# Moizibnyousaf Marketing CLI Image Gen

> Moizibnyousaf Marketing Cli Image Gen

- Skill: `tomevault-io/moizibnyousaf-marketing-cli-image-gen` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add tomevault-io/moizibnyousaf-marketing-cli-image-gen`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/moizibnyousaf-marketing-cli-image-gen/raw
- Safety review: pending (external: skill-scanner PASS, skillspector CAUTION)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Marketing & Growth
- Author: tomevault-io (https://skillmd.com/u/tomevault-io)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/tomevault-io/moizibnyousaf-marketing-cli-image-gen

---


# /image-gen — On-Brand Image Generation

Describe what you need. Get an image that looks like your brand made it.

This skill reads your visual brand identity from `brand/creative-kit.md`, crafts a narrative prompt that bakes in your style constraints, and generates the image via Gemini API. No brand style defined yet? It still works — just at a lower enhancement level. Run `/visual-style` first for the best results.

---

## On Activation

1. Check `GEMINI_API_KEY` environment variable.
   - If missing: "Image generation requires a Gemini API key. Set GEMINI_API_KEY in your environment. Get one at ai.google.dev."
   - Do not proceed without it.

2. Read brand files in priority order:
   - `brand/creative-kit.md` — look for `## Visual Brand Style` section
   - `brand/voice-profile.md` — personality informs image tone
   - `brand/positioning.md` — angles inform visual metaphors
   - `brand/landscape.md` — Claims Blacklist (don't generate imagery that visually implies blacklisted claims)

3. Determine enhancement level:

| Level | Context available | Image quality |
|-------|------------------|---------------|
| L0 | No brand files | Good generic images — uses discovery questions + prompt craft |
| L1 | voice-profile.md | Personality-aligned — playful brand gets warm/bright images |
| L2 | + creative-kit.md colors/typography | Color-constrained — palette woven into prompts |
| L3 | + Visual Brand Style section | Fully on-brand — style anchors, lighting, mood, composition all applied |

---

## Phase 1: Discovery

Use AskUserQuestion. Ask one at a time. Skip questions the user already answered in their request.

**Question 1: Purpose**
"What's this image for?"
- Blog header / article illustration
- Social media post (which platform?)
- Product shot / marketing asset
- Hero image / landing page
- Presentation / slide deck
- Something else (describe it)

This determines aspect ratio:

| Use case | Default ratio | Resolution |
|----------|---------------|------------|
| Blog header | 16:9 | 2K |
| Social square | 1:1 | 2K |
| Social story | 9:16 | 2K |
| Hero / banner | 21:9 | 2K |
| Product shot | 4:3 | 4K |
| Thumbnail | 16:9 | 1K |

**Question 2: Feeling**
"What should someone feel when they see this?"
(Free text — this drives the prompt's emotional anchor)

**Question 3: Style override** (only if L3 brand style exists)
"Use your on-brand style, or something different?"
- On-brand (default) — applies Visual Brand Style from creative-kit.md
- Different — describe the style you want instead

If user picks "different," their description overrides the brand style for this image only.

**Skip discovery when:** The user's request is specific enough. "Generate a 16:9 blog header showing a glowing terminal on a dark background, warm rim lighting" — don't ask what they want, they just told you.

---

## Phase 2: Prompt Crafting (Nano Banana Prompt Engineering)

You are an expert Nano Banana prompt engineer. Your job is to turn the user's brief into a single, high-quality prompt for Nano Banana 2 (or Pro), a "thinking" image model used for professional asset production.

**Core principle: brief a senior art director, don't list keywords.** Write natural language in full sentences. Never use "tag soup" like "dog, park, 4k, realistic."

### The 10 Rules

**1. General style.** Be specific and descriptive about subject, setting, composition, camera/viewpoint, lighting, mood, materials, and textures. Full sentences, not comma lists.

**2. Context and purpose.** Always encode the purpose and audience (YouTube thumbnail, app icon, hero banner, tweet graphic, 4K wallpaper). Let purpose guide style, polish level, and framing.

**3. Text and infographics.** If text must appear, put it clearly in quotes in the prompt. Ask for legible, clean typography and specify style (bold sans-serif, monospace, handwritten). For data, ask the model to compress into infographics, diagrams, or whiteboards.

**4. Character and brand consistency.** When reference images exist, explicitly refer to them: "Keep the person's facial features exactly the same as Image 1." Allow changes in pose, expression, angle while preserving identity.

**5. Grounding and realism.** For real data, locations, or products, tell the model to rely on up-to-date factual knowledge. Encourage coherent details consistent with physics.

**6. Editing and restoration.** For edits to existing images, give semantic instructions: "remove," "replace," "add," "restore," "change the season." Maintain original structure, only change what's intended.

**7. Dimensional and structural control.** For floor plans, schematics, wireframes, grids, tell the model to follow that layout closely. For 2D↔3D, describe how the new representation should look while preserving key relationships.

**8. Resolution, detail, and format.** Specify resolution ("high detail suitable for 4K wallpaper," "clean 16:9 thumbnail"). Call out micro details and textures when needed (brushed steel, cracked paint, mossy stone).

**9. Narrative and sequences.** For multiple images, describe the story arc, emotional beats, what stays consistent across images. Specify count, format, and identity/style consistency.

