AI导哈

数据与研究

research-refine-pipeline

wanshuiyin/auto…in-sleep

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.

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安装命令

npx skills add https://github.com/wanshuiyin/auto-claude-code-research-in-sleep --skill research-refine-pipeline

SKILL.md

Research Refine Pipeline: End-to-End Method and Experiment Planning

Before each reviewer slot, follow Selectable Reviewers: resolve invocation → .aris/reviewer.json → Claude Code default (Codex MCP) with reviewer_route.py through the canonical helper resolver, preserving this slot's tier, fresh contexts, source/image inputs and deterministic gates. Codex examples/pins below apply only to backend=codex; other routes use their own first-call/reply contract. Save the route and actual returned identity; unavailable selections are REVIEW_UNAVAILABLE. Classify acceptance from actual families/completion/scope. Forward invocation reviewer/model/effort overrides to reviewer-bearing children. Generation workers are unchanged.

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:

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