Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Nano Banana Pro with auto model fallback — generate/edit images via Gemini Image API. Run via: uv run {baseDir}/scripts/generate_image.py --prompt 'desc' --filename 'out.png' [--resolution 1K|2K|4K] [-i input.png]. Supports text-to-image + image-to-image (up to 14); 1K/2K/4K. Fallback chain: gemini-2.5-flash-image → gemini-2.0-flash-exp. MUST use uv run, not python3.
Nano Banana Pro with auto model fallback — generate/edit images via Gemini Image API. Run via: uv run {baseDir}/scripts/generate_image.py --prompt 'desc' --filename 'out.png' [--resolution 1K|2K|4K] [-i input.png]. Supports text-to-image + image-to-image (up to 14); 1K/2K/4K. Fallback chain: gemini-2.5-flash-image → gemini-2.0-flash-exp. MUST use uv run, not python3.
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
Use the bundled script to generate or edit images. Automatically falls back through multiple Gemini models if one fails. ⚠️ IMPORTANT: MUST use uv run or the generate wrapper. Do NOT use python3 directly — dependencies won't be available. Generate (option A: wrapper script) {baseDir}/scripts/generate --prompt "your image description" --filename "output.png" --resolution 1K Generate (option B: uv run) uv run {baseDir}/scripts/generate_image.py --prompt "your image description" --filename "output.png" --resolution 1K Edit (single image) uv run {baseDir}/scripts/generate_image.py --prompt "edit instructions" --filename "output.png" -i "/path/in.png" --resolution 2K Multi-image composition (up to 14 images) uv run {baseDir}/scripts/generate_image.py --prompt "combine these into one scene" --filename "output.png" -i img1.png -i img2.png -i img3.png API key GEMINI_API_KEY env var Or set skills."nanobanana-pro-fallback".apiKey / skills."nanobanana-pro-fallback".env.GEMINI_API_KEY in ~/.openclaw/openclaw.json Notes Resolutions: 1K (default), 2K, 4K. Models tried in order: gemini-2.5-flash-image → gemini-2.0-flash-exp-image-generation (configurable via NANOBANANA_FALLBACK_MODELS env var). Use timestamps in filenames: yyyy-mm-dd-hh-mm-ss-name.png. The script prints a MEDIA: line for OpenClaw to auto-attach on supported chat providers. Do not read the image back; report the saved path only.
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Largest current source with strong distribution and engagement signals.