Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add marchatton/agent-skills --skill nano-banana-progit clone --depth 1 https://github.com/marchatton/agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/marchatton/agent-skills/nano-banana-pro)<a href="https://agentmods.dev/skills/marchatton/agent-skills/nano-banana-pro"><img src="https://agentmods.dev/badge/skills/marchatton/agent-skills/nano-banana-pro/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/marchatton/agent-skills/nano-banana-pro"><img src="https://agentmods.dev/badge/skills/marchatton/agent-skills/nano-banana-pro.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00046 | $0.00716 |
| Opus 5 | $0.00023 | $0.00358 |
| Sonnet 5 | $0.00009 | $0.00143 |
| Haiku 4.5 | $0.00005 | $0.00072 |
Grade A, and why
nano-banana-pro scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Nano Banana Pro Image Generation & Editing
Quick Start
Generate:
uv run ~/.codex/skills/nano-banana-pro/scripts/generate_image.py --prompt "A serene Japanese garden" --filename "2025-11-23-14-23-05-japanese-garden.png" --resolution 1K
Edit:
uv run ~/.codex/skills/nano-banana-pro/scripts/generate_image.py --prompt "make the sky dramatic" --filename "2025-11-23-14-25-30-dramatic-sky.png" --input-image "original.png" --resolution 2K
Compose:
uv run ~/.codex/skills/nano-banana-pro/scripts/compose_images.py "Create a group photo" group.png person1.png person2.png
Multi-turn chat:
uv run ~/.codex/skills/nano-banana-pro/scripts/multi_turn_chat.py --model gemini-3-pro-image-preview --output-dir .
Scripts
generate_image.py: text-to-image + edit via--input-image, resolution 1K/2K/4K, optional--aspect, auto-detect resolution on edit.edit_image.py: explicit edit CLI (input, instruction, output).compose_images.py: combine up to 14 reference images.multi_turn_chat.py: interactive refine session (/save,/load,/clear,/quit).gemini_images.py: Python helper class.
Model
- Default:
gemini-3-pro-image-preview. - Only use other models if user asks.
Resolution + Aspect
- Resolution:
1Kdefault,2K,4K. - Aspect ratios (where supported):
1:1,2:3,3:2,3:4,4:3,4:5,5:4,9:16,16:9,21:9. - Map words: "1080/low/1K"->1K, "2K/2048/medium"->2K, "4K/high/ultra"->4K.
Workflow
- Draft 1K, iterate small prompt diffs, final 4K.
- For edits, keep same
--input-imageuntil final.
API Key
GEMINI_API_KEYrequired.generate_image.pyalso supports--api-key.
Filenames
- Pattern:
yyyy-mm-dd-hh-mm-ss-name.png. - Lowercase, hyphenated, 1-5 words.
Output
- Run from user cwd so files save there.
generate_image.pyconverts output to PNG.- Do not open/read images; report saved path.
Preflight
command -v uvtest -n "$GEMINI_API_KEY"- If editing:
test -f "path/to/input.png"
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 71 lines · 46 tokens per session scan A cc7bce3d2eb5
nano-banana-pro is a skill published in the GitHub repository marchatton/agent-skills (5 stars, last pushed 6mo ago), licensed MIT. It adds 46 tokens to every session and 716 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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