gpt-image

gpt-image

Agent runbook for GPT Image 2 generation/editing. Use the prompt library + packaged CLI. Do not reimplement image API code.

Operating loop

1. Classify request: generate, edit, inpaint, or multi-reference; identify asset type, exact text, aspect ratio, references, safety constraints, and budget/quality.
2. Search references first: open references/gallery.md; load/search the closest references/gallery-<category>.md file(s). Read actual Prompt text before choosing a pattern.
3. Refine with craft: load references/craft.md for dense text, diagrams, UI, data visualization, multi-panel layouts, weak prompts, or no close gallery match.
4. Confer when useful: before costly/ambiguous/high-polish calls, present 1–3 matched directions plus planned size/quality; ask at most one concise question. Skip long discussion for precise “generate now” requests.
5. Preflight, no side effects: use existing CLI/skill if present. Check command availability (command -v gpt-image), installed tool lists when the tool manager exists, or the runtime’s own skill registry when available. Do not assume a local home path in cloud/hosted runtimes.
6. No blind setup: do not reinstall, overwrite skill folders, create/modify .env, or write API keys unless the user explicitly requested setup. Global/shared installs are opt-in only.
7. Execute via CLI only: call gpt-image or scripts/generate.py. Do not create a new generate.py, SDK wrapper, or ad-hoc script for normal image requests.
8. Report: output file path(s), 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
gpt-image -p "PROMPT" [-f OUT] [-i REF...] [-m MASK] [options]

# Installed skill folder; use runtime-provided skill path when available
uv run "$SKILL_DIR/scripts/generate.py" -p "PROMPT" [-f OUT] [-i REF...] [-m MASK] [options]

# Direct transient CLI when the user requested setup/one-off CLI execution
uvx --from git+https://github.com/wuyoscar/gpt_image_2_skill gpt-image -p "PROMPT" [options]

scripts/generate.py is a launcher: repo-local src/gpt_image_cli → installed gpt-image → PATH gpt-image → transient uvx/uv fallback.

Key and cost rules

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

Flags

| Flag | Values | Use | |---|---|---| | -p, --prompt | string | Required prompt/edit instruction | | -f, --file | path | Output path; auto-named if omitted | | -i, --image | repeatable path | Use edits endpoint; supports multiple references | | -m, --mask | PNG path | Inpaint with alpha mask; requires -i | | --model | default gpt-image-2 | Image model | | --size | 1k, 2k, 4k, portrait, landscape, square, wide, tall, or literal | Canvas size | | --quality | low, medium, high, auto | Cost/quality dial | | -n, --n | integer | Number of images | | --background | auto, opaque | Generation background | | --moderation | auto, low | Generation moderation setting | | --format | png, jpeg, webp | Output encoding | | --compression | 0-100 | JPEG/WebP compression | | --user | string | Optional end-user identifier |

Quality policy:

• low: cheap drafts, broad exploration, many variants.
• medium: normal exploration, style probing, balanced cost.
• high: final assets, Chinese text, posters, diagrams, UI, 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 | |---|---|---| | Text-to-image | no -i | /v1/images/generations | | Reference edit | one or more -i | /v1/images/edits | | Inpaint | -i + -m | /v1/images/edits 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 162-prompt Reference Gallery Atlas. Load first.
• references/gallery-*.md: concrete prompts, previews, paths, metadata, attribution. Load 1 category for normal requests; 2–3 for hybrids.
• references/craft.md: prompt-craft checklist. Load for prompt repair, exact text, UI/data/diagram grammar, edit invariants, and multi-panel consistency.
• references/openai-cookbook.md: official parameter/model semantics. Load for API behavior or model capability questions.

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

Verification

• Before API call: confirm endpoint mode, size, quality, output path, and required reference/mask files.
• After CLI call: report path(s) printed by the CLI and surface stderr on failure.
• For edits/inpaints: verify -i paths exist; verify -m exists when used.

Preserve Curated vs Author + Source metadata when adapting examples. Add new collected prompts to the Reference Gallery before README promotion.