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 ayuayue/PiDeck --skill image-gengit clone --depth 1 https://github.com/ayuayue/PiDeckWrote 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/ayuayue/pideck/image-gen)<a href="https://agentmods.dev/skills/ayuayue/pideck/image-gen"><img src="https://agentmods.dev/badge/skills/ayuayue/pideck/image-gen.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 74 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 87 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00075 | $0.02397 |
| Opus 5 | $0.00037 | $0.01198 |
| Sonnet 5 | $0.00015 | $0.00479 |
| Haiku 4.5 | $0.00007 | $0.00240 |
Grade A, and why
image-gen scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -sS "$EP/generations" \ How it starts
The opening of the file, as written. The whole thing — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
图片生成(image-gen)
这是什么
当用户说「帮我画一张图」「生成一张海报」「做一个 logo」等请求时,用本技能 直接调用生图 API 出图。生成的图片保存为本地文件,交给用户在项目里使用。
生图供应商配置与「会话 LLM」完全分离:生图用的是 PiDeck 的 imagegen.json
(或用户直接提供的 baseUrl / apiKey / 模型),不碰 AI 对话用的模型配置。
第一步:确定模型与凭据
生图请求最少需要三样:baseUrl + apiKey + 模型 id。按优先级取:
-
读 PiDeck 生图配置(如果用户在用 PiDeck):
平台 配置路径 Windows 安装版 %APPDATA%\pi-desktop\imagegen.json(即C:\Users\<用户>\AppData\Roaming\pi-desktop\imagegen.json)Windows 便携版 <exe 同目录>\data\imagegen.jsonmacOS ~/Library/Application Support/pi-desktop/imagegen.jsonLinux ~/.config/pi-desktop/imagegen.json文件结构:
{ "providers": [ { "id": "ig-1", "name": "OpenAI 或 Ark", "baseUrl": "https://api.openai.com", // 根地址,端点按规则推导(见下) "apiKey": "sk-xxxx", "models": ["gpt-image-1"], // 该供应商可选模型 "extraParams": { "size": true, "output_format": false, "watermark": true }, "referenceMode": "none | edits | image-field", // 参考图 API 形态 "apiStyle": "openai | siliconflow" // 字段名/响应方言 } ], "activeProviderId": "ig-1", // 用户上次选中的供应商 "activeModel": "gpt-image-1" // 用户上次选中的模型 }- 默认用
activeProviderId+activeModel:用户上次选的,通常是想要的。 - 模型必须在该供应商的
models[]里;如果有多个模型,让用户确认用哪个(用户会指定)。
- 默认用
-
读不到配置 / 用户不在 PiDeck 里:询问用户三样东西——
baseUrl、apiKey、模型 id。并顺手问是否需要参考图(图生图)。
第二步:确定是否有参考图
用户可能要求「基于这张图改一下」(图生图 / 局部编辑)。有参考图时:
- 让用户提供图片的文件路径,或直接上传。
- 把图片转成 base64 / data URI 备用(见下文各形态)。
- 若供应商
referenceMode是none:该供应商不支持图生图,直接告诉用户 「这个供应商没开启参考图能力」,不要硬发图。
参考图约束(与 PiDeck 一致):≤ 4 张,支持 png/jpeg/webp。
第三步:拼端点 URL
baseUrl 是根地址,生图端点按下面规则推导(不要盲猜):
- 已经以
/images/generations结尾 → 直接用。 - 以版本段结尾(
/v1、/v1beta、/api、/api/v3等)→ 直接追加/images/generations。- 例:
https://ark.cn-beijing.volces.com/api/v3→.../api/v3/images/generations
- 例:
- 裸根地址 → 补
/v1再追加。- 例:
https://api.openai.com→https://api.openai.com/v1/images/generations
- 例:
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 · 172 lines · 75 tokens per session scan A 4bd23311cb40
image-gen is a skill published in the GitHub repository ayuayue/PiDeck (760 stars, last pushed today), licensed MIT. It adds 75 tokens to every session and 2,397 once invoked, about $0.0004 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 2026-08-30.
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