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 HK-hub/AgentSkills --skill imagencngit clone --depth 1 https://github.com/HK-hub/AgentSkillsWrote 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/hk-hub/agentskills/imagencn)<a href="https://agentmods.dev/skills/hk-hub/agentskills/imagencn"><img src="https://agentmods.dev/badge/skills/hk-hub/agentskills/imagencn/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/hk-hub/agentskills/imagencn"><img src="https://agentmods.dev/badge/skills/hk-hub/agentskills/imagencn.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 | $0.00025 | $0.04850 |
| Opus 5 | $0.00013 | $0.02425 |
| Sonnet 5 | $0.00005 | $0.00970 |
| Haiku 4.5 | $0.00003 | $0.00485 |
Grade A, and why
imagenCN 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 9d 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 — 448 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ImagenCN - Alibaba Cloud Bailian Text-to-Image Skill
Overview
Generate images using Alibaba Cloud Bailian API. Default endpoint is China region.
Supports five platforms across nine model families:
- Alibaba Cloud Bailian (DashScope): Qwen-Image 2.0, Qwen-Image Edit, Qwen-Image legacy, Wan Series, Z-Image
- ByteDance Volcano Ark: Doubao-Seedream series (OpenAI-compatible REST)
- Tencent Hunyuan: Hunyuan Image 3.0 (OpenAI-compatible REST)
- Zhipu / BigModel: CogView-4 and GLM-Image (OpenAI-compatible REST)
- StepFun / 阶跃星辰: Step-2X and Step-Image-Edit (OpenAI-compatible REST)
Cross-platform support: Windows, macOS, Linux
When to Use This Skill
Automatically activate this skill when:
- User requests image generation with Chinese text or calligraphy
- Need photorealistic images or photography-style visuals
- Creating commercial posters, illustrations, or digital art
- User mentions any of these: Alibaba Cloud / Bailian / Qwen / Wan / DashScope, ByteDance / Volcano Ark / Seedream / Doubao, Tencent / Hunyuan
- Any task where AI-generated image with strong Chinese support would be helpful
Workflow
Step 1 — Refine the prompt (interactive, never skip)
Users often give short, casual descriptions ("生成一只猫"). Before calling the API, present 3 refined prompt options with different style directions. Add, as appropriate:
- Subject details (shape, colour, material, expression, pose)
- Lighting (golden hour, studio, rim light, soft diffused, neon, cinematic)
- Composition (rule of thirds, shallow depth of field, wide shot, close-up)
- Style / medium (photorealistic, oil painting, watercolour, 3D render, vector)
- Mood / atmosphere (serene, dramatic, whimsical, dystopian, elegant)
- Quality keywords (8K, hyperdetailed, award-winning, professional photography)
- For Chinese text on images: text content, placement, font style, colour, size
Label the options clearly (e.g. A / B / C) with a one-line summary of each direction. Let the user pick one, combine elements from multiple, or request a new direction. Iterate until they confirm ("go", "generate", "ok", etc.), then proceed to generation.
What ships with it
6 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.
- 9d ago First seen · 448 lines · 25 tokens per session scan A 511a18a8cae7
imagenCN is a skill published in the GitHub repository HK-hub/AgentSkills (6 stars, last pushed 25d ago), licensed MIT. It adds 25 tokens to every session and 4,850 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 2026-09-03.
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