What problem does it solve? Researchers often write Results and Discussion sections before experiments are complete, risking unsupported claims, untraceable contributions, and mock data leaking into final manuscripts. This Skill enforces a gated planning workflow that keeps experiment design, traceability, and placeholder data strictly separated from real evidence. ## Core Features & Use Cases - Experiment Protocol Design: Defines datasets, split strategies, baselines, metrics, ablations, efficiency and robustness checks before any results are written. - Method-Experiment Traceability: Maps every Introduction contribution to method modules, experiments, tables/figures, and allowed claims via a traceability matrix. - Mock Data Boundary Control: Enforces mock_/synthetic_ file naming, PLANNING DATA notes, and [待真实实验替换] markers so placeholder values are never presented as real findings. - Use Case: While drafting a federated learning paper, use this Skill to lock the experiment protocol, build the contribution-to-experiment traceability table, and scaffold result tables with clearly labeled mock data until real logs arrive. ## Quick Start Ask the assistant to plan the experiment protocol and result table schema for your paper's contributions before any real experiment data is available.
