gpt-image

Agent runbook for GPT Image 2 / 2.5 generation/editing. Use the prompt library + packaged CLI. Do not reimplement image API code.

Operating loop

1. Classify request and resolve model: generate, edit, inpaint, or multi-reference; identify asset type, exact text, aspect ratio, references, safety constraints, and budget/quality. Apply the model-choice rules below before any API call.
2. Choose the reference path: Image 2 keeps the gallery-first workflow below. For 2.5, a precise brief needs no reference loading; otherwise choose one short task slice.
3. Refine only as needed: preserve the brief. Add a specific gallery case, craft section or template only to fill a concrete gap; do not load them as a bundle for 2.5.
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 at a time. Skip long discussion for precise “generate now” requests with a resolved model.
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 with an explicit --model. 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: confirmed 2.5 model + precise prompt + “generate now” → preflight and CLI, without a mandatory reference/craft pass. Do not reconfirm an exact valid model.

Model choice and prompt adaptation