research-planning

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Research Planning

研究规划

Create comprehensive research plans and paper architectures from a research topic or idea.
基于研究主题或想法生成完整的研究计划和论文架构。

Input

输入

  • $0
    — Research topic, idea description, or paper to reproduce
  • $0
    — 研究主题、想法描述,或待复现的论文

References

参考资料

  • Planning prompts from Paper2Code, AI-Researcher, AgentLaboratory:
    ~/.claude/skills/research-planning/references/planning-prompts.md
  • Output schemas and templates:
    ~/.claude/skills/research-planning/references/output-schemas.md
  • 来自Paper2Code、AI-Researcher、AgentLaboratory的规划提示词:
    ~/.claude/skills/research-planning/references/planning-prompts.md
  • 输出schema与模板:
    ~/.claude/skills/research-planning/references/output-schemas.md

Workflow

工作流

Step 1: Understand the Research Context

步骤1:理解研究背景

  • Read any provided papers, code, or references
  • Identify the core research question and its significance
  • Assess available resources (datasets, compute, existing code)
  • 阅读所有提供的论文、代码或参考资料
  • 明确核心研究问题及其意义
  • 评估现有可用资源(数据集、算力、现有代码)

Step 2: Generate Research Plan

步骤2:生成研究计划

Use the 4-stage planning approach (adapted from Paper2Code):
