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 allenhutchison/obsidian-gemini --skill image-generationgit clone --depth 1 https://github.com/allenhutchison/obsidian-geminiWrote 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/allenhutchison/obsidian-gemini/image-generation)<a href="https://agentmods.dev/skills/allenhutchison/obsidian-gemini/image-generation"><img src="https://agentmods.dev/badge/skills/allenhutchison/obsidian-gemini/image-generation/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/allenhutchison/obsidian-gemini/image-generation"><img src="https://agentmods.dev/badge/skills/allenhutchison/obsidian-gemini/image-generation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00036 | $0.00629 |
| Opus 5.5 | $0.00014 | $0.00252 |
| Sonnet 5.5 | $0.00007 | $0.00126 |
| Haiku 4.5 | $0.00004 | $0.00063 |
Grade A, and why
image-generation 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 2mo 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 — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Image Generation
Generate images from text descriptions using the generate_image tool and embed them in vault notes.
How to Use
Call the generate_image tool with these parameters:
prompt(required) — A detailed text description of the image to generate.target_note(optional) — Path to a note that determines which attachment folder the image is saved to. If omitted, the currently active note is used.
Critical Two-Step Workflow
The generate_image tool only generates and saves the image file — it does NOT insert the image into any note. To embed the image in a note:
- Call
generate_imagewith your prompt - Use the returned
wikilink(e.g.,![[generated-image.png]]) and insert it into the target note withwrite_file
Always complete both steps when the user wants an image in a specific note.
Prompt Engineering Tips
Write detailed, specific prompts for the best results:
- Be descriptive — "A serene mountain lake at sunset with snow-capped peaks reflected in still water" is much better than "a lake"
- Specify style — Include keywords like: photorealistic, watercolor, minimalist, sketch, oil painting, digital art, flat illustration, isometric
- Include composition — Mention perspective: close-up, wide angle, aerial view, eye-level, birds-eye view
- Set the mood — Describe lighting and atmosphere: warm golden hour light, dramatic shadows, soft diffused lighting, moody fog
- State what to avoid — If certain elements shouldn't appear, mention that in the prompt
Example Prompts
- "A minimalist flat illustration of a bookshelf filled with colorful books, soft pastel colors, clean lines, white background"
- "Photorealistic close-up of a mechanical keyboard with cherry blossom keycaps, shallow depth of field, warm desk lamp lighting"
- "Watercolor painting of a cozy reading nook with an armchair, stack of books, and a steaming cup of tea, warm autumn tones"
Common Use Cases
- Note illustrations — Visual headers or concept diagrams for notes
- Creative projects — Story illustrations, mood boards, concept art
- Blog and presentation images — Custom visuals for published content
- Visual thinking — Generating images to explore ideas or concepts
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.
- 2mo ago First seen · 54 lines · 36 tokens per session scan A e58bb2681cef
image-generation is a skill published in the GitHub repository allenhutchison/obsidian-gemini (534 stars, last pushed today), licensed MIT. It adds 36 tokens to every session and 629 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
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