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 davidtoby/agent-skills --skill nano-banana-progit clone --depth 1 https://github.com/davidtoby/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/davidtoby/agent-skills/nano-banana-pro)<a href="https://agentmods.dev/skills/davidtoby/agent-skills/nano-banana-pro"><img src="https://agentmods.dev/badge/skills/davidtoby/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/davidtoby/agent-skills/nano-banana-pro"><img src="https://agentmods.dev/badge/skills/davidtoby/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 | $0.00055 | $0.01511 |
| Opus 5 | $0.00028 | $0.00756 |
| Sonnet 5 | $0.00011 | $0.00302 |
| Haiku 4.5 | $0.00006 | $0.00151 |
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.
This is a copy
91% identical to nano-banana-pro — 14 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Nano Banana Pro Image Generation & Editing
Generate new images or edit existing ones using Google's Nano Banana Pro API (Gemini 3 Pro Image).
Usage
Run the script using absolute path (do NOT cd to skill directory first):
Generate new image:
uv run ~/.codex/skills/nano-banana-pro/scripts/generate_image.py --prompt "your image description" --filename "output-name.png" [--resolution 1K|2K|4K] [--api-key KEY]
Edit existing image:
uv run ~/.codex/skills/nano-banana-pro/scripts/generate_image.py --prompt "editing instructions" --filename "output-name.png" --input-image "path/to/input.png" [--resolution 1K|2K|4K] [--api-key KEY]
Important: Always run from the user's current working directory so images are saved where the user is working, not in the skill directory.
Default Workflow (draft → iterate → final)
Goal: fast iteration without burning time on 4K until the prompt is correct.
- Draft (1K): quick feedback loop
uv run ~/.codex/skills/nano-banana-pro/scripts/generate_image.py --prompt "<draft prompt>" --filename "yyyy-mm-dd-hh-mm-ss-draft.png" --resolution 1K
- Iterate: adjust prompt in small diffs; keep filename new per run
- If editing: keep the same
--input-imagefor every iteration until you’re happy.
- If editing: keep the same
- Final (4K): only when prompt is locked
uv run ~/.codex/skills/nano-banana-pro/scripts/generate_image.py --prompt "<final prompt>" --filename "yyyy-mm-dd-hh-mm-ss-final.png" --resolution 4K
Resolution Options
The Gemini 3 Pro Image API supports three resolutions (uppercase K required):
- 1K (default) - ~1024px resolution
- 2K - ~2048px resolution
- 4K - ~4096px resolution
Map user requests to API parameters:
- No mention of resolution →
1K - "low resolution", "1080", "1080p", "1K" →
1K - "2K", "2048", "normal", "medium resolution" →
2K - "high resolution", "high-res", "hi-res", "4K", "ultra" →
4K
API Key
The script checks for API key in this order:
--api-keyargument (use if user provided key in chat)GEMINI_API_KEYenvironment variable
What ships with it
3 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 · 131 lines · 55 tokens per session scan A 4ea88f4b0e95
nano-banana-pro is a skill published in the GitHub repository davidtoby/agent-skills (10 stars, last pushed 1mo ago), licensed MIT. It adds 55 tokens to every session and 1,511 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to nano-banana-pro, differing in 14 lines, and is treated as a copy.
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