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 agentmods add skills/desirecore/market/dashscope-image-gennpx skills add desirecore/market --skill dashscope-image-gengit clone --depth 1 https://github.com/desirecore/marketWrote 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/desirecore/market/dashscope-image-gen)<a href="https://agentmods.dev/skills/desirecore/market/dashscope-image-gen"><img src="https://agentmods.dev/badge/skills/desirecore/market/dashscope-image-gen.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 | $0.00094 | $0.02621 |
| Opus 5 | $0.00047 | $0.01311 |
| Sonnet 5 | $0.00019 | $0.00524 |
| Haiku 4.5 | $0.00009 | $0.00262 |
Grade A, and why
dashscope-image-gen scanned grade A with 1 finding 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 5d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
5. **Use Bash curl throughout** — do not use the HttpRequest tool or Python How it starts
The opening of the file, as written. The whole thing — 240 lines — stays where its author put it; the contents beside it link to each section on GitHub.
dashscope-image-gen Skill
Mandatory Rules (violations cause failure)
- STRICTLY follow the execution steps below — do NOT improvise, explore alternative endpoints, or try models not listed in this document
- Must access agent-service over HTTPS — the API address is already provided in the system prompt under the local API section (e.g.
https://127.0.0.1:PORT); use it directly with-kto skip certificate verification - Must upload to media-store via
/api/media/upload—/tmpis only a transient download/decode location, never use a local path as the final output - Must use the
dc-media://protocol to display images — the only form the frontend can render correctly - Use Bash curl throughout — do not use the HttpRequest tool or Python
- Use
/images/generationsendpoint — synchronous call; the response contains b64_json image data - Only use models listed below — do NOT try dall-e-3, qwen-vl, or any model not in the Model Selection table
Provider & Default Compute
You do NOT need to specify a provider — just pass "serviceType": "image_gen" and the system will automatically route to the correct provider.
Never try to query provider lists, read compute.json, or explore available models through API calls. The models listed below are guaranteed to work.
Model Selection
| Model | Characteristics | When to use |
|---|---|---|
| gpt-image-2 | High quality, fast, versatile styles | Default — use when user does not specify a model |
| wan2.7-image | Standard high quality (requires DashScope provider) | Only when user explicitly asks for Wan / DashScope |
| wan2.7-image-pro | Flagship, 4K resolution (requires DashScope provider) | Only when user explicitly asks for top quality Wan model |
Default rule: if the user does not specify a model, use gpt-image-2.
Note: wan2.7-image and wan2.7-image-pro only work when the user has configured their own Alibaba Cloud DashScope provider. If you get an error with these models, fall back to gpt-image-2.
What ships with it
2 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.
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.
- 5d ago First seen · 240 lines · 94 tokens per session scan A 3be681fc6405
dashscope-image-gen is a skill published in the GitHub repository desirecore/market (2 stars, last pushed today), licensed MIT. It adds 94 tokens to every session and 2,621 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
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image-gen-tool
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imagegen
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rexai-image-generation
Use when the user wants to generate an image, edit an image, create visual artwork, produce text-to-image output, transform an existing image with image-to-image, or asks for 生图, 生成图片, 文生图, 图生图, text-to-image, image-to-image, AI image, picture generation, image result, image edit, or visual generation.
gemini-image-generator
Use when generating professional posed product images for e-commerce using Gemini AI with optimized prompts.
image-gen
Use when aI image generation — Stable Diffusion, Midjourney, DALL-E, ComfyUI. Prompt engineering for images, inpainting, outpainting, ControlNet. Use when working with image gen.