nanobot is a small, self-hosted personal AI agent framework written in Python, providing an agent runtime that can operate through a WebUI, terminal, or chat applications. Users use it to connect language models with tools, memory, MCP integrations, scheduled automation, and multi-agent workflows. The catalogue add-ons provide skills and instructions for working with nanobot.
Getting it into your agent
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
Wrote 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/hkuds/nanobot/image-generation)<a href="https://agentmods.dev/skills/hkuds/nanobot/image-generation"><img src="https://agentmods.dev/badge/skills/hkuds/nanobot/image-generation.svg" alt="Measured on agentmods" 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 | $0.00013 | $0.00655 |
| Opus 5 | $0.00006 | $0.00328 |
| Sonnet 5 | $0.00003 | $0.00131 |
| Haiku 4.5 | $0.00001 | $0.00065 |
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 8d 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- image-generation — 100% identical, 0 lines differ
- image-generation — 89% identical, 8 lines differ
How it starts
The opening of the file, as written. The whole thing — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Image Generation
Use the generate_image tool when the user asks you to create, render, draw, design, generate, or edit an image.
If the generate_image tool is not available in the current tool list, tell the user that image generation is not enabled for this nanobot instance.
When To Use
- Text-to-image: call
generate_imagewith a concreteprompt. - Image editing: pass the saved artifact path or user image path in
reference_images. - Iterative edits in the same conversation: prefer the most recent generated image artifact if the user says things like "make it brighter", "change the background", or "try another version".
- Ambiguous edits: ask a short clarifying question if multiple recent images could be the target.
- After generating images, call the
messagetool with the artifact paths in themediaparameter to deliver them to the user.
Prompt Rules
Write prompts with enough detail for image models:
- Subject and scene.
- Composition and camera or layout.
- Style, mood, lighting, and color palette.
- Text that must appear in the image, quoted exactly.
- Constraints such as "keep the same character", "preserve the logo", or "do not change the background".
Artifact Rules
The tool stores generated images as persistent artifacts under nanobot's media directory and returns structured metadata:
id: generated image id, such asimg_ab12cd34ef56.path: local file path for internal follow-up edits.mime: image MIME type.prompt,model, andsource_images: provenance for follow-up edits.
In normal user-facing replies, do not expose local filesystem paths. Keep the reply natural, for example "Done, I generated it." You may include the short image id when it helps the user refer to a specific image, but keep raw path internal unless the user explicitly asks for debug details or a local artifact reference. Never paste base64.
For follow-up edits, pass the prior artifact path to reference_images. If the user provides a new uploaded image, use that path as the reference instead.
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.
- 8d ago First seen · 67 lines · 13 tokens per session scan A 6b93425db720
image-generation is a skill published in the GitHub repository HKUDS/nanobot (47,813 stars, last pushed today), licensed MIT. It adds 13 tokens to every session and 655 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 2026-08-30.
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