使用方法
- 复制安装命令，在自己的智能体环境安装前先检查源码包。
- 从原始文档核对所需工具、凭据和支持的宿主。
- 说明输入材料与期望交付物，并对照来源检查输出。
npx skills add https://github.com/lilmgenius/paperthin --skill aim开始前需了解
- 安装不包含模型订阅、API 额度或访问文件的权限。
- 仓库星数和安装量反映活跃情况，不等于独立质量或安全测试。
仓库原始内容
按源仓库内容呈现，保留标题、案例、代码、表格、链接以及原文引用的演示图片。
Read the data and propose the intent behind it, for the user to confirm.
Goal
The result is a proposal the user only confirms, revises, or rejects — never a question. Asking makes the user compose a sentence they did not have ready; proposing lets them answer with a yes. If the turn ends with them writing that sentence anyway, the skill missed.
Workflow
- Read every piece of the handed-over data end to end before proposing anything.
- State the intent you read, in one line grounded in what the data actually shows.
- State briefly what you would do next on that intent.
- Ask only to confirm — right, wrong, or adjust.
Rules
- Read before proposing. A proposal without reading is a guess.
- Ground it in the data. Point at what you read, not what you assumed.
- One intent per turn. If two are plausible, propose the likelier and name the other in a clause.
- Confirm, don't compose. If the turn ends with the user assembling a sentence, redo the proposal.
- If the data is too thin to propose from, say so and stop. Do not fall back to asking.
Verification
The user's next reply is short — a yes, a correction, or a small adjustment. If they had to explain what they wanted from scratch, the proposal was wrong, or was really a question in disguise.
