research-refine-pipeline

To turn a vague research direction into a concrete proposal, you can run an end-to-end research pipeline that chains ideation, method refinement, and experiment planning. This workflow outputs standardized artifacts like FINAL_PROPOSAL.md and EXPERIMENT_PLAN.md.

The best way to refine research methods is to use a structured pipeline that applies stage gating across triage, refinement, and integration phases. This ensures a robust method and generates a REFINEMENT_REPORT.md to track changes before experiment planning.

An end-to-end research workflow handles proposal generation by chaining research-refine and experiment-plan steps into a unified pipeline. It produces standardized outputs including REVIEW_SUMMARY.md, EXPERIMENT_TRACKER.md, and PIPELINE_SUMMARY.md to monitor progress.

Yes, you can use a single integrated pipeline to generate both a final proposal and an actionable experiment plan. By combining the research-refine and experiment-plan workflows, it outputs FINAL_PROPOSAL.md and EXPERIMENT_PLAN.md together.

No, the research refinement pipeline does not require any specific components or dependencies to run. You simply provide the starting research direction to initiate the integrated workflow and produce the standardized output artifacts.

Chaining research refinement and experiment planning steps generates six standardized artifacts: FINAL_PROPOSAL.md, REVIEW_SUMMARY.md, REFINEMENT_REPORT.md, EXPERIMENT_PLAN.md, EXPERIMENT_TRACKER.md, and PIPELINE_SUMMARY.md.