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 farmfriend-labs/agent-skills-farming --skill nanobana-image-generatorgit clone --depth 1 https://github.com/farmfriend-labs/agent-skills-farmingWrote 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/farmfriend-labs/agent-skills-farming/nanobana-image-generator)<a href="https://agentmods.dev/skills/farmfriend-labs/agent-skills-farming/nanobana-image-generator"><img src="https://agentmods.dev/badge/skills/farmfriend-labs/agent-skills-farming/nanobana-image-generator/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/farmfriend-labs/agent-skills-farming/nanobana-image-generator"><img src="https://agentmods.dev/badge/skills/farmfriend-labs/agent-skills-farming/nanobana-image-generator.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 | $0.00000 | $0.03667 |
| Opus 5 | $0.00000 | $0.01834 |
| Sonnet 5 | $0.00000 | $0.00733 |
| Haiku 4.5 | $0.00000 | $0.00367 |
Grade A, and why
nanobana-image-generator 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 12d 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 — 459 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Nano Banana Image Generator
Google Gemini 2.5 Flash Image (Nano Banana) model for generating, editing, and creating AI-powered visual content including infographics, product photos, illustrations, and more.
Purpose
Provide farmers and agricultural content creators with AI-powered image generation capabilities using Google's Nano Banana model. This skill enables creation of professional infographics, product mockups, educational visuals, and marketing assets for agricultural documentation, presentations, and promotional materials.
Problem Solved
Creating high-quality agricultural visual content is expensive and time-consuming. Hiring designers for infographics, product photos, and illustrations costs thousands annually. Farmers need professional visuals for grant applications, market materials, educational content, and social media, but lack design skills and budgets. This skill provides free AI-powered image generation for agricultural contexts.
Capabilities
- Generate text-to-image visuals from natural language descriptions
- Create multi-panel infographics with data visualizations
- Generate product mockups and commercial photography
- Edit existing images with text prompts (add, remove, modify elements)
- Style transfer and artistic transformation
- Character consistency across multiple images (up to 14 reference images)
- Support for aspect ratios (1:1, 16:9, 21:9, 9:16, etc.)
- Multiple resolution options (1K, 2K, 4K)
- Google Search integration for real-time data grounding
- Batch image generation for multiple concepts
- Multi-turn conversation for iterative refinement
- SynthID watermark included on all generated images
Instructions
Usage by AI Agent
-
Setup API Connection
- Get API key from Google AI Studio: https://aistudio.google.com/apikey
- Set GOOGLE_API_KEY environment variable
- Install Google Generative AI Python library: pip install google-generativeai
-
Generate Simple Images
- Construct natural language prompts describing desired image
- Set model to gemini-2.5-flash-image for speed and efficiency
- Configure aspect ratio and resolution as needed
- Generate and save image to file
What ships with it
12 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.
- __init__.py 276 B runs code
- .env.example 1.3 KB
- examples/usage-examples.md 4.4 KB
- QUICK_START.md 2.1 KB
- references/documentation.md 7.5 KB
- resources/config-template.json 3.8 KB
- scripts/generator.py 10 KB runs code
- scripts/run.sh 829 B runs code
- scripts/setup.sh 1.4 KB runs code
- scripts/test.sh 1.7 KB runs code
- simple_generate.py 4.8 KB runs code
- tools.json 3.9 KB
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.
- 12d ago First seen · 459 lines · 0 tokens per session scan A 5b9d792a4bb6
nanobana-image-generator is a skill published in the GitHub repository farmfriend-labs/agent-skills-farming (2 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,667 tokens. 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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