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 Wan-Video/Wan-skills --skill wan2.7-image-skillgit clone --depth 1 https://github.com/Wan-Video/Wan-skillsWrote 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/wan-video/wan-skills/wan2.7-image-skill)<a href="https://agentmods.dev/skills/wan-video/wan-skills/wan2.7-image-skill"><img src="https://agentmods.dev/badge/skills/wan-video/wan-skills/wan2.7-image-skill/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/wan-video/wan-skills/wan2.7-image-skill"><img src="https://agentmods.dev/badge/skills/wan-video/wan-skills/wan2.7-image-skill.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 | $0.00291 | $0.02481 |
| Opus 5 | $0.00146 | $0.01241 |
| Sonnet 5 | $0.00058 | $0.00496 |
| Haiku 4.5 | $0.00029 | $0.00248 |
Grade A, and why
wan2.7-image-skill 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 11d 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
1 near-identical copy found in the catalogue:
- wan2.7-image-skill — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 219 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Wan2.7 Image Generation Skill （Wan2.7 图片生成编辑技能）
Generate AI images with "Wan2.7 Image" via direct API calls.
Quick Start
1. 配置环境 → common.md
2. 了解能力 → 阅读下文核心能力介绍
3. 选择模式 → 根据需求选择三种操作模式之一
4. 详细用法 → image-generation-editing.md
核心能力：
- ✅ 文生图：纯文本生成单张图像
- ✅ 图像编辑：基于参考图的编辑、风格迁移、多图融合
- ✅ 组图生成：文生组图、图生组图（最多 12 张）
Workflow: Unified Image Generation & Editing（统一图像生成与编辑）
graph TB
A[用户请求] --> B{是否有参考图？}
B -->|无参考图 | C[文生图/文生组图]
B -->|有参考图 | D[图生图/图像编辑/图生组图]
C --> E[调用image-generation-editing.py]
D --> E
E -->|SUCCEEDED| I[返回图片 URL]
E -->|FAILED| J[错误处理]
流程说明：
- 判断模式 - 根据是否有参考图以及用户内容，选择文生图,图生图还是组图生成
- 预处理脚本执行 - 根据输入情况自动选择：
- 有文件路径：调用
scripts/file_to_oss.py --file上传文件到OSS - 有 base64 数据（如Claw chat框粘贴场景）：调用
scripts/file_to_oss.py --base64上传到OSS - 有分辨率和长宽比的需求：执行
scripts/parse_resolution.py获取size配置
- 有文件路径：调用
- 调用生成脚本 - 调用
scripts/image-generation-editing.py，根据下述三种操作模式进行对应的参数填充 - 获取结果 - 从响应中提取图片 URL（有效期 24 小时）
- 展示结果 - 把图片URL在用户交互界面中显示出来
- 保存图片 - 提示用户图片结果链接有有效期，如果用户想长期保存结果，让用户指定一个目录，把图片存进这个目录
📖 详细流程与参数： image-generation-editing.md
Three Operation Modes（三种操作模式）
Mode 1: 图像生成（文生图）
用途： 纯文本生成单张图像
输入： 文本提示词
输出： 图片
特点： 无需输入参考图
关键参数：
enable_sequential: falsen: 生成数量 1size: 分辨率 (支持 1K/2K 或自定义)
📖 详细说明与用例： image-generation-editing.md#mode-1
Mode 2: 图像编辑（图生图、风格迁移、多图融合）
用途： 基于参考图像进行编辑、风格迁移或保持主体一致性生成
输入： 文本提示词 + 1-9 张参考图
输出： 图片
特点： 输入1-9张参考图进行参考生成
关键参数：
enable_sequential: falsen: 生成数量 1size: 分辨率（支持 1K/2K 或自定义）
📖 详细说明与用例： image-generation-editing.md#mode-2
Mode 3: 组图生成
用途： 根据文本描述生成系列图像（一次生成多张关联的图片，教程、故事等）
输入： 文本提示词 + 可选参考图（最多 9 张）
输出： 最多 12 张图片
特点： 一次生成多张关联的图片，实际数量由模型决定
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.
- 11d ago First seen · 219 lines · 291 tokens per session scan A 869628bd33b2
wan2.7-image-skill is a skill published in the GitHub repository Wan-Video/Wan-skills (76 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 291 tokens to every session and 2,481 once invoked, about $0.0015 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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