image-gen · git:20260701.526d880 · 2026-07-01 · sha256 754508dc90981ffb
image-gen git:20260701.526d880A
Immutable. This exact content is served forever at /api/v1/blob/754508dc90981ffb.
---
name: image-gen
description: "AI image generation: Gemini and Nano Banana backends; single/series/batch workflows with prompt-to-disk."
agent: python-general-engineer
user-invocable: false
routing:
category: image-generation
triggers:
- generate image
- create image
- image generation
- AI image
- gemini image
- make image
- draw
- illustrate
- sprite generation
- card art
- batch generation
- series of images
- character art
- pixel art
- image post-processing
not_for: "HTML visualization or charts (use html-artifact), or deterministic non-AI palette/matrix pixel art (use game-asset-generator)"
pairs_with:
- python-general-engineer
- game-sprite-pipeline
---
# 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, backend confirmed before Phase 2.
## Phase 2: Write Prompt File
Write the complete prompt to disk before any API call. Prompt files serve as the generation record and the anchor-chain input for series — writing them first means the full intent is on disk before any quota is spent.
File naming:
- Single image: `prompts/YYYY-MM-DD-{slug}.md`
- Series: `prompts/{series-name}-01.md`, `prompts/{series-name}-02.md`, ...
Prompt file format:
```markdown
---
model: gemini-3-pro-image-preview
aspect-ratio: 1:1
flags: []
---
Full prompt text here. Be explicit about subject, style, background, and constraints.
```
Create the `prompts/` directory if absent:
```bash
mkdir -p prompts
```
For a series, write all prompt files before calling any generation script. See `references/series-consistency.md` for the anchor-chain algorithm and why this ordering prevents drift.
**Gate**: all prompt files written and reviewed before Phase 3.
## Phase 3: Select Mode and Script
Use `references/backend-selection.md` to map the request to the correct script and subcommand.
| Use case | Script | Notes |
|---|---|---|
| Single image, Gemini | `scripts/generate_image.py` | `--prompt` flag |
| Batch from prompt file, Gemini | `scripts/generate_image.py` | `--batch` flag |
| Single or batch with post-processing | `scripts/nano-banana-generate.py` | Full flag set in backend ref |
| Series with anchor chain | `scripts/nano-banana-generate.py with-reference` | Load ref images from previous outputs |
| Post-processing only | `scripts/nano-banana-process.py` | crop, remove-bg, pipeline subcommands |
**Gate**: script and subcommand identified before Phase 4.
## Phase 4: Generate
Call the selected script with absolute paths for output files — relative paths break when scripts run from different working directories.
For series generation, follow the anchor-chain sequence from `references/series-consistency.md`:
1. Generate image 1 with no reference.
2. Use output of image 1 as `--reference` for image 2.
3. Continue: each image references the previous output.
Show the full script output — the user needs status messages, warnings, and partial failure information.
**Gate**: script exits 0 before Phase 5.
## Phase 5: Verify and Report
Visual inspection is mandatory. Read the generated image file to verify:
- Subject matches the prompt
- No unwanted watermarks, logos, or artifacts
- Aspect ratio and framing are correct
- No excessive padding or dark borders that need cropping
If visual inspection fails: regenerate with an adjusted prompt. Report the issue clearly before retrying.
Report to the user:
- Output file path (absolute)
- Image dimensions
- Model used
- Post-processing applied (if any)
- Visual verification result
Report only what was requested. The user did not ask for style suggestions or additional generations.
## Error Handling
| Error | Cause | Resolution |
|---|---|---|
| `GEMINI_API_KEY not set` | Missing env var | `export GEMINI_API_KEY=your_key` or `export GOOGLE_API_KEY=your_key` |
| `No image in response` | Prompt triggered safety filter or text-only response | Adjust prompt phrasing; check for policy-violating content |
| `Missing dependency: google-genai` | Package not installed | `pip install google-genai pillow` |
| `Rate limit exceeded (429)` | Too many API calls | Increase `--delay`; default 2s may be too aggressive on free tier |
| `Content policy violation (400)` | Restricted prompt content | Rephrase using neutral language; this restriction is API-side |
| `No image data in response` | API returned text only | Set `response_modalities=["IMAGE", "TEXT"]` in config |