| name | ls-gen-image-or-video |
| description | Use when generating AI images or videos — marketing visuals, hero banners, social media assets, product mockups, ad creative, animated backgrounds, exploding views, 3D renders, scroll-synced video assets. Triggers on 'generate an image', 'create an image', 'gen-image', 'make me an image', 'image gen', 'marketing image', 'product mockup', 'hero image', 'generate a video', 'create a video', 'gen-video', 'make me a video', 'video gen', 'animated background', 'exploding view', 'veo', 'video asset', 'scroll animation video', 'chatgpt image', 'gpt image', 'chatgpt flag'. |
AI Image & Video Generation
Image Generation
Six tiers: 1) Gemini API (default, Python script) → 2) Codex Desktop (gpt-image-2 via bridge, free, no API key) → 3) ChatGPT Desktop CDP (cli-anything-chatgpt, best quality, one command) → 4) ChatGPT Browser (Claude-in-Chrome fallback) → 5) LiteImage (local SD) → 6) Local Gateway (SSE, optional).
Video Generation
Google Veo via Gemini API: 1) Text-to-video → 2) Image-to-video → 3) Video extension.
Step 1: Detect Media Type
Read the user's request. Determine if they need an image or a video:
- Video signals: "animated", "video", "scroll animation", "exploding view", "rotating", "3D animation", "hero background video", "motion", "cinematic", "panning shot", "Veo", "mp4"
- Image signals: "image", "banner", "mockup", "screenshot", "poster", "thumbnail", "png", "jpg"
- Ambiguous: Ask which they want via AskUserQuestion.
Step 2: Gather Parameters (MANDATORY)
CRITICAL: You MUST call the AskUserQuestion tool IMMEDIATELY as your FIRST action. Do NOT respond with plain text. Do NOT ask questions via normal chat. Do NOT skip this step. Do NOT generate anything until AskUserQuestion has been answered.
The ONLY exception: If the user's message explicitly provides ALL required parameters, skip straight to Step 3.
For Images — collect these 5:
- Aspect ratio —
1:1, 3:4, 4:3, 9:16, 16:9 (default), 21:9
- Resolution —
1K (default), 2K, 4K (pro model only)
- Reference images — paths or "none"
- Purpose — hero banner, social post, ad, mockup, etc.
- Save location — default:
~/Pictures/gen-image/
For Videos — collect these 6:
- Aspect ratio —
16:9 (default) or 9:16
- Resolution —
720p (default), 1080p, 4k (1080p/4k require duration=8)
- Duration —
4, 6, or 8 seconds (default: 8)
- Model —
fast (default, $0.15/sec) or standard ($0.40/sec)
- Purpose — hero background, scroll animation, product demo, social, etc.
- Save location — default:
~/Videos/gen-video/
Also ask: Do they have a starting image? (enables image-to-video mode)
AskUserQuestion templates:
Image:
Before I generate the image:
1. **Aspect ratio?** 16:9 (banner), 1:1 (social), 9:16 (story)? [default: 16:9]
2. **Resolution?** 1K, 2K, or 4K? [default: 1K]
3. **Reference images?** Any existing images to match the style? (paste paths or "none")
4. **Purpose?** Hero banner, social post, ad, mockup, etc.?
5. **Save to?** [default: ~/Pictures/gen-image/]
Video:
Before I generate the video:
1. **Aspect ratio?** 16:9 (landscape) or 9:16 (portrait)? [default: 16:9]
2. **Resolution?** 720p, 1080p, or 4k? [default: 720p]
3. **Duration?** 4, 6, or 8 seconds? [default: 8]
4. **Model?** fast (~$1.20/8s) or standard (~$3.20/8s)? [default: fast]
5. **Starting image?** Any image to animate from? (paste path or "none")
6. **Save to?** [default: ~/Videos/gen-video/]
Omit any parameter the user already provided.
Red flags — if you're thinking any of these, STOP:
- "I'll just ask in chat" — NO. Use the AskUserQuestion tool.
- "I have enough info" — Do you have ALL required params? If not, ask.
- "I'll use defaults" — The USER picks defaults, not you. Ask them.
- "Let me generate first and ask later" — WRONG ORDER. Ask first.
