satsuki-64/miniagentworkflow/research-refine-pipeline
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Checking that the SKILL.md file is still in the repository.
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 \"\u4e32\u8d77\u6765\", build a pipeline, do it end-to-end, or generate both the method and experiment plan together.
Install
npx vskill@latest install satsuki-64/miniagentworkflow/research-refine-pipelineSKILL.md
The same SKILL.md was published earlier as loujc/auto-claude-code-research-in-sleep-manual/research-refine-pipeline.
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:
research-refinefor method refinementexperiment-planfor 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.mdrefine-logs/REVIEW_SUMMARY.mdrefine-logs/REFINEMENT_REPORT.mdrefine-logs/EXPERIMENT_PLAN.mdrefine-logs/EXPERIMENT_TRACKER.mdrefine-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.mdalready exists and still matches the current request. - If the proposal is missing, stale, or materially different from the current request, run the full
research-refinestage. - If the proposal is already strong and aligned, reuse it and jump to experiment planning.
- If in doubt, prefer re-running
research-refinerather 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.mdrefine-logs/REVIEW_SUMMARY.mdrefine-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
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, andPIPELINE_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
Security
- Security scanPassed, 90 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryChecking.skills/skills-codex/research-refine-pipeline/SKILL.md
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