
Create Image with GPT
FreeGenerate photorealistic or designed images using AI.
Free · Opens the source repo
What Create Image with GPT does
The Create Image with GPT skill allows users to generate a single image using OpenAI's gpt-image endpoints via fal.ai. It supports two model families: gpt-image-1 and gpt-image-2. The default model, gpt-image-1, is suitable for fixed output sizes and is used in various applications like character anchors and photoreal scenes. On the other hand, gpt-image-2 provides the flexibility of custom output sizes up to 3840px, making it ideal for designed sheets such as storyboards, where precise layouts are essential.
This skill is particularly useful for developers and designers who need to create high-quality images for projects that require visual representation of characters or scenes. By simply providing a text prompt, users can generate images that match their specifications. The skill also supports an edit variant, allowing users to refine images based on reference images, which is beneficial for creating consistent character designs or adapting scenes.
The implementation is straightforward, as the skill includes a Python script that handles the image generation process. Users can specify various parameters such as aspect ratio, image size, and quality, ensuring that the output meets their needs. Additionally, the skill routes requests through a proxy, which simplifies credential management and billing, making it easier to integrate into existing workflows.
Overall, this skill is an efficient tool for generating custom images tailored to specific requirements, enhancing the creative process for developers and designers alike.
When to use it
Use this skill when you need to generate photorealistic or designed images for projects, such as character designs or storyboards.
When not to use it
Avoid using this skill for generating images that require readable text, as the AI models may distort text elements.
What you can build with it
Generating Character Anchors
Create detailed character images based on text descriptions to use as visual references in projects.
Designing Storyboards
Generate storyboard sheets for visual storytelling, allowing for custom layouts and high-quality outputs.
Editing Existing Images
Refine images by using reference URLs to edit and adapt existing designs, ensuring consistency across visuals.
How to install Create Image with GPT
View source1. Install with the skills CLI
npx skills add gooseworks-ai/goose-skills/create-image-gpt-image-fal --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by gooseworks-aicreate-image-gpt-image-fal
Purpose
Generate one image via fal.ai's OpenAI gpt-image endpoints. Two model families are supported through a single --model flag:
gpt-image-1(default) —fal-ai/gpt-image-1. The FAL fallback for Higgsfield'sgpt_image_2. Fixed output sizes only. Used by:video-orchestrator/lock-characterPhase 0 (anchor portrait) and Phase 1 (angle keyframes via/edit)video-orchestrator/create-clipsPhase 1 for photoreal scenes- the orchestrator's
generate_with_fallback.pyrouter on Higgsfield failure
gpt-image-2—openai/gpt-image-2. The newer model; accepts custom output sizes (any multiple of 16, up to 3840px) and renders dense text/layouts well. Used for designed sheets such as ad storyboards (create-storyboard-sheets-fal).
The default stays gpt-image-1 so existing callers and the lock-character anchor-parity contract are unaffected. Opt into the newer model with --model gpt-image-2.
Pricing (approximate, as of 2026-05)
- gpt-image-1 — $0.04 (low), $0.08 (medium), $0.20 (high) per image. Source: fal.ai/models/fal-ai/gpt-image-1.
- gpt-image-2 — token-priced; rough per-image estimate $0.02 (low), $0.07 (medium), $0.19 (high). Source: fal.ai/models/openai/gpt-image-2.
The script defaults to medium; pass --quality high for finals.
Inputs
Required:
--prompt— text prompt. A verbatim character descriptor block goes here for character work.--output— local PNG destination.
Optional:
--model—gpt-image-1(default) orgpt-image-2.--aspect-ratio—9:16(default),16:9,1:1,2:3,3:2. gpt-image-2 also accepts3:4,4:3,4:5. Used when--image-sizeis not given.--image-size— explicitWIDTHxHEIGHT(e.g.1728x2304). gpt-image-2 only — values are rounded to multiples of 16 and capped at 3840px. Ongpt-image-1a custom size is ignored with a warning and the aspect-ratio mapping is used instead.--quality—low | medium | high(defaultmedium).--ref-image/--ref-url— a PUBLIC image URL for the/editvariant. Repeatable — pass it twice to send multiple refs (e.g. identity + style). The proxy does not upload local files, so a local path is rejected — host the image first (MCPget_upload_url→get_download_url, or any public URL) and pass that URL. When present, routes to the model's/editvariant so the model can match the references. Order matters: pass identity (character) first, then style refs.--with-logs— stream fal queue logs.
Credentials (proxy-routed — NOT a raw FAL key):
- The bundled
scripts/media_proxy.pyroutes every call through the GooseWorks fal-proxy, which bills the Ads agent. It reads~/.gooseworks/credentials.json(api_base,api_key,agent_id) — written bygooseworks login. Do not setFAL_API_KEY: an agent (cal_) token is not a FAL key and 401s against fal directly. - Set
GW_PROJECT_ID=<ad project id>in the env so the generation's spend attributes to that ad project (per-project cost shows in the app).
