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Create Image Gpt Image Fal

OrganizationPopular
gooseworks-ai
create-image-gpt-image-fal

Generate a single photoreal or designed image with OpenAI gpt-image via fal.ai. Supports gpt-image-1 (default, fixed sizes — the FAL fallback for Higgsfield's `gpt_image_2`) and gpt-image-2 (`openai/gpt-image-2`, custom output sizes up to 3840px). Routes to text-to-image or the edit variant depending on whether a reference image is provided. Use for photoreal character anchors, scene keyframes, and designed sheets (e.g. storyboards) where precise layout and legible text matter.

Overview

Publishergooseworks-ai
Repositorygoose-skills
Skill namecreate-image-gpt-image-fal
Stars
1.2K
Forks
208
Bundled files
9
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 9 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by gooseworks-ai on GitHub. Read the source before you install it.

Installation

Install the Create Image Gpt Image Fal AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git /tmp/goose-skills
mkdir -p .claude/skills
cp -r /tmp/goose-skills/skills/ads/capabilities/create-image-gpt-image-fal .claude/skills/create-image-gpt-image-fal
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Create Image Gpt Image Fal in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Create Image Gpt Image Fal on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Create Image Gpt Image Fal is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

create-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's gpt_image_2. Fixed output sizes only. Used by:
    • video-orchestrator/lock-character Phase 0 (anchor portrait) and Phase 1 (angle keyframes via /edit)
    • video-orchestrator/create-clips Phase 1 for photoreal scenes
    • the orchestrator's generate_with_fallback.py router on Higgsfield failure
  • gpt-image-2openai/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)

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:

  • --modelgpt-image-1 (default) or gpt-image-2.
  • --aspect-ratio9:16 (default), 16:9, 1:1, 2:3, 3:2. gpt-image-2 also accepts 3:4, 4:3, 4:5. Used when --image-size is not given.
  • --image-size — explicit WIDTHxHEIGHT (e.g. 1728x2304). gpt-image-2 only — values are rounded to multiples of 16 and capped at 3840px. On gpt-image-1 a custom size is ignored with a warning and the aspect-ratio mapping is used instead.
  • --qualitylow | medium | high (default medium).
  • --ref-image / --ref-url — a PUBLIC image URL for the /edit variant. 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 (MCP get_upload_urlget_download_url, or any public URL) and pass that URL. When present, routes to the model's /edit variant 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.py routes every call through the GooseWorks fal-proxy, which bills the Ads agent. It reads ~/.gooseworks/credentials.json (api_base, api_key, agent_id) — written by gooseworks login. Do not set FAL_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

bash
test -f ~/.gooseworks/credentials.json || { echo "Missing credentials — run: gooseworks login"; exit 1; }
python3 -c "import requests" || pip3 install requests

Workflow

bash
# 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:

  1. Loads the agent credentials from ~/.gooseworks/credentials.json via the bundled media_proxy.py (proxy-routed; bills the Ads agent).
  2. Resolves the model family (--model) and output size (--image-size if given and supported, else the aspect-ratio mapping).
  3. If one or more --ref-image / --ref-url flags are set, passes them as image_urls=[url1, url2, ...] (they must already be PUBLIC URLs) and routes to the model's /edit variant. Otherwise routes to the /text-to-image variant.
  4. Submits through the GooseWorks fal-proxy and polls the queue to completion — host-swapping the queue.fal.run status/response URLs to the proxy base (see media_proxy.py); never polls queue.fal.run directly.
  5. Downloads the first result image to --output.
  6. Writes <output>.meta.json with gateway: "fal-proxy", model id, model_family, request, and cost.

Output

  • <output_path> — PNG (≥ 1 KB).
  • <output_path>.meta.json — request + result metadata + cost, including model_family (gpt-image-1 or gpt-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.json includes gateway: "fal-proxy", the resolved model id, model_family, image_size, and quality.
  • 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 or ffmpeg drawtext for any overlay containing readable text. Reserve image gen for purely visual content (characters, scenes, backgrounds). Repeats LEARNINGS L4.

Failure Modes

SymptomLikely causeFix
401 Unauthorized from falCalling fal directly with an agent token, or polling queue.fal.run instead of the proxyThis 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 URLsPassed a local path to --ref-image / --ref-urlThe proxy does not upload local files. Host it (MCP get_upload_urlget_download_url) and pass the resulting public URL.
429 Too Many RequestsRPS limitDrop concurrency to 2-3.
Custom size ignored--image-size passed with --model gpt-image-1gpt-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, 1536x1024The script maps aspect ratios to these internally.
Size rejected (gpt-image-2)Dimension not a multiple of 16, or > 3840pxThe script rounds to /16 and caps at 3840; pass a smaller size.
Anchor reference ignored/text-to-image variant doesn't accept refsPass --ref-image to force the /edit variant.
Skin / face looks "AI-stock"gpt-image's failure modeAdd 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_image with model="gpt_image_2"
  • Shared helper: scripts/media_proxy.py (proxy-routed FAL/ElevenLabs; bills the Ads agent — the helper generate.py actually imports). scripts/fal_helpers.py is a LEGACY raw-FAL helper kept for reference only; generate.py does not use it (it would need a real FAL_KEY).
  • Storyboard-sheet consumer: create-storyboard-sheets-fal (video flow, in the separate ads-video repo)

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Create Image Gpt Image Fal AI skill do?

Generate a single photoreal or designed image with OpenAI gpt-image via fal.ai. Supports gpt-image-1 (default, fixed sizes — the FAL fallback for Higgsfield's `gpt_image_2`) and gpt-image-2 (`openai/gpt-image-2`, custom output sizes up to 3840px). Routes to text-to-image or the edit variant depending on whether a reference image is provided. Use for photoreal character anchors, scene keyframes, and designed sheets (e.g. storyboards) where precise layout and legible text matter.

Why use Create Image Gpt Image Fal on TypingMind?

Because you install it once and use it with any model. Create Image Gpt Image Fal is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Create Image Gpt Image Fal in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/create-image-gpt-image-fal. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Create Image Gpt Image Fal?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Create Image Gpt Image Fal?

As many as you like. As long as a model supports skills, you can use Create Image Gpt Image Fal with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Create Image Gpt Image Fal AI skill free?

Yes. It is published on GitHub by gooseworks-ai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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