research-refine-pipeline
$
npx mdskill add wanshuiyin/Auto-claude-code-research-in-sleep/research-refine-pipelineRefine and concretize: **$ARGUMENTS**
SKILL.md
.github/skills/research-refine-pipelineView on GitHub ↗
--- name: research-refine-pipeline description: 'Run an end-to-end workflow that chains `research-refine` and `experiment-plan`. Use when the user wants a one-shot pipeline from vague research direction to focused final proposal plus detailed experiment roadmap, or asks to "串起来", build a pipeline, do it end-to-end, or generate both the method and experiment plan together.' allowed-tools: Bash(*), Read, Write, Edit, Grep, Glob, WebSearch, WebFetch, mcp__codex__codex, mcp__codex__codex-reply --- # Research Refine Pipeline: End-to-End Method and Experiment Planning Refine and concretize: **$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`: ```markdown # Pipeline Summary **Problem**: [problem] **Final Method Thesis**: [one sentence] **Final Verdict**: [READY / REVISE / RETHINK] **Date**: [today] ## Final Deliverables - Proposal: `refine-logs/FINAL_PROPOSAL.md` - Review summary: `refine-logs/REVIEW_SUMMARY.md` - Experiment plan: `refine-logs/EXPERIMENT_PLAN.md` - Experiment tracker: `refine-logs/EXPERIMENT_TRACKER.md` ## Contribution Snapshot - Dominant contribution: - Optional supporting contribution: - Explicitly rejected complexity: ## Must-Prove Claims - [Claim 1] - [Claim 2] ## First Runs to Launch 1. [Run] 2. [Run] 3. [Run] ## Main Risks - [Risk]: - [Mitigation]: ## Next Action - Proceed to `/run-experiment` ``` ### Phase 5: Present a Brief Summary to the User ``` Pipeline complete. Method output: - refine-logs/FINAL_PROPOSAL.md Experiment output: - refine-logs/EXPERIMENT_PLAN.md - refine-logs/EXPERIMENT_TRACKER.md Pipeline summary: - refine-logs/PIPELINE_SUMMARY.md Best next step: - /run-experiment ``` ## 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 -> one-shot method + experiment planning /research-refine -> method refinement only /experiment-plan -> experiment planning only /run-experiment -> execution ```
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