Preflight
test -f ~/.gooseworks/credentials.json || { echo "Missing credentials — run: gooseworks login"; exit 1; }
python3 -c "import requests" || pip3 install requests
Workflow
# Text-to-image, default model (gpt-image-1)
python3 skills/ads/capabilities/create-image-gpt-image-fal/scripts/generate.py \
--prompt "..." \
--output /path/to/anchor.png \
--aspect-ratio 9:16 \
--quality medium
# Edit-from-reference (anchor -> angle). --ref-image must be a PUBLIC URL,
# NOT a local path (the proxy does not upload local files):
python3 .../generate.py \
--prompt "..." \
--output /path/to/angle-3q-left.png \
--ref-image "https://.../anchor.png" \
--aspect-ratio 9:16
# gpt-image-2 with a custom output size (e.g. a designed storyboard sheet)
python3 .../generate.py \
--prompt "..." \
--output /path/to/storyboard.png \
--model gpt-image-2 \
--image-size 1728x2304 \
--quality high
The script:
- Loads the agent credentials from
~/.gooseworks/credentials.jsonvia the bundledmedia_proxy.py(proxy-routed; bills the Ads agent). - Resolves the model family (
--model) and output size (--image-sizeif given and supported, else the aspect-ratio mapping). - If one or more
--ref-image/--ref-urlflags are set, passes them asimage_urls=[url1, url2, ...](they must already be PUBLIC URLs) and routes to the model's/editvariant. Otherwise routes to the/text-to-imagevariant. - Submits through the GooseWorks fal-proxy and polls the queue to completion — host-swapping the
queue.fal.runstatus/response URLs to the proxy base (seemedia_proxy.py); never pollsqueue.fal.rundirectly. - Downloads the first result image to
--output. - Writes
<output>.meta.jsonwithgateway: "fal-proxy", model id,model_family, request, and cost.
Output
<output_path>— PNG (≥ 1 KB).<output_path>.meta.json— request + result metadata + cost, includingmodel_family(gpt-image-1orgpt-image-2).
Quality Checks
- Output file exists and is > 1 KB.
- For character anchors: visually inspect against the descriptor block (hair, shirt color, age).
meta.jsonincludesgateway: "fal-proxy", the resolvedmodelid,model_family,image_size, andquality.- For gpt-image-2 custom sizes: confirm the output dimensions match the requested
WIDTHxHEIGHT. - No readable text in the prompt that should appear in the image. AI image models mangle short brand text, URLs, code tokens, captions, and wordmarks even with explicit prompting. Examples observed:
"ffmpeg"→"ffmmg";"klarify"→"clarify";"therapists"→"therapits". Use PIL orffmpeg drawtextfor any overlay containing readable text. Reserve image gen for purely visual content (characters, scenes, backgrounds). Repeats LEARNINGS L4.
Failure Modes
| Symptom | Likely cause | Fix |
|---|---|---|
401 Unauthorized from fal | Calling fal directly with an agent token, or polling queue.fal.run instead of the proxy | This atom is proxy-routed — it uses the ~/.gooseworks/credentials.json agent token via media_proxy.py, never a raw FAL_API_KEY. Run gooseworks login if the credentials file is missing. |
ERROR: ref images must be PUBLIC URLs | Passed a local path to --ref-image / --ref-url | The proxy does not upload local files. Host it (MCP get_upload_url → get_download_url) and pass the resulting public URL. |
429 Too Many Requests | RPS limit | Drop concurrency to 2-3. |
| Custom size ignored | --image-size passed with --model gpt-image-1 | gpt-image-1 only supports fixed sizes; use --model gpt-image-2 for custom sizes. |
| Aspect-ratio drift (gpt-image-1) | gpt-image-1 only supports 1024x1024, 1024x1536, 1536x1024 | The script maps aspect ratios to these internally. |
| Size rejected (gpt-image-2) | Dimension not a multiple of 16, or > 3840px | The script rounds to /16 and caps at 3840; pass a smaller size. |
| Anchor reference ignored | /text-to-image variant doesn't accept refs | Pass --ref-image to force the /edit variant. |
| Skin / face looks "AI-stock" | gpt-image's failure mode | Add anti-AI cues to the prompt: "natural skin texture with pores, slight asymmetry, no perfect teeth". |
Cross-provider parity note
When this atom generates a character anchor (lock-character Phase 0), the anchor approved here MUST be pinned for all downstream angle gens, and the same --model must be used for those angle gens. Mixing model families (or mixing FAL-gpt-image with Higgsfield-gpt_image_2) introduces aesthetic drift. The orchestrator's generate_with_fallback.py inherits gateway/model_family from the anchor's .meta.json for subsequent calls.
References
- fal.ai/models/fal-ai/gpt-image-1
- fal.ai/models/openai/gpt-image-2
- Sibling Higgsfield path:
mcp__higgsfield__generate_imagewithmodel="gpt_image_2" - Shared helper:
scripts/media_proxy.py(proxy-routed FAL/ElevenLabs; bills the Ads agent — the helpergenerate.pyactually imports).scripts/fal_helpers.pyis a LEGACY raw-FAL helper kept for reference only;generate.pydoes not use it (it would need a realFAL_KEY). - Storyboard-sheet consumer:
create-storyboard-sheets-fal(video flow, in the separate ads-video repo)
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