**10. Output rules.** Do not ask follow-up questions about the prompt. Resolve small ambiguities with sensible professional defaults. Output a single flowing narrative prompt.

### Prompt Structure

Build the narrative in this order, woven into flowing prose:

1. **Purpose and format** — what this is for, aspect ratio, resolution
2. **Scene** — what's happening, where, environment
3. **Subject** — detailed description with textures, materials, poses
4. **Composition** — framing, focal point, depth of field, negative space
5. **Lighting** — source, quality, color temperature, interaction with materials
6. **Mood** — emotional tone, atmosphere
7. **Text** — any text in quotes with typography specification
8. **Technical** — camera/lens for photorealistic, style reference for illustrated

### Brand Constraints (L3)

When Visual Brand Style exists, weave constraints INTO the narrative — don't add as a separate block:

- Primary Aesthetic → sets overall style direction
- Lighting → overrides generic lighting with brand-specific lighting
- Backgrounds → constrains background treatment
- Composition → constrains layout/framing
- Mood → anchors emotional tone
- Avoid → explicit exclusions baked into prompt
- Reference Prompts → use as structural templates, adapting subject matter

See [references/prompt-patterns.md](references/prompt-patterns.md) for proven patterns.
See [references/visual-metaphors.md](references/visual-metaphors.md) for concept-to-metaphor mapping.

---

## Phase 3: Generate

### Gemini API Call

```python
import os
from google import genai
from google.genai import types

client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])

response = client.models.generate_content(
    model="gemini-3.1-flash-image-preview",
    contents=["<narrative prompt>"],
    config=types.GenerateContentConfig(
        response_modalities=['TEXT', 'IMAGE'],
        image_config=types.ImageConfig(
            aspect_ratio="<ratio>",
            image_size="<resolution>",
        ),
    ),
)

for part in response.parts:
    if part.text:
        print(part.text)
    elif part.inline_data:
        image = part.as_image()
        image.save("output.png")
```

**Default to `gemini-3.1-flash-image-preview` (Nano Banana 2).** Launched Feb 26, 2026. Pro quality at Flash speed/pricing. 4K support, up to 14 reference images for style consistency. Use `gemini-3-pro-image-preview` (Nano Banana Pro) only when text-heavy infographics or premium quality justify the higher cost.

### Save and Log

1. Save image to project directory (e.g., `images/`, `assets/`, or wherever the project keeps visuals)
2. Append to `brand/assets.md`:
   ```
   | <date> | image | <file-path> | image-gen | <1-line description of what was generated> |
   ```

---

## Phase 4: Iterate

After generating, show the image and offer:

"Image generated. Want me to:"
1. Adjust the lighting or mood
2. Change the composition or framing
3. Try a completely different approach
4. Generate more variations
5. Ship it

For adjustments, use Gemini's multi-turn chat API for iterative refinement — pass the previous image + adjustment prompt.

```python
chat = client.chats.create(model="gemini-3-pro-image-preview")
response = chat.send_message("Make the lighting warmer and add more negative space on the left for text")
```

---

## Image Editing

When the user provides an existing image to modify:

```python
from PIL import Image

img = Image.open("input.png")
response = client.models.generate_content(
    model="gemini-3-pro-image-preview",
    contents=["<edit instruction>", img],
    config=types.GenerateContentConfig(
        response_modalities=['TEXT', 'IMAGE'],
    ),
)
```

Supports: style transfer, background replacement, object removal, color grading, text overlay.

---

## Claims Blacklist Awareness

If `brand/landscape.md` exists, check the Claims Blacklist before generating:
- Don't generate imagery that visually implies "the only X" if that claim is blacklisted
- Don't generate competitor comparisons that misrepresent the competitive landscape
- When in doubt, describe the concept to the user and ask if it implies a blacklisted claim

---

## Anti-Patterns

| Anti-pattern | Why it fails | Instead |
|-------------|-------------|---------|
| Listing comma-separated keywords | "professional, modern, tech, blue, minimal" produces generic AI art | Write a narrative: "A single glowing terminal on a dark slate desk, soft amber rim lighting catching the screen edges" |
| Ignoring aspect ratio | Generating 1:1 for a blog header means the user has to crop, losing composition | Always ask where the image goes FIRST — ratio determines everything |
| Overriding brand style silently | User defined a visual brand identity for consistency — ignoring it defeats the purpose | Default to brand style. Only override when user explicitly asks for something different |
| Generating without purpose | "A nice image" produces nothing distinctive | Every image needs a purpose (blog header, social, hero) and a feeling (trust, excitement, calm) |
| Saving as JPEG when PNG needed | Gemini returns JPEG by default — transparency and quality loss | Always convert to PNG with `image.save("output.png", format="PNG")` |
| Skipping the assets log | Future agents won't know what images exist, leading to duplicate generation | Always append to brand/assets.md after generating |

---

## Related Skills

- **/visual-style** — builds the Visual Brand Style section this skill reads
- **/creative** — produces multi-mode creative briefs (not pixels). Route here for ad concepts and video scripts
- **/paper-marketing** — designs in Paper MCP. Route here for carousels, slideshows, and social graphics designed as HTML
- **/app-store-screenshots** — specialized screenshot generator for App Store listings

---
> Source: [MoizIbnYousaf/marketing-cli](https://github.com/MoizIbnYousaf/marketing-cli) — distributed by [TomeVault](https://tomevault.io).
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