Ongoing: Keep Asking Via AskUserQuestion
After generating, you remain in generation mode. Any follow-up questions — regeneration, tweaks, batch requests — MUST go through AskUserQuestion, NOT plain text.
Stop condition: Only stop if the user explicitly moves on to a different topic.
Step 3: Generate
Image — Gemini API (Default)
GEN="python ${CLAUDE_SKILL_DIR}/gen_image.py"
$GEN output.png "SaaS dashboard, dark theme, modern UI" --aspect 16:9
$GEN output.png "Epic dragon" --aspect 16:9 --size 4K --model pro
$GEN out.png "Same style, new subject" --ref style_ref.png
$GEN out.png "cube" "sphere" "pyramid" --aspect 1:1
$GEN out.png "gear icon" --style styles/blue_glass_3d.md
$GEN edit out.png "Change background to blue" -i input.png
$GEN edit out.png "Merge these art styles" -i style1.png -i style2.png
$GEN describe image.png
$GEN describe a.png b.png --prompt "Compare these two images"
Image Models
| Alias | Model ID | Quality | Max Resolution |
|---|
flash | gemini-2.5-flash-image | Fast (default) | 1K |
pro | gemini-3-pro-image-preview | Best | 4K |
legacy | gemini-2.0-flash-exp | Fallback | 1K |
Resolution: --size 1K (default), 2K, 4K (pro only)
Aspect ratios: 1:1, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9 (default), 21:9
References: Up to 14 images for style/composition guidance.
Model Selection Rules
Auto-select model based on quality signals in the user's message — no need to ask:
| Signal | Model | Examples |
|---|
| Cheap / fast | flash (default) | "go cheap", "don't spend a lot", "quick image", "test this", "rough draft" |
| High quality | pro | "go big", "best quality", "really good", "4K", "hero image", "final version", "production ready", "make it perfect" |
| Codex / OpenAI | codex | "codex", "use codex", "openai image", "gpt-image-2", "codex desktop" — free via Codex Desktop bridge, gpt-image-2, up to 4K |
| ChatGPT / GPT | chatgpt | "chatgpt", "gpt image", "use chatgpt", "chatgpt flag", "5.5 image", "use gpt" — CDP CLI (preferred) or browser automation fallback, best photorealistic quality |
| No signal | flash | default — save money unless quality is explicitly needed |
Image — Codex Desktop Bridge (Tier 2, FREE)
Use when: User says "codex", "openai image", "gpt-image-2", or you want gpt-image-2 quality without API key cost. Routes through the Codex Desktop app via LiteHarness bridge — uses your logged-in Codex Desktop OAuth session, zero API cost.
Requirements: Codex Desktop app installed and running with an active OpenAI account. LiteHarness bridge operational (requires LiteSuite running with the Mon1 bridge active).
How it works:
- Format a structured prompt using the Codex imagegen prompt schema
- Send to Codex Desktop via
liteharness codex-desktop-send
- Codex generates using built-in
image_gen tool (gpt-image-2, OAuth auth)
- Output lands in
~/.codex/generated_images/<session-id>/
- Copy the output to the target save location
Prompt Schema (from Codex imagegen skill):
Use case: <taxonomy slug>
Asset type: <where the asset will be used>
Primary request: <user's main prompt>
Scene/backdrop: <environment>
Subject: <main subject>
Style/medium: <photo/illustration/3D/etc>
Composition/framing: <wide/close/top-down; placement>
Lighting/mood: <lighting + mood>
Color palette: <palette notes>
Text (verbatim): "<exact text>"
Constraints: <must keep/must avoid>
Avoid: <negative constraints>
Use-case taxonomy slugs: photorealistic-natural, product-mockup, ui-mockup, infographic-diagram, ads-marketing, logo-brand, illustration-story, stylized-concept, historical-scene
Workflow:
python -m liteharness.cli codex-desktop-list
python -m liteharness.cli codex-desktop-send "Generate an image: <structured prompt>"
ls -t ~/.codex/generated_images/*/
cp ~/.codex/generated_images/<session>/<file>.png <save_location>/
Sizes (gpt-image-2): 1024x1024 (square), 1536x1024 (landscape), 1024x1536 (portrait), 2048x2048 (2K), 3840x2160 (4K landscape), auto
Quality tiers: low (fast drafts), medium, high, auto (final assets)
Transparent images via chroma-key removal:
python -m liteharness.cli codex-desktop-send "Generate the subject on a perfectly flat solid #00ff00 chroma-key background. No shadows, gradients, or reflections."
