Ad Designer

Generate marketing ad images from campaign-planner creative briefs. Wrap nano-banana-pro with brand-aware prompt construction, aspect ratio handling, and a self-review loop that catches quality issues before marking images final.

Roles

• - Ad Designer (this skill) — sole executor
• nano-banana-pro — image generation engine (upstream dependency)
• campaign-planner — upstream source of creative briefs
• brand-bible-builder — upstream source of brand visual identity

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Prerequisites

Verify before starting:

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If uv is missing: tell the user to install it with curl -LsSf https://astral.sh/uv/install.sh | sh.
If GEMINI_API_KEY is unset: tell the user to export it from Google AI Studio.
If the script is missing: tell the user the nano-banana-pro skill must be installed first.

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Step 1: Collect Inputs

Identify which inputs are present in the conversation or filesystem:

Input	Source	Where to find it
Creative brief(s)	campaign-planner skill	INLINECODE3 → ad_creatives[] array, or inline in conversation
Brand bible

brand-bible-builder skill | /tmp/marketing/brands/<brand>/brand-bible.md or inline |
| Aspect ratio | User or brief | Defaults to 1:1 if not specified |
| Resolution mode | User | Defaults to draft (1K) unless user says "final" or "4K" |

If the creative brief is missing, ask:

"I need a creative brief to generate the ad. Run /campaign-planner first, or paste the brief details: headline, visual direction, CTA, and target audience."

If the brand bible is missing, proceed with neutral visual defaults — note this in the output and recommend running /brand-bible-builder for on-brand results.

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Step 2: Read Brand Bible Visual Identity

Open the brand bible and extract these fields into a working reference:

• - Primary colors — hex codes or descriptors (e.g. #1A2E5A deep navy, #F5A623 amber)
• Secondary / accent colors — supporting palette
• Font style — serif vs sans-serif, weight, mood descriptor (e.g. "bold geometric sans", "light editorial serif")
• Imagery style — photography vs illustration, lifestyle vs product-only, color grading mood (warm/cool/muted/vibrant)
• Layout pattern — minimal and clean vs content-dense, whitespace-heavy vs layered
• Tone — formal, casual, bold, playful, premium, approachable

Keep this as a 6-field internal reference. Do not show it to the user. Use it when constructing prompts in Step 3.

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Step 3: Construct Image Generation Prompt

Apply these rules every time. They are non-negotiable.

Core Rules (from best-practice image generation)

Rule 1 — Less is more. Short, focused prompts outperform long descriptive ones. Target 15–30 words for the visual description. Cut adjectives that repeat the same idea.

Rule 2 — No logos, brand names, or company names. Never include the brand name, product name, logo description, or any trademark in the prompt. The generation engine hallucinates these badly and they must be added in post-production.

Rule 3 — Only include text that is explicitly specified. If the brief specifies a headline to appear in the image, include it exactly as written — no paraphrasing. If no text is specified, do not add any text to the prompt. Do not include CTAs, taglines, or copy unless the brief explicitly says to render text.

Rule 4 — Describe emotion and composition, not data. Instead of "a woman saving money on her bills," write "confident woman, bright home office, warm morning light, relaxed expression." The emotion communicates the message; the model handles the rest.

Rule 5 — Translate brand colors without naming the brand. Convert hex codes to descriptors: #1A2E5A → "deep navy", #F5A623 → "warm amber". Use these color words in the prompt naturally.

Prompt Construction Formula

Assemble the prompt in this order:

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Do not use all 8 fields every time. Use only those relevant to the brief. A 5-field prompt is often stronger than an 8-field one.

Example Construction

Brief input:
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Brand bible: warm coral #E8735A, off-white #FAF7F2, editorial sans-serif, warm and minimal photography style.

Constructed prompt:
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What was excluded: brand name, CTA text, product name, headline text (no text was specified for visual rendering).

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Step 4: Select Aspect Ratio

Map the brief's platform or format to the correct ratio flag and pixel dimensions:

Platform / Format	Ratio	Pixel Dimensions	Use Case
Instagram / Facebook Feed	1:1	1080 × 1080	Square feed post
Instagram Story / Reel

9:16 | 1080 × 1920 | Full-screen vertical |
| Facebook Feed (portrait) | 4:5 | 1080 × 1350 | Taller feed post, more screen area |
| YouTube / LinkedIn Cover | 16:9 | 1920 × 1080 | Landscape / banner |

If the brief does not specify a platform, default to 1:1.

