nanoresearch-experimen…
Generate a Python code skeleton from an experiment blueprint
Produce an experiment blueprint from a research hypothesis
$ npx -y skills add OpenRaiser/NanoResearch --skill nanoresearch-planning --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/nanoresearch-planningContext preview
The summary Claude sees to decide when to auto-load this skill.
Produce an experiment blueprint from a research hypothesis
name: nanoresearch-planning description: Produce an experiment blueprint from a research hypothesis version: 0.1.0
Take the selected hypothesis from ideation and produce a detailed experiment blueprint specifying datasets, baselines, evaluation metrics, and ablation groups.
None. This skill operates entirely through LLM reasoning over the ideation output.
1. Parse the selected hypothesis and supporting literature from the ideation output 2. Identify candidate datasets that are publicly available and appropriate for validating the hypothesis 3. Select 2-4 baseline methods from the surveyed literature for comparison 4. Define primary and secondary evaluation metrics aligned with the hypothesis 5. Design ablation groups that isolate each novel component of the proposed approach 6. Estimate computational requirements and timeline for each experiment 7. Compile everything into a structured experiment blueprint
Produces `papers/experiment_blueprint.json` containing:
端到端自主 AI 科研引擎 — 从研究想法到完整论文,全程自动化 快速开始 · 效果展示 · 流水线 · Claude Code · 飞书机器人 🔬 NanoResearch 真正运行计算实验——它不仅生成代码,还能将代码提交到 GPU 集群执行训练,收集真实实验结果,生成论文配图,最终输出一篇有实验数据支撑的完整 LaTeX 论文。论文中的每一个数据、表格、图表都来自实际运行的实验结果,而非 LLM 编造。
Generate a Python code skeleton from an experiment blueprint
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