python "$USERPROFILE/.codex/skills/.system/imagegen/scripts/remove_chroma_key.py" \
--input source.png --out final.png \
--auto-key border --soft-matte --despill
Limitations:
- Async — no direct return value, must poll output directory
- One image at a time (sequential, not batch)
- Codex Desktop must be running and visible
- Output dir changes per Codex session
Video — Google Veo (Gemini API)
VEO="python ${CLAUDE_SKILL_DIR}/gen_video.py"
$VEO out.mp4 "Cinematic aerial shot of a coastal city at golden hour"
$VEO out.mp4 "Rotating 3D globe, dark bg" --res 1080p --duration 8
$VEO out.mp4 "Exploding view of a house, white bg" --model standard --res 4k
$VEO out.mp4 "Floating app icons orbiting a golden hub" --count 3
$VEO i2v out.mp4 --image hero.png "Camera slowly pans across the scene"
$VEO i2v out.mp4 --image start.png --last-frame end.png "Smooth interpolation"
$VEO extend longer.mp4 --input clip.mp4 "Continue the camera movement"
Video Models
| Alias | Model ID | Cost (720p/1080p) | Cost (4K) |
|---|
fast | veo-3.1-fast-generate-preview | $0.15/sec | $0.35/sec |
standard | veo-3.1-generate-preview | $0.40/sec | $0.60/sec |
veo2 | veo-2.0-generate-001 | $0.35/sec | — |
Cost Examples (8-second clip)
| Model | 720p | 1080p | 4K |
|---|
| fast | $1.20 | $1.20 | $2.80 |
| standard | $3.20 | $3.20 | $4.80 |
Video Specs
| Property | Value |
|---|
| Format | MP4, 24fps |
| Resolutions | 720p (default), 1080p, 4K |
| Aspect ratios | 16:9 (landscape), 9:16 (portrait) |
| Duration | 4, 6, or 8 seconds per generation |
| Audio | Natively generated (Veo 3.1+) |
| Extension | +7 seconds per call, up to 20 extensions (~141s total) |
| Latency | 11s to 6 min depending on load |
Constraints
- 1080p and 4K require
duration=8
- Video extension is 720p only
- Image-to-video uses
person_generation="allow_adult" (not "allow_all")
- Generated video URIs expire after 2 days — download immediately
- SynthID watermark embedded in all outputs
Image — ChatGPT Desktop CDP (Tier 3, PREFERRED for ChatGPT)
Use when: User says "chatgpt", "gpt image", "use chatgpt", "chatgpt flag", "5.5 image", "use gpt". Controls ChatGPT Desktop (Electron) directly via Chrome DevTools Protocol — no browser extension needed.
Requirements: ChatGPT Desktop installed (Windows Store), Pro account logged in, cli-anything-chatgpt installed.
Install: Clone https://github.com/cli-anything/chatgpt-agent-harness and run pip install -e . from the repo root, or check PyPI for cli-anything-chatgpt if a published package is available.
Cost: Included in ChatGPT Pro subscription. No per-image cost.
Quality: Best photorealistic image gen available. Perfect text rendering, complex infographics.
Workflow (ONE COMMAND)
cli-anything-chatgpt launch
cli-anything-chatgpt image "A dark cockpit UI for an AI agent swarm wizard" -o ~/Pictures/gen-image/wizard.png
cli-anything-chatgpt --json image "epic sunset" -o ~/Pictures/gen-image/sunset.png
cli-anything-chatgpt chat "Explain this architecture..."
cli-anything-chatgpt read
cli-anything-chatgpt new
cli-anything-chatgpt status
How It Works
- Kills existing ChatGPT Desktop, relaunches with
--remote-debugging-port=9223
- Connects via CDP WebSocket to the Electron renderer
- Types into chat textarea via
Runtime.evaluate (React-compatible native setter)
- Polls DOM for generated
<img> elements (up to 120s timeout)
- Downloads image URL to target path
Auth persists — Electron user data dir keeps OAuth tokens across relaunches.
