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

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 paper's claims a compact pipeline summary that says what to run next This skill composes two existing workflows: 1. research refine for method refinement 2. experiment plan for claim driven validation planning For stage specific detail, read these sibling skills only when needed: ../research refine/SKILL.md ../experiment plan/SKILL.md Core Rule Do not plan a large experiment suite on top of an unstable method. First stabilize the thesis. Then turn the stable thesis into experiments. Default Outputs refine logs/FINAL PROPOSAL.md refine logs/REVIEW SUMMARY.md refine logs/REFINEMENT REPORT.md refine logs/EXPERIMENT PLAN.md refine logs/EXPERIMENT TRACKER.md refine logs/PIPELINE SUMMARY.md Workflow Phase 0: Triage the Starting Point Extract the problem, rough approach, constraints, resources, and target venue. Check whether refine logs/FINAL PROPOSAL.md already exists and still matches the current request. If the proposal is missing, stale, or materially different from the current request, run the full research refine stage. If the proposal is already strong and aligned, reuse it and jump to experiment planning. If in doubt, prefer re running research refine rather than planning experiments for the wrong method. Phase 1: Method Refinement Stage Run the research refine workflow and keep its V3 philosophy intact: preserve the Problem Anchor prefer the smallest adequate mechanism keep one dominant contribution modernize only when it improves the paper Exit this stage only when these are explicit: the final method thesis the dominant contribution the complexity intentionally rejected the key claims and must run ablations the remaining risks, if any If the verdict is still REVISE , continue into experiment planning only if the remaining weaknesses are clearly documented. Phase 2: Planning Gate Before the experiment stage, write a short gate check: What is the final method thesis? What is the dominant contribution? What complexity was intentionally rejected? Which reviewer concerns still matter for validation? Is a frontier primitive central, optional, or absent? If these answers are not crisp, tighten the final proposal first. Phase 3: Experiment Planning Stage Run the experiment plan workflow grounded in: refine logs/FINAL PROPOSAL.md refine logs/REVIEW SUMMARY.md refine logs/REFINEMENT REPORT.md Ensure the experiment plan covers: the main anchor result novelty isolation a simplicity or deletion check a frontier necessity check if applicable run order, budget, and decision gates Phase 4: Integration Summary Write refine logs/PIPELINE SUMMARY.md : Phase 5: Present a Brief Summary to the User Output Protocols Follow these shared protocols for all output files: [Output Versioning Protocol](../shared references/output versioning.md) — write timestamped file first, then copy to fixed name [Output Manifest Protocol](../shared references/output manifest.md) — log every output to MANIFEST.md [Output Language Protocol](../shared references/output language.md) — respect the project's language setting Key Rules Large file handling : If the Write tool fails due to file size, immediately retry using Bash ( cat << 'EOF' file ) to write in chunks. Do NOT ask the user for permission — just do it silently. Do not let the experiment plan override the Problem Anchor. Do not widen the paper story after method refinement unless a missing validation block is truly necessary. Reuse the same claims across FINAL PROPOSAL.md , EXPERIMENT PLAN.md , and PIPELINE SUMMARY.md . Keep the main paper story compact. If the method is intentionally simple, defend that simplicity in the experiment plan rather than adding new components. If the method uses a modern LLM / VLM / Diffusion / RL primitive, make its necessity test explicit. If the method does not need a frontier primitive, say that clearly and avoid forcing one. Prefer the staged skills when the user only needs one stage; use this skill for the integrated flow. Composing with Other Skills

research-refine-pipeline