菜单
Write an AsPredicted pre-registration for a study. Walk through each field with the user, then produce a complete pre-registration document.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
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This is default workflow for data analysis. It includes steps for data cleaning, exploration, and visualization.
End-of-session wrap-up — updates todo.md, comms.md, and current_state.md with session summary, commits/pushes if git repo, and creates a handoff briefing for the next session. Use when the user says "log off", "wrap up", "call it a night", "done for today", or is ending a work session.
Send the user an iMessage notification when a long-running task finishes. Use after any multi-step or long-running task, especially one the user has stepped away from.
| name | aspredicted |
| description | Write an AsPredicted pre-registration for a study. Walk through each field with the user, then produce a complete pre-registration document. |
When this skill is triggered, walk the user through writing an AsPredicted pre-registration. Go field by field, drafting each section based on what you know about the study from context. Present a draft for each field and let the user revise before moving on. At the end, compile the full pre-registration into a clean document.
Have any data been collected for this study already?
What is the main question being asked or hypothesis being tested in this study?
Describe the key dependent variable(s), specifying how they will be measured.
How many and which conditions will participants be assigned to?
Specify exactly which analyses you will conduct to examine the main question/hypothesis.
Describe exactly how outliers will be defined and handled, and your precise rule(s) for excluding observations.
How many observations will be collected or what will determine sample size?
Anything else you would like to pre-register?
Give a title for this AsPredicted pre-registration.
After all fields are finalized, compile into a single clean markdown document saved to the project directory as aspredicted_<short-name>.md. Use concise, precise scientific language. Avoid hedging or filler.