Prompt Tips
- Be extremely descriptive — it follows instructions precisely
- Specify style: "photorealistic", "infographic", "illustration", "3D render"
- For text in images: spell out exactly what text should appear
- For UI mockups: describe colors (#hex), fonts, layout, spacing in detail
Image — ChatGPT Browser (Tier 4, FALLBACK)
Use when: ChatGPT Desktop CDP is unavailable. Falls back to Claude-in-Chrome browser automation.
Requirements: Chrome with Claude-in-Chrome extension, logged into chatgpt.com with Pro account.
Cost: Included in ChatGPT Pro subscription ($200/mo). No per-image cost.
Quality: Currently the best photorealistic image gen available. Perfect text rendering, complex infographics, photorealistic subjects.
Workflow
-
Get browser context:
mcp__claude-in-chrome__tabs_context_mcp({ createIfEmpty: true })
-
Find or create a ChatGPT tab:
- If an existing tab has
chatgpt.com in the URL, use it
- Otherwise create a new tab and navigate to
https://chatgpt.com
mcp__claude-in-chrome__tabs_create_mcp()
mcp__claude-in-chrome__navigate({ tabId: <id>, url: "https://chatgpt.com" })
-
Type the prompt into the chat input:
mcp__claude-in-chrome__form_input({
tabId: <id>,
ref_id: "<textbox ref for 'Chat with ChatGPT'>",
value: "<user's image prompt>"
})
-
Submit the prompt — click the send button or press Enter:
mcp__claude-in-chrome__computer({
tabId: <id>,
action: "key",
key: "Return"
})
-
Poll for image completion — ChatGPT takes 15-60s to generate. Poll every 10s:
mcp__claude-in-chrome__read_page({
tabId: <id>,
filter: "all",
depth: 5
})
Look for img[alt="Generated image"] in the accessibility tree. Keep polling until it appears or a text response indicates failure.
-
Download the generated image:
mcp__claude-in-chrome__javascript_tool({
action: "javascript_exec",
tabId: <id>,
text: `
const img = document.querySelector('img[alt="Generated image"]');
if (img) {
const a = document.createElement('a');
a.href = img.src;
a.download = '<filename>.png';
document.body.appendChild(a);
a.click();
document.body.removeChild(a);
'Download triggered';
} else { 'No image found'; }
`
})
-
Move from Downloads to target directory:
mv ~/Downloads/<filename>.png <save_location>/<filename>.png
ChatGPT Prompt Tips
- ChatGPT excels at infographics, photorealistic scenes, text-heavy images, and complex compositions
- Be extremely descriptive — it follows instructions precisely
- Specify style: "photorealistic", "infographic", "illustration", "3D render", "watercolor"
- For infographics: describe sections, data points, layout, color scheme
- For text in images: spell out exactly what text should appear
- Can do image editing via "Edit image" button on existing generations
Limitations
- No API — browser automation only, requires active Chrome session
- One image at a time (no batch)
- No programmatic seed control
- Download lands in browser's default Downloads folder — must move after
- Session/auth can expire — may need to re-login
- Rate limits unclear — Pro tier is generous but not unlimited
Image Fallback 3: LiteImage API (Local SD)
Requirements: LiteImage app running locally (part of LiteSuite — requires LiteSuite running). Exposes local Stable Diffusion on port 7426.
If LiteImage is running — local Stable Diffusion on port 7426.
curl -s -X POST http://127.0.0.1:7426/generate \
-H "Content-Type: application/json" \
-d '{
"prompt": "Professional SaaS dashboard screenshot, dark theme",
"width": 1024, "height": 576, "steps": 25,
"guidance_scale": 7.5,
"negative_prompt": "blurry, low quality, distorted"
}' --max-time 300
Response includes imagePath (saved file) and imageBase64 (inline). Check status first:
curl -s http://127.0.0.1:7426/status
curl -s http://127.0.0.1:7426/models
LiteImage Parameters
| Param | Default | Notes |
|---|
prompt | required | Image description |
width | 512 | Pixel width |
height | 512 | Pixel height |
steps | 20 | Inference steps (20-30 for quality) |
guidance_scale | 7.5 | Prompt adherence (5-12 range) |
negative_prompt | "" | What to avoid |
seed | -1 | -1 = random, set for reproducibility |
batch_count | 1 | Number of images |
Common Sizes
| Use Case | Width | Height | Ratio |
|---|
| YouTube thumbnail / hero banner | 1280 | 720 | 16:9 |
| Instagram / Twitter post | 1024 | 1024 | 1:1 |
| Instagram/TikTok Story | 576 | 1024 | 9:16 |
| Blog / presentation | 1024 | 768 | 4:3 |
| Pinterest / Facebook ad | 768 | 1024 | 3:4 |
Image Fallback 4: Local Gateway (SSE, Optional)
If you have a local image-generation gateway running on port 8200 that exposes an SSE endpoint:
curl -X POST http://127.0.0.1:8200/v1/marketing/generate/image \
-H "Content-Type: application/json" \
-d '{"prompt": "...", "style": "photorealistic", "aspect_ratio": "16:9"}' \
--no-buffer 2>/dev/null | while IFS= read -r line; do
[[ "$line" == data:* ]] && echo "${line#data: }"
done || true
Example gateway styles: photorealistic, illustration, 3d-render, flat-design, cinematic
Note: This tier requires a custom local gateway server on port 8200. It is optional — skip to Tier 1 (Gemini API) if you don't have one configured.
Prompt Engineering
Image Prompts
Structure: [Subject] + [Context/Setting] + [Style] + [Mood] + [Technical quality]
"Young professional using laptop at modern coworking space,
natural light, confident expression, photorealistic, 8k"
Video Prompts
Structure: [Camera movement] + [Subject/Action] + [Style] + [Background] + [Mood]
# Hero background
"Slow cinematic orbit around floating holographic app icons,
dark background with subtle gold particle effects, premium tech aesthetic"
# Exploding view (Nick Saraev style)
"High quality exploding view animation of a house showing interior design,
white background, explodes in all directions vertically and horizontally,
nothing goes outside the frame"
# 3D product rotation
"Rotating 3D globe with glowing data connections, dark background,
center of mass stays fixed, smooth rotation on axis"
# Scroll-synced (generate then extract frames)
"Smooth zoom into a futuristic dashboard interface,
camera pushes forward through layers of UI panels, dark theme with gold accents"
Tips for video:
- Specify camera movement (orbit, pan, zoom, dolly, static)
- Say "white background" or "dark background" for easy website integration
- Say "nothing goes outside the frame" to keep assets contained
- Generate 2-3 variants and pick the best one
- For scroll-synced: extract frames as JPEGs with ffmpeg after generation
Post-Processing: Background Removal (MANDATORY for Images)
After EVERY image generation, remove the background unless the user explicitly says to keep it.
Gemini-generated images always have a solid background (usually white or light gray corners on icons/logos). Strip it immediately:
python -c "
from PIL import Image
import numpy as np
img = Image.open('OUTPUT.png').convert('RGBA')
data = np.array(img)
r, g, b, a = data[:,:,0], data[:,:,1], data[:,:,2], data[:,:,3]
# Remove white/light corners (threshold 200+ on all channels)
white_mask = (r > 200) & (g > 200) & (b > 200)
data[white_mask, 3] = 0
Image.fromarray(data).save('OUTPUT.png')
"
Adjust the threshold based on the background color:
- White backgrounds:
> 200 on R, G, B
- Light gray:
> 180 on R, G, B
- Specific color: target that color's range
When NOT to remove: User says "keep background", "solid background", or the image is a photograph/scene (not an icon/logo/asset).
Post-Processing: Frame Extraction for Scroll Animations
After generating a video for scroll-synced use:
mkdir -p frames
ffmpeg -i video.mp4 -vf "fps=24" -q:v 2 frames/frame_%04d.jpg
ffmpeg -i video.mp4 -vf "fps=24" -quality 80 frames/frame_%04d.webp
ffmpeg -i hero.mp4 -vcodec libx264 -crf 28 -preset slow -an hero_compressed.mp4
Workflow
- Detect media type (image vs video)
- Gather parameters via AskUserQuestion
- Image: run
gen_image.py (Gemini default) or LiteImage/Gateway fallback
- Image: remove background (MANDATORY — see Post-Processing section)
- Video: run
gen_video.py (Veo default)
- Review output (use Read tool on saved path)
- Post-process if needed (frame extraction, compression)
- Generate 2-3 variants for A/B testing when doing marketing work
