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 tallesborges/zdx --skill imaginegit clone --depth 1 https://github.com/tallesborges/zdxWrote 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/tallesborges/zdx/imagine)<a href="https://agentmods.dev/skills/tallesborges/zdx/imagine"><img src="https://agentmods.dev/badge/skills/tallesborges/zdx/imagine.svg" alt="Measured on agentmods" 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 | $0.00056 | $0.03509 |
| Opus 5 | $0.00028 | $0.01754 |
| Sonnet 5 | $0.00011 | $0.00702 |
| Haiku 4.5 | $0.00006 | $0.00351 |
Grade A, and why
imagine 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.
How it starts
The opening of the file, as written. The whole thing — 301 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Imagine – Image Generation & Editing via zdx imagine
Generate images from text prompts or edit existing images using Gemini, OpenAI, or Alibaba (Qwen-Image) image models. Supports text-to-image generation, image editing (inpainting, outpainting, style transfer), and multi-image composition.
CLI reference
zdx imagine --prompt <PROMPT> [OPTIONS]
Options:
-p, --prompt <PROMPT> Text prompt (required)
-s, --source <IMAGE> Source image for editing (repeatable for multi-image)
-o, --out <PATH> Output path — written exactly as given (default: $ZDX_HOME/artifacts/image-<timestamp>.<ext>)
--model <MODEL> Model override (default: gemini:gemini-3.1-flash-image-preview)
--aspect <RATIO> Aspect ratio (Gemini only; see table below)
--size <SIZE> 512px | 1K (default) | 2K | 4K
Output: prints the exact saved file path(s) to stdout. --out is honored literally; the model picks the image format (often JPEG for Gemini), so a file named .png may actually hold JPEG bytes. That is fine — zdx reads images by content, not extension. Use --out to control the path and always view/attach the printed path.
When running inside zdx (TUI, bot, or CLI), $ZDX_ARTIFACT_DIR is the preferred output location. Pass it via --out:
zdx imagine -p "..." --out "$ZDX_ARTIFACT_DIR/descriptive-name.png"
If no --out is given, images default to $ZDX_HOME/artifacts/.
Provider guidance
- Default: If you do not pass
--model,zdx imagineusesgemini:gemini-3.1-flash-image-preview. - OpenAI support:
zdx imaginealso supports bothopenai:gpt-image-2andopenai-codex:gpt-image-2. - Preferred OpenAI path: When using OpenAI, prefer
openai-codex:gpt-image-2unless the user explicitly asks for plainopenai:gpt-image-2. - Alibaba (Qwen-Image) support:
zdx imaginesupportsalibaba:qwen-image-3.0-pro,alibaba:qwen-image-3.0, andalibaba:qwen-image-2.0-pro— combined text-to-image + editing models on Alibaba DashScope. RequiresALIBABA_API_KEY. Use them when the user asks for Qwen/Alibaba image generation. - Preferred Alibaba path: Use
alibaba:qwen-image-3.0-pro. It is the strongest of the three at dense layouts, small text (~10px), and multilingual typography. Fall back toalibaba:qwen-image-3.0for cheaper/faster runs, and toalibaba:qwen-image-2.0-proonly when explicitly asked. - Gemini vs OpenAI/Alibaba:
--aspectcurrently works with Gemini only; OpenAI, OpenAI Codex, and Alibaba require--sizeinstead. - OpenAI size support: OpenAI/OpenAI Codex support
1K,2K, and4K.512pxis Gemini-only. - Alibaba size support: All Alibaba Qwen-Image models support
512px,1K, and2K(not4K).
What ships with it
1 file 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.
- 8d ago First seen · 301 lines · 56 tokens per session scan A 3ad7f9eaebef
imagine is a skill published in the GitHub repository tallesborges/zdx (20 stars, last pushed 3d ago), licensed MIT. It adds 56 tokens to every session and 3,509 once invoked, about $0.0003 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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