Production prompt-engineering pipeline for GPT-Image-2 / OpenAI image generation. Pairs a 'media-designer' agent with a hosted searchable corpus of 7,405 community-vetted prompts (9,903 reference images), decomposed across 10 controlled vocabularies (subjects, styles, lighting, cameras, moods, palettes, compositions, mediums, techniques, usecases). Each record carries: full prompt body, twitter/X attribution link, downloaded reference image. Workflow: agent diagnoses the user brief → searches the corpus → picks a mood-aligned base → refactors the chosen prompt into a parameterised {argument} template → resolves arguments from user intent → returns the final paste-ready prompt with attribution + reference image. Use when the user wants a polished image-generation prompt for ads, posters, product shots, portraits, character sheets, UI mockups, infographics, exploded-view diagrams, or any other GPT-Image-2 / OpenAI image task.
Two CLI tools for image generation + vision analysis using goclaw's provider-chain pattern. `create_image` generates images via 7-provider chain (ChatGPT-OAuth/Codex, OpenRouter, Gemini, OpenAI, MiniMax, DashScope, BytePlus) — first available credential wins (OAuth session OR API key), embeds prompt into PNG tEXt metadata, saves to date-folder workspace. The ChatGPT-OAuth provider reads from `~/.codex/auth.json` so a ChatGPT Plus / Codex login works without any API key. `read_image` analyzes images via 4-provider vision chain (OpenRouter, Gemini, Anthropic, DashScope) — accepts file path. Supports `--prompt-file` for long/multi-line prompts, auto UTF-8 stdout, `.env` auto-load, and `--list-providers` diagnostic. Use when Claude needs to generate images or run vision analysis with a specific provider rather than relying on Claude's built-in image understanding.