Image Generation & Editing (GPT Image default, Gemini fallback)
Generate new images or edit existing ones. The script picks a provider based on which API keys are available:
- OpenAI
gpt-image-2— used whenOPENAI_API_KEYis set (default). - Gemini
gemini-3.1-flash-image-preview— used when onlyGEMINI_API_KEYis set.
When both keys are set, OpenAI is picked by default; force Gemini with --provider gemini. If an auto-selected OpenAI call fails at runtime (quota, moderation, network), the script transparently falls back to Gemini when a Gemini key is available.
Usage
The script is at scripts/generate_image.py relative to this skill's directory (the directory containing this SKILL.md). Resolve the full path from the skill's location before running. Do not hardcode ~/.codex/..., because the skill may be installed in a different location.
Keep the distinction clear:
- The script path tells you where to find
generate_image.py. - The output path is controlled by the current working directory plus
--filename. - Run from the user's working directory so relative filenames save output there, not in the skill directory.
Generate new image:
uv run <this-skill-directory>/scripts/generate_image.py --prompt "your image description" --filename "output-name.png" [--resolution 1K|2K|4K] [--provider auto|openai|gemini] [--model MODEL] [--openai-api-key KEY | --gemini-api-key KEY]
Edit existing image:
uv run <this-skill-directory>/scripts/generate_image.py --prompt "editing instructions" --filename "output-name.png" --input-image "path/to/input.png" [--resolution 1K|2K|4K] [--provider auto|openai|gemini] [--model MODEL] [--openai-api-key KEY | --gemini-api-key KEY]
Important: Always run from the user's current working directory so images are saved where the user is working, not in the skill directory.
Default Workflow (draft → iterate → final)
Goal: fast iteration without burning time on 4K until the prompt is correct.
- Draft (1K): quick feedback loop
uv run <this-skill-directory>/scripts/generate_image.py --prompt "<draft prompt>" --filename "yyyy-mm-dd-hh-mm-ss-draft.png" --resolution 1K
- Iterate: adjust prompt in small diffs; keep filename new per run
- If editing: keep the same
--input-imagefor every iteration until you’re happy.
- If editing: keep the same
- Final (4K): only when prompt is locked
uv run <this-skill-directory>/scripts/generate_image.py --prompt "<final prompt>" --filename "yyyy-mm-dd-hh-mm-ss-final.png" --resolution 4K
Resolution Options
The script accepts three resolution tiers (uppercase K required):
- 1K (default) - ~1024px
- 2K - ~2048px
- 4K - ~4096px (Gemini) / 3840×2160 landscape under OpenAI
Map user requests to API parameters:
- No mention of resolution →
1K - "low resolution", "1080", "1080p", "1K" →
1K - "2K", "2048", "normal", "medium resolution" →
2K - "high resolution", "high-res", "hi-res", "4K", "ultra" →
4K
OpenAI 4K note: gpt-image-2 supports non-square 4K outputs within its size limits. --resolution 4K with OpenAI maps to 3840×2160.
Provider & Model Selection
Two providers are available:
| Provider | Default model | When chosen |
|---|---|---|
| OpenAI | gpt-image-2 |
--provider auto (default) when OPENAI_API_KEY is set, or --provider openai |
| Gemini | gemini-3.1-flash-image-preview |
--provider auto when only GEMINI_API_KEY is set, or --provider gemini, or as runtime fallback from a failed auto-OpenAI call |
Override either default with --model. Note: the model name is provider-specific; passing a Gemini model name while the script falls back to Gemini automatically will not preserve a user-specified OpenAI model (each provider uses its own default during fallback).
Common model options:
- OpenAI:
gpt-image-2(default) - Gemini:
gemini-3.1-flash-image-preview(default, fast),gemini-3-pro-image-preview(higher quality, slower)
API Keys
The script resolves provider-specific keys first, while preserving the original Gemini-only --api-key behavior:
- Explicit, provider-specific flags:
--openai-api-key KEY,--gemini-api-key KEY - Generic
--api-key KEY— kept for backward compatibility with the original Gemini-only script. Underauto, it is treated as a Gemini key unless an OpenAI key is provided by--openai-api-keyorOPENAI_API_KEY. Under explicit--provider openai, it is treated as an OpenAI key; under explicit--provider gemini, it is treated as a Gemini key. - Environment variables:
OPENAI_API_KEY,GEMINI_API_KEY
When --provider auto is selected and OpenAI fails at runtime, fallback to Gemini requires --gemini-api-key, --api-key, or the GEMINI_API_KEY env var.
