research-refine-pipeline
Run an end-to-end workflow that chains `research-refine` and `experiment-plan`. Use when the user wants a one-shot pipeline from vague research direction to focused final proposal plus detailed experiment roadmap, or asks to "串起来", build a pipeline, do it end-to-end, or generate both the method and experiment plan together.
Profile →npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill research-refine-pipeline --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Research Refine Pipeline: End-to-End Method and Experiment Planning Refine and concretize: **$ARGUMENTS** ## Overview Use this skill when the user does not want to stop at a refined method. The goal is to produce a coherent package that includes: - a problem-anchored, elegant final proposal - the review history explaining why the method is focused - a detailed experiment roadmap tied to the pape
What does the research-refine-pipeline skill do?
Run an end-to-end workflow that chains `research-refine` and `experiment-plan`. Use when the user wants a one-shot pipeline from vague research direction to focused final proposal plus detailed experiment roadmap, or asks to "串起来", build a pipeline, do it end-to-end, or generate both the method and experiment plan together.
How do I install it?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill research-refine-pipeline --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Auto-Empirical-Research-Skills, a repository with 3,244 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.