For carousel ads: generate all cards at the same ratio. Use 1:1 unless the brief specifies otherwise.

Pass the ratio to the script via --resolution. The nano-banana-pro script handles internal sizing. Generate at 1K for drafts, 4K for finals.

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Step 5: Generate Images

Create the output directory:

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Single image generation

Use this command pattern. Always use absolute path for the script.

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Filename format: yyyy-mm-dd-hh-mm-ss-<brief-id>-draft.png

• - brief-id: lowercase kebab-case derived from the brief headline (e.g. finally-sleep-works)
• Use current date/time for timestamp

Draft-first workflow

Always follow this sequence:

1. 1. Draft at 1K — generate first at 1K for fast feedback. Present to user.
2. Iterate — if issues found in self-review (Step 6), adjust prompt and regenerate at 1K. Max 3 attempts.
3. Final at 4K — only after user approves the draft or after self-review passes. Change filename suffix from -draft to -final, set --resolution 4K.

Carousel ads

Generate each card as a separate image. Naming convention:
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Ensure visual consistency across cards:

• - Use the same color palette descriptor in every card's prompt
• Use the same style descriptor in every card's prompt
• Use the same lighting descriptor in every card's prompt
• Vary only the subject and composition per card

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Step 6: Self-Review Loop (CRITICAL)

After generating each image, perform a structured self-review before presenting to the user. Do not skip this step.

Run through this checklist for every generated image:

Check	Pass Condition	Fail Action
Text accuracy	Any specified text appears correctly and is readable	Simplify prompt; add explicit text instruction
No hallucinated logos

No brand marks, wordmarks, icons, or watermarks visible | Add "no logos, no text, no watermarks" to avoid clause |
| No hallucinated brand names | No company names or product names rendered as text | Add "no brand names, no product names" to avoid clause |
| Aspect ratio | Matches requested format | Re-run with correct ratio flag |
| Color alignment | Dominant colors match brand palette intent | Strengthen color descriptors in prompt |
| Overall quality | Image is coherent, professional, on-brief | Rebuild prompt from scratch using simpler structure |

Fail response

If any check fails:

1. 1. Identify the specific failure from the table above.
2. Apply the corresponding fail action to the prompt.
3. Regenerate at 1K.
4. Re-run the self-review checklist on the new image.
5. Stop after 3 total attempts. If still failing on attempt 3, present the best result to the user with a note explaining what the issue is and what was tried.

Do not present a failing image silently. Always tell the user what was wrong and what fix was applied.

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Step 7: HITL — Present for User Review

After self-review passes (or after 3 attempts), present the results:

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Wait for the user's response before generating the 4K final or moving to the next brief.

If the user says "adjust" or describes changes:

• - Apply the change to the prompt (keep changes minimal — one diff at a time)
• Regenerate at 1K
• Re-run self-review
• Present again

If the user approves:

• - Regenerate at 4K with -final filename suffix
• Confirm: "Final saved: /tmp/marketing/assets/images/[filename]-final.png"

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Step 8: Process Multiple Briefs

If the input contains multiple briefs (e.g. from a campaign-planner JSON with 3–5 image ad entries), process them sequentially. Complete the full cycle (generate → self-review → HITL approval → final) for each brief before moving to the next.

After all briefs are processed, present a summary:

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Error Handling

Error	Action
INLINECODE23	Tell user to run export GEMINI_API_KEY=<key> and retry
INLINECODE25

Verify the --input-image path exists; fix path and retry |
| quota / 403 / permission API error | Wrong key or quota exceeded; ask user to check Google AI Studio quota |
| Script not found at ~/.codex/skills/... | nano-banana-pro skill is not installed; tell user to install it from ClawHub |
| uv: command not found | Run curl -LsSf https://astral.sh/uv/install.sh | sh then retry |
| Image generation returns blank/empty | Prompt may be too restrictive; remove avoid clauses and simplify to subject + style only |

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File Paths Reference

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