gpt-image-cookbook

name	gpt-image-cookbook
description	Use this skill whenever a user asks to generate, create, draw, render, or edit images with AI image models — gpt-image-2, DALL-E, Google Imagen, Flux, or others. Covers text-to-image, reference-image editing, inpainting, posters, typography, UI mockups, diagrams, and curated gallery prompts. Search the bundled cookbook references for matching patterns, confer on direction when ambiguous, then call the packaged `gic` CLI. Do not write new image-generation code unless the user explicitly asks to modify this repo.
compatibility	Requires Python 3.11+ and one of `gic`, `uv`, or `uvx`. CLI/API calls read provider API keys from env (`OPENAI_API_KEY`, `GOOGLE_API_KEY`, `FAL_KEY`, etc.) and may incur charges on the user's account.
metadata	{"openclaw":{"requires":{"anyBins":"[Truncated]"},"primaryEnv":"OPENAI_API_KEY","homepage":"https://github.com/eugeniughelbur/gpt-image-cookbook"}}

gpt-image-cookbook

Agent runbook for multi-provider AI image generation and editing. Use the prompt cookbook + packaged gic CLI. Do not reimplement image API code.

Operating loop

1. Classify the request: generate, edit, inpaint, or multi-reference. Identify asset type, exact text to render, aspect ratio, references, safety constraints, and budget/quality tier.
2. Pick a provider: default to openai (gpt-image-2). Switch to imagen for Google-native quality on photoreal scenes, or flux for fast/cheap drafts and stylized art. The user's explicit request always wins.
3. Search references first: open references/gallery.md (the routing index). Load the closest references/gallery-<category>.md file(s). Read actual **Prompt** text before choosing a pattern — never guess from category name alone.
4. Refine with craft: load references/craft.md for dense text, diagrams, UI mockups, data visualization, multi-panel layouts, or when the gallery has no close match.
5. Confer when useful: before costly, ambiguous, or high-polish calls, present 1–3 matched directions plus planned size/quality/provider; ask at most one concise question. Skip the discussion for precise "generate now" requests.
6. Preflight, no side effects: check command -v gic first. Do not reinstall, overwrite skill folders, create or modify .env, or write API keys. Global/shared installs are opt-in only.
7. Execute via CLI only: call gic. Do not create a new generate.py, SDK wrapper, or ad-hoc script for normal image requests.
8. Report: output file path(s), the provider/model used, key flags, and one concise refinement suggestion if useful.

Fast path: precise prompt + explicit "generate now" → quick reference/craft check, then CLI.

CLI resolution

Preferred call order:

# Existing CLI on PATH
gic -p "PROMPT" [-f OUT] [-i REF...] [-m MASK] [--provider openai|imagen|flux] [options]

# Repo-local launcher (when the skill folder is bundled with the runtime)
uv run "$SKILL_DIR/scripts/generate.py" -p "PROMPT" [options]

# Transient install when the user requested a one-off CLI execution
uvx --from git+https://github.com/eugeniughelbur/gpt-image-cookbook gic -p "PROMPT" [options]

scripts/generate.py is a launcher: repo-local src/gic → installed gic on PATH → transient uvx fallback.

Provider selection

Provider	Model default	When to use
openai	gpt-image-2	Default. Strong on text rendering, posters, UI mockups, Chinese typography, research figures.
imagen	imagen-4	Photoreal scenes, product shots, faces, lighting realism. Google-account billing.
flux	flux-pro-1.1	Fast/cheap drafts, stylized art, broad style exploration. fal.ai or Replicate billing.

The CLI resolves the provider from the --provider flag, then GIC_DEFAULT_PROVIDER env var, then falls back to openai.

Key and cost rules

• The CLI reads provider keys from process env, then .env, then ~/.env without overriding existing env. Successful API calls bill the user's provider account.
• If a host runtime has native platform-managed image generation and the user wants that path, use the host tool instead of this CLI.
• If the required key is unset, report the missing key and the env var name; do not write secrets.
• If the user wants to avoid local-key use, respect unset OPENAI_API_KEY (etc.); if a key exists in .env/~/.env, tell them to remove or rename it for the session rather than working around it.
• Never print secret values.

Flags

Flag	Values	Use
-p, --prompt	string	Required prompt or edit instruction
-f, --file	path	Output path; auto-named if omitted
-i, --image	repeatable path	Use the edits endpoint; supports multiple references
-m, --mask	PNG path	Inpaint with alpha mask; requires -i
--provider	openai, imagen, flux	Provider router
--model	string	Override the provider's default model
--size	1k, 2k, 4k, portrait, landscape, square, wide, tall, or literal WxH	Canvas size
--quality	low, medium, high, auto	Cost/quality dial (provider-mapped)
-n, --n	integer	Number of images
--background	auto, opaque, transparent	Background mode (provider-dependent)
--format	png, jpeg, webp	Output encoding
--user	string	Optional end-user identifier passed to provider

Quality policy:

• low: cheap drafts, broad exploration, many variants.
• medium: normal exploration, style probing, balanced cost.
• high: final assets, dense text, posters, diagrams, UI mockups, paper figures, dense labels.

Size policy:

• default/social square: 1k / 1024x1024
• poster/mobile/beauty: portrait
• landscape/gameplay/photo: landscape
• print/paper figure: 2k
• widescreen hero: 4k
• vertical story/banner: tall

Endpoint routing

Mode	Trigger	Endpoint family
Text-to-image	no -i	provider's generations endpoint
Reference edit	one or more -i	provider's edits endpoint
Inpaint	-i + -m	provider's edits endpoint with mask

Surface API errors verbatim enough for debugging. Exit codes: 0 success, 1 API/refusal, 2 bad args/missing key.

Reference loading

• references/gallery.md: routing index for the cookbook gallery. Load first.
• references/gallery-*.md: concrete prompts, previews, paths, metadata. Load 1 category for normal requests; 2–3 for hybrids.
• references/craft.md: prompt-craft checklist. Load for prompt repair, exact text rendering, UI/data/diagram grammar, edit invariants, and multi-panel consistency.
• references/providers.md: provider/model semantics. Load for API behavior or capability questions.

Reference loading policy: load the smallest useful slice; never load all category files by default.

Verification

After a generation call:

1. Confirm the output file exists at the reported path.
2. If the prompt requested specific text, verify the text renders correctly — re-run with --quality high if it doesn't.
3. For edits/inpainting, confirm the unmasked regions are preserved.