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 wpsnote/wpsnote-skills --skill image-gengit clone --depth 1 https://github.com/wpsnote/wpsnote-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/wpsnote/wpsnote-skills/image-gen)<a href="https://agentmods.dev/skills/wpsnote/wpsnote-skills/image-gen"><img src="https://agentmods.dev/badge/skills/wpsnote/wpsnote-skills/image-gen/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/wpsnote/wpsnote-skills/image-gen"><img src="https://agentmods.dev/badge/skills/wpsnote/wpsnote-skills/image-gen.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 | $0.00176 | $0.02485 |
| Opus 5.5 | $0.00070 | $0.00994 |
| Sonnet 5.5 | $0.00035 | $0.00497 |
| Haiku 4.5 | $0.00018 | $0.00248 |
Grade A, and why
image-gen 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 1mo 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 — 261 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Image Gen — AI 图像生成
支持文生图 + 图生图，自动管理 API Key，生成结果可直接插入 WPS 笔记。
铁律
- API Key 不得在对话中输出，无论任何情况
encrypt-key子命令输出的ciphertext_b64可以展示（这是密文，不是真实 Key）- 告警文案必须完整展示，不可省略
- 模型名称不允许修改，不允许用户自定义。每个 provider 只有唯一一个确认可用的模型，AI 必须严格使用下表中的值，不得根据用户描述、偏好或自行推断填写其他模型名——任何其他模型名均视为幻觉：
| provider | 唯一可用模型（硬编码，不可改动） |
|---|---|
| openrouter | google/gemini-3.1-flash-image-preview |
| dashscope（百炼） | qwen-image-2.0-pro |
| ark（即梦） | doubao-seedream-5-0-260128 |
| gemini | gemini-3-pro-image-preview |
用户只能选择用哪个 provider，模型由 AI 根据上表自动填入，任何情况下不接受覆盖。
核心流程
确认需求 → 确定 provider + model → 获取/解密 Key → 执行生图 → 询问是否插入笔记
Step 1：确认生图需求
询问：
请告诉我：
1. 生图描述（prompt）是什么？
2. 有参考图吗？（有 → 图生图；没有 → 文生图）
3. 比例偏好？（1:1 / 16:9 / 9:16 / 4:3 / 3:4，默认 1:1）
- 无参考图 → 文生图，全部 provider 可用
- 有参考图 → 图生图，仅 openrouter（本地文件）/ gemini（本地文件）/ ark即梦（公网 URL）支持；百炼不支持图生图
Step 2：确定 Provider
让用户从以下四个 provider 中选一个，模型由 AI 自动填入（见铁律）：
| provider | 特点 | 适合场景 |
|---|---|---|
| openrouter | 走代理，文生图 + 图生图（本地文件垫图） | 代理环境，需要图生图 |
| dashscope（百炼） | 国内直连，仅文生图 | 国内网络，纯文生图 |
| ark（即梦） | 国内直连，文生图 + 图生图（垫图须公网 URL） | 国内网络，需要图生图 |
| gemini | 走代理，文生图 + 图生图（本地文件垫图） | 代理环境，Google 直连 |
用户未指定时，根据是否有代理、是否需要图生图主动推荐。
openrouter / gemini 国内需要代理，询问用户是否提供
--proxy。
Step 3：获取 Key
3.1 先搜笔记
search_notes 搜索 图像生成 Key，找到后 read_note 读取，在表格中找 provider 对应行，取出 ciphertext_b64 和 note_id。
找到密文 → 直接进入 Step 4（note 模式，脚本自动解密）。
找不到笔记或对应行 → 进入 Step 3.2。
3.2 向用户索取 Key
我需要 {provider} 的 API Key 才能继续。
获取地址：{平台 URL}
请直接粘贴你的 Key：
| provider | Key 获取地址 |
|---|---|
| openrouter | https://openrouter.ai/workspaces/default/keys |
| dashscope | https://bailian.console.aliyun.com/cn-beijing?tab=model#/api-key |
| ark | https://console.volcengine.com/ark/ |
| gemini | https://aistudio.google.com/app/api-keys |
收到 Key 后询问是否保存（见 Step 3.3）。
3.3 询问是否保存 Key
必须完整展示以下告警：
⚠️ 安全风险告知（请认真阅读）
如果你选择保存，Key 将以 AES 加密后存入 WPS 笔记：
- 加密密钥由「本机设备 ID + 笔记 ID + provider」现场派生，本机无需存储额外文件
- WPS 笔记不会获取你的 Key 内容，密文在其他设备上无法解密
- ⚠️ 如果你添加了第三方 MCP 插件，该插件可读取笔记内容（含密文）
- ⚠️ 换设备后，同一密文无法解密，需重新保存
是否保存？ A. 保存（我已知悉风险） B. 不保存（本次临时使用）
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.
- 1mo ago First seen · 261 lines · 176 tokens per session scan A 6e292ce2d71f
image-gen is a skill published in the GitHub repository wpsnote/wpsnote-skills (183 stars, last pushed today), licensed MIT. It adds 176 tokens to every session and 2,485 once invoked, about $0.0007 per session on Opus 5.5. 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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