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 rullerzhou-afk/pet-forge --skill pet-forgegit clone --depth 1 https://github.com/rullerzhou-afk/pet-forgeWrote 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/rullerzhou-afk/pet-forge/pet-forge)<a href="https://agentmods.dev/skills/rullerzhou-afk/pet-forge/pet-forge"><img src="https://agentmods.dev/badge/skills/rullerzhou-afk/pet-forge/pet-forge/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/rullerzhou-afk/pet-forge/pet-forge"><img src="https://agentmods.dev/badge/skills/rullerzhou-afk/pet-forge/pet-forge.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 | $0.00088 | $0.05399 |
| Opus 5.5 | $0.00035 | $0.02160 |
| Sonnet 5.5 | $0.00018 | $0.01080 |
| Haiku 4.5 | $0.00009 | $0.00540 |
Grade A, and why
pet-forge 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 27d 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 — 295 lines — stays where its author put it; the contents beside it link to each section on GitHub.
pet-forge skill —— 触发条件 + 调用流程
给 AI coding agent 看的 skill 接入文档。当用户说"我想做桌宠"时,agent 应该按本文件的指引响应。
触发条件
当用户消息中出现以下信号时,激活 pet-forge skill:
强信号(必触发)
- "我想做(自己的 / 一个)桌宠"
- "做个 SVG 桌宠 / APNG 桌宠"
- "帮我做一个 idle 动画"
- "怎么做桌宠"
- "桌宠 [角色名],[风格]"
弱信号(询问后再决定)
- "我喜欢某个现有桌宠案例"(可能想要 fork 而不是做新的)
- "想做个动画"(可能不是桌宠,可能是其他动画)
- "做个角色"(可能是设计需求,不是动画)
弱信号且上下文仍无法判断时,用一句简短问题确认目标;已经能从上下文判断时直接继续。
反触发(不要触发)
- 现有项目中的任务与桌宠造型、动画素材、状态衔接、后期或运行时验证无关
- 用户只是在问某个现有桌宠是什么,而不是动手做
第一轮响应
先从用户已经给出的内容中提取角色、拓扑、审美方向、运行时目标和路线倾向。只询问会实质影响下一步、且上下文里尚未说明的信息;不要把固定问卷当作开工门槛,也不要重复询问已经确定的内容。
当用户还没有表达清楚时,可以围绕这些维度补问:
- 角色是什么:已有设定、参考图,还是从概念开始;
- 角色拓扑:主体、脸部、肢体、附属物、道具和支撑关系;
- 审美方向:风格、材质、描边、色板与参考作品;
- 运行时与路线:目标尺寸、贴边/悬浮方式,以及 SVG、APNG 或混合路线。
路线选择决策树
用户回答"想要..."
│
├─ "循环完美 / 不付费 / 可热改" → 推荐 SVG 路线
├─ "快出成品 / 不在乎钱 / 风格化强" → 推荐 APNG 路线
├─ "不会写代码" → 推荐 APNG 路线(prompt 工程门槛低于前端动画)
├─ "想要精致圆润矢量感" → SVG 路线 + apple-precise preset
├─ "想要像素感" → SVG 路线 + pixel-art preset
├─ "自然人物动作 + 精确文字/粒子/符号" → APNG 人物层 + SVG 效果层
└─ "都想试试" → 先 SVG(启动门槛低),跑通再考虑 APNG
SVG 路线工作流(skill 引导)
第 0 步:角色拓扑盘点
先不要默认角色一定有完整头、身体、手脚和嘴巴。问清:
- 主体形态:只有头、头+身体、一团主体、道具/物件,还是其他轮廓;
- 脸部结构:有没有眼睛、嘴巴、腮红、表情符号;
- 附属结构:有没有手、脚、耳朵、尾巴、触角、翅膀、道具;
- 支撑关系:站地、悬浮、贴边、挂载,还是靠道具支撑;
- 目标动作:转头、抬低头、眼睛跟随、表情、走路、挥手、弹跳、漂浮。
根据拓扑决定后续读哪些文档:
- 有脸部方向需求 →
routes/svg/conventions/head-motion-axis.md - 有主体 / 身体转向需求 →
routes/svg/conventions/body-motion-axis.md - 有手脚、尾巴、触角、道具等附属结构 →
routes/svg/conventions/limb-rig-points.md - 有嘴巴或多表情系统 →
routes/svg/conventions/expression-mouth-system.md - 没有手脚、尾巴、触角或道具时,不要强行套附属结构 rig;退化为主体轮廓、重心 / 悬浮基准和呼吸即可
- 没有嘴巴时,不要强行套 mouth rig;用眼睛、眉毛、腮红、表情符号或整体形变表达情绪
第 1 步:确定角色基础造型
从零生图、外部 API 和已有图片共用的选图与交接方法见 shared/image-generation.md。
根据用户现有素材选择来源:
- 已有 PNG → 直接用;
- 想让 AI 生成或编辑 → 当前 Codex 有内置生图能力且用户未指定渠道时可直接使用;用户指定图像 API 时走对应服务并保存本地成品;
- 自己画 → Figma / Procreate / 其他绘图工具。
用户说“去生图”“再画一版”或指定若干方案时,已经授权了这一批图像生成。按请求的范围执行,不额外设置固定张数,也不静默扩大批次。编辑已有角色前先查看输入图片,只修改用户指定的结构或姿势,保留其余识别特征。
What ships with it
13 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.
- examples/apng-runtime-notes.md 1.7 KB
- examples/README.md 624 B
- examples/svg-case-study-notes.md 1.5 KB
- examples/svg-gpt-pear/idle.svg.html 1.6 KB
- examples/svg-gpt-pear/pear-gpt-5.5-pro.svg 12 KB
- examples/svg-gpt-pear/pear.svg 21 KB
- examples/svg-gpt-pear/README.md 2.1 KB
- examples/svg-gpt-pear/source.png 356 KB
- examples/svg-soft-orb/idle.svg.html 3.2 KB
- examples/svg-soft-orb/README.md 1.1 KB
- examples/svg-soft-orb/soft-orb.svg 60 KB
- examples/svg-soft-orb/source.png 9.8 KB
- scripts/validate.mjs 5.7 KB runs code
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.
- 27d ago Changed · +10 lines · -1 tokens per session dbacb9843b10
- 1mo ago Changed · +17 lines · +8 tokens per session 99e60fd5635f
- 1mo ago Changed · +3 lines 32366937b30b
- 1mo ago First seen · 265 lines · 81 tokens per session scan A 141dba07f0a0
pet-forge is a skill published in the GitHub repository rullerzhou-afk/pet-forge (65 stars, last pushed 27d ago), licensed MIT. It adds 88 tokens to every session and 5,399 once invoked, about $0.0004 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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