image-gen

# image-gen Backend-agnostic image generation workflow: single images, series with anchor-chain consistency, and batch pipelines. Two backends: Gemini (API) and Nano Banana (local scripts with post-processing). ## Reference Loading Table | Signal | Load These Files | Why | |---|---|---| | Every request (always load) | `references/series-consistency.md` | Anchor-chain and prompt-file-first rules apply to all generation | | Every request (always load) | `references/backend-selection.md` | Mode decision required before every generation | | Script output `gemini` | `references/backends/gemini.md` | Gemini API models, env vars, flags | | Script output `nano-banana` | `references/backends/nano-banana.md` | Nano Banana subcommands, flags, aspect ratios | ## Phase 1: Detect Mode and Load References Run the backend detection script — it reads environment variables and outputs a single word: ```bash python3 skills/content/image-gen/scripts/detect-backend.py ``` Output values: - `gemini` — GEMINI_API_KEY or GOOGLE_API_KEY is set - `ask` — no key found; ask the user which backend to use Load references based on output: 1. Load `references/series-consistency.md` (always — applies to every generation). 2. Load `references/backend-selection.md` (always — needed to pick mode and script). 3. Load `references/backends/gemini.md` when output is `gemini`. 4. Ask the user to set `GEMINI_API_KEY` or confirm they want to use local scripts when output is `ask`. **Gate**: references loaded,...