Goose Skills is a library of workflows and data APIs that lets coding agents handle growth and go-to-market work such as advertising, social media, content, SEO, lead generation, and customer research. It is intended for teams using Claude Code, Cursor, Codex, and similar agents. The catalogue entries are its reusable skills.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add gooseworks-ai/goose-skills --skill create-image-gpt-image-falgit clone --depth 1 https://github.com/gooseworks-ai/goose-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/gooseworks-ai/goose-skills/create-image-gpt-image-fal)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/create-image-gpt-image-fal"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/create-image-gpt-image-fal/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/create-image-gpt-image-fal"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/create-image-gpt-image-fal.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 4 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 42 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 48 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 80 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 104 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00129 | $0.02530 |
| Opus 5 | $0.00064 | $0.01265 |
| Sonnet 5 | $0.00026 | $0.00506 |
| Haiku 4.5 | $0.00013 | $0.00253 |
Grade A, and why
create-image-gpt-image-fal scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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'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.
What ships with it
9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 13d ago First seen · 124 lines · 129 tokens per session scan A dd59fd7cd09e
create-image-gpt-image-fal is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,202 stars, last pushed 11d ago), licensed MIT. It adds 129 tokens to every session and 2,530 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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