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Skill

/nanoresearch-planning

Produce an experiment blueprint from a research hypothesis

From plugin
nanoresearch
1.4k16 skills9 commands
Install
$ npx -y skills add OpenRaiser/NanoResearch --skill nanoresearch-planning --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/nanoresearch-planning

Context preview

The summary Claude sees to decide when to auto-load this skill.

Produce an experiment blueprint from a research hypothesis

SKILL.md

nanoresearch-planning.SKILL.md
name: nanoresearch-planning
description: Produce an experiment blueprint from a research hypothesis
version: 0.1.0

Planning Skill

Purpose

Take the selected hypothesis from ideation and produce a detailed experiment blueprint specifying datasets, baselines, evaluation metrics, and ablation groups.

Tools Required

None. This skill operates entirely through LLM reasoning over the ideation output.

Input

  • `ideation_output`: Path to `papers/ideation_output.json` produced by the ideation skill

Process

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

Output

Produces `papers/experiment_blueprint.json` containing:

  • Selected hypothesis (carried forward)
  • Dataset specifications (name, source, splits, preprocessing steps)
  • Baseline methods with references
  • Evaluation metrics and success criteria
  • Ablation study design (groups, variables, expected outcomes)
  • Resource estimates and experiment schedule
Read more
Ships withnanoresearch

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。

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