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 DorianSchlede/nexus-template --skill google-gemini-imagegit clone --depth 1 https://github.com/DorianSchlede/nexus-templateWrote 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/dorianschlede/nexus-template/google-gemini-image)<a href="https://agentmods.dev/skills/dorianschlede/nexus-template/google-gemini-image"><img src="https://agentmods.dev/badge/skills/dorianschlede/nexus-template/google-gemini-image/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/dorianschlede/nexus-template/google-gemini-image"><img src="https://agentmods.dev/badge/skills/dorianschlede/nexus-template/google-gemini-image.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 | $0.00029 | $0.01227 |
| Opus 5 | $0.00015 | $0.00613 |
| Sonnet 5 | $0.00006 | $0.00245 |
| Haiku 4.5 | $0.00003 | $0.00123 |
Grade A, and why
google-gemini-image 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 10d 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 — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Google Gemini Image Generation
Generate brand-consistent images using AI with color theory and prompt engineering.
Quick Start
cd 03-skills/google-gemini-image
uv run python gemini-generate-image/scripts/generate_image.py "PROMPT" --output "path.png"
uv run python gemini-generate-image/scripts/generate_image.py "PROMPT" --aspect 16:9 --output "path.png"
Reference Documentation
| Topic | File | Description |
|---|---|---|
| Color Theory | color-theory.md | Color psychology, specification rules, contrast |
| Color Harmonies | color-harmonies.md | Complementary, triadic, analogous, etc. |
| Prompt Structure | prompt-structure.md | The 7-part prompt structure, golden rules |
| Style Presets | style-presets.md | Linear, Vercel, Stripe, Raycast aesthetics |
| Asset Templates | asset-templates.md | Logo, hero, social, pattern, merch templates |
| Negative Prompts | negative-prompts.md | What to avoid per asset type |
| Mutagent Brand | mutagent-brand.md | Mutagent-specific colors and guidelines |
Mutagent Colors (Quick Reference)
| Role | Color | Hex |
|---|---|---|
| Primary | Electric Purple | #7C3AED |
| Secondary | Deep Navy | #1E293B |
| Accent | Cyan | #06B6D4 |
| BG Dark | Slate 900 | #0F172A |
| BG Light | Slate 100 | #F1F5F9 |
| Success | Emerald | #10B981 |
| Warning | Amber | #F59E0B |
| Error | Rose | #F43F5E |
Asset Types & Ratios
| Type | Ratio | Use Case |
|---|---|---|
| Logo | 1:1 | Brand mark, favicon |
| Icon | 1:1 | App icons |
| Hero | 16:9 | Website headers |
| Social Profile | 1:1 | Avatar (circular crop) |
| Social Cover | 3:1 | Banner/header |
| Pattern | 1:1 | Tileable backgrounds |
| T-Shirt | 1:1 | Screen print graphic |
Style Presets (Quick Reference)
What ships with it
19 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.
- gemini-edit-image/scripts/edit_image.py 5.4 KB runs code
- gemini-edit-image/SKILL.md 1.3 KB
- gemini-generate-image/scripts/generate_image.py 4.5 KB runs code
- gemini-generate-image/SKILL.md 1.2 KB
- gemini-refine-image/scripts/refine_image.py 6.1 KB runs code
- gemini-refine-image/SKILL.md 1.6 KB
- pyproject.toml 242 B
- references/asset-templates.md 4.3 KB
- references/color-harmonies.md 2.7 KB
- references/color-theory.md 2.3 KB
- references/mutagent-brand.md 3.4 KB
- references/negative-prompts.md 2.4 KB
- references/prompt-structure.md 2.9 KB
- references/style-presets.md 2.6 KB
- scripts/check_gemini_config.py 2.5 KB runs code
- scripts/color_theory.py 11 KB runs code
- scripts/gemini_client.py 2.8 KB runs code
- scripts/prompt_engineering.py 18 KB runs code
- uv.lock 163 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.
- 10d ago First seen · 177 lines · 29 tokens per session scan A 5372409453fc
google-gemini-image is a skill published in the GitHub repository DorianSchlede/nexus-template (8 stars, last pushed 7mo ago), licensed MIT. It adds 29 tokens to every session and 1,227 once invoked, about $0.0001 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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