with Mode=banner, N=<presets count>, headline + CTA + brand + subhead + style + per-preset aspect ratios. Spawn ONE Agent. Receives JSON {"slides":[{"number":1,"prompt":"..."}]} — 1–3 sentence prompts per preset following composition-zone hints (see references/composition-zones.md: leaderboard/mobile horizontal → headline LEFT + CTA RIGHT; medium-rectangle/OG balanced → headline TOP + visual MIDDLE + CTA BOTTOM; skyscraper vertical → headline TOP + CTA BOTTOM). Headline + CTA + brand in double quotes. Library styles via common/visual-prompt-library/styles/_index.md.

6. Estimate cost + confirm — inherits SKILLS_CAROUSEL_BUDGET=1.50.

7. Batch execute — common.runners.batch.run_batch().

8. Output:

   ./generated/banner/<slug>/
     og.png
     linkedin-ad.png
     leaderboard.png
     manifest.json
     style-used.md
     prompts.md
   

MODES

Required

• banner-maker --headline "<text>" --cta "<text>"

Recommended

• --brand "<name>"

Optional content

• --subhead "<text>"
• --logo <path-or-url> — brand mark reference
• --lang en|ru — language hint (default: auto-detect)

Visual

• --presets og,linkedin-ad,leaderboard,medium-rectangle,mobile-banner,wide-skyscraper,facebook-ad,twitter-card — comma list (default og,linkedin-ad)
• --style auto|<library-id> — visual style
• --style-mod "<override>" — tweak
• --variants N — variants per preset (default 1)
• --model auto|<slug> — image provider

Execution

• --execute — actually generate
• --output <dir> — custom output
• --parallelism N — concurrent calls (default 2)
• --yes — skip cost confirmation
• --resume — retry failed
• --prompts-only — dry run

STRUCTURED LAYOUT (Ideogram 4 only)

When --model is an ideogram-4* tier, emit the layout as structure instead of flattening it into a sentence: add json_prompt to each plan item's kwargs, following common/references/json-prompt.md. This skill already knows where every element goes; sending that directly is what stops the arrangement drifting between variants.

On any v3 tier the provider refuses a json_prompt rather than ignoring it, so keep the prose prompt as written and send nothing extra.

REFERENCES (load on demand)

File	When to load
references/aspect-presets.md	Step 2 — exact pixel dimensions per preset + platform target
references/composition-zones.md	Step 5 — per-preset composition templates (where headline / CTA / visual go)
references/style-presets.md	Step 3 — which library styles work as ad anchors
references/troubleshoot.md	When text wraps wrong, CTA gets lost, extreme aspects fail

EXAMPLES

See examples/before-after.md — 3 calibration runs: SaaS launch (OG + LinkedIn), Google Display leaderboard + medium rectangle, conference event Twitter card.

CONSTRAINTS

• Headline ≤7 words. Past 7, text gets crowded in narrow presets (leaderboard, mobile-banner).

• CTA is short. "Start free trial" / "Learn more" / "Get demo". Never longer than 4 words.

• Brand mark is small. Logo / wordmark sits in a corner (top-left or bottom-right). Doesn't dominate the composition.

• Extreme aspects are unforgiving. Leaderboard (1456×180) and mobile-banner (640×200) have very limited vertical real estate. Headline must fit one line. Skill auto-truncates to 5 words for these presets.

• Default model is text-rendering-strongest. ideogram-3-quality is the default — ad banners live and die on legibility.

• One brand voice per batch. All presets share the same headline / CTA / style. Run multiple batches for A/B tests.

• Cost confirm ONCE per batch. Sum across presets × variants.

• Per-platform spec compliance is YOUR responsibility. Google Display has limits (150KB file size, JPG/PNG/GIF). LinkedIn caps at 5MB. We output PNG — you may need to compress before upload.

• Logo file is approximated, not pixel-replicated. Model places "logo region" near a corner; exact mark replacement is a downstream design-tool step.

• Never print API keys. Mask in errors.

INVOCATION HINTS

When the user says any of:

• "banner ad", "display ad", "Google Display creative"
• "OG image", "Twitter card", "LinkedIn ad creative"
• "Facebook ad image", "social ad"
• "баннер для рекламы", "OG-картинка", "креатив для рекламы"
• "превью для шарения" / "preview image for sharing"

Map "social preview / OG / шарилка" → og preset (1200×630). Map "LinkedIn ad" → linkedin-ad. Map "Google Display" → leaderboard + medium-rectangle (the two most-used IAB sizes). Map "Twitter card / header" → twitter-card.

Defaults: --presets og,linkedin-ad --variants 1 --style auto --model ideogram-3-quality. Without --execute, returns prompts.

This skill is distinct from:

• cover-maker — book/album/podcast covers with title+creator
• flyer-maker — event posters with date+location+CTA
• thumbnail-maker — 16:9 content marketing with face+title
• logo-maker — brand mark only (no headline/CTA)
• quote-card-maker — text-dominant (no CTA / brand emphasis)
• image-prompt — free-form (no platform presets)