image-gen

# image-gen Backend-agnostic image generation: single images, series with anchor-chain consistency, batch pipelines. Two backends: Gemini (API) and Nano Banana (local scripts with post-processing). ## Deep References | Signal | Load | Content | |---|---|---| | Gemini backend selected | `references/backends/gemini.md` | Models, env vars, flag table, examples, error codes | | Nano Banana needed (post-processing, series, JSON batch, style-match) | `references/backends/nano-banana.md` | Subcommands, flags, aspect ratios, prompt patterns by asset type | ## Phase 1: Detect Backend ```bash python3 skills/content/image-gen/scripts/detect-backend.py ``` - `gemini` -- load `references/backends/gemini.md` - `ask` -- no key found; ask the user to set `GEMINI_API_KEY` **Gate**: backend confirmed. ## Phase 2: Write Prompt Files Write all prompts to disk before any API call. Prompt files are the generation record and anchor-chain input for series. File naming: single `prompts/YYYY-MM-DD-{slug}.md`, series `prompts/{series-name}-01.md` through `-NN.md`. ```markdown --- model: gemini-3-pro-image-preview aspect-ratio: 1:1 flags: [] --- Full prompt text. Be explicit about subject, style, background, constraints. ``` ```bash mkdir -p prompts ``` For series: write ALL prompt files before calling any generation script. **Gate**: all prompt files written and reviewed. ## Phase 3: Select Script | Use case | Script | Subcommand | |---|---|---| | Single image, Gemini | `scripts/genera...