If no key is resolvable for the chosen provider, the script exits with a clear error message listing both ways to fix it.
Preflight + Common Failures (fast fixes)
Preflight:
command -v uv(must exist)- At least one of:
test -n "$OPENAI_API_KEY" -o -n "$GEMINI_API_KEY"(or pass--openai-api-key,--gemini-api-key, or backward-compatible--api-key) - If editing:
test -f "path/to/input.png"
Common failures:
Error: No API key found...→ setOPENAI_API_KEYorGEMINI_API_KEY, or pass an explicit--*-api-keyflagError loading input image:→ wrong path / unreadable file; verify--input-imagepoints to a real image[warn] OpenAI call failed (...); falling back to Gemini.→ informational; a Gemini key was available and produced the image. Investigate the OpenAI error separately (quota, moderation, network)- "quota/permission/403" style errors with no fallback → no Gemini key available, or user used
--provider openai(explicit provider disables fallback). Try a different key, or drop the explicit provider to enable fallback
Filename Generation
Generate filenames with the pattern: yyyy-mm-dd-hh-mm-ss-name.png
Format: {timestamp}-{descriptive-name}.png
- Timestamp: Current date/time in format
yyyy-mm-dd-hh-mm-ss(24-hour format) - Name: Descriptive lowercase text with hyphens
- Keep the descriptive part concise (1-5 words typically)
- Use context from user's prompt or conversation
- If unclear, use random identifier (e.g.,
x9k2,a7b3)
Examples:
- Prompt "A serene Japanese garden" →
2025-11-23-14-23-05-japanese-garden.png - Prompt "sunset over mountains" →
2025-11-23-15-30-12-sunset-mountains.png - Prompt "create an image of a robot" →
2025-11-23-16-45-33-robot.png - Unclear context →
2025-11-23-17-12-48-x9k2.png
Image Editing
When the user wants to modify an existing image:
- Check if they provide an image path or reference an image in the current directory
- Use
--input-imageparameter with the path to the image - The prompt should contain editing instructions (e.g., "make the sky more dramatic", "remove the person", "change to cartoon style")
- Common editing tasks: add/remove elements, change style, adjust colors, blur background, etc.
Prompt Handling
For generation: Pass user's image description as-is to --prompt. Only rework if clearly insufficient.
For editing: Pass editing instructions in --prompt (e.g., "add a rainbow in the sky", "make it look like a watercolor painting")
Preserve user's creative intent in both cases.
Prompt Templates (high hit-rate)
Use templates when the user is vague or when edits must be precise.
Generation template:
- “Create an image of: . Style: . Composition: <camera/shot>. Lighting: . Background: . Color palette: . Avoid: .”
Editing template (preserve everything else):
- “Change ONLY: . Keep identical: subject, composition/crop, pose, lighting, color palette, background, text, and overall style. Do not add new objects. If text exists, keep it unchanged.”
Output
- Saves PNG to current directory (or specified path if filename includes directory)
- Script outputs the full path to the generated image
- Do not read the image back - just inform the user of the saved path
Examples
Generate new image (auto provider):
uv run <this-skill-directory>/scripts/generate_image.py --prompt "A serene Japanese garden with cherry blossoms" --filename "2025-11-23-14-23-05-japanese-garden.png" --resolution 2K
Force Gemini:
uv run <this-skill-directory>/scripts/generate_image.py --prompt "A serene Japanese garden with cherry blossoms" --filename "2025-11-23-14-23-05-japanese-garden-4k.png" --resolution 4K --provider gemini
Edit existing image (auto provider):
uv run <this-skill-directory>/scripts/generate_image.py --prompt "make the sky more dramatic with storm clouds" --filename "2025-11-23-14-25-30-dramatic-sky.png" --input-image "original-photo.jpg" --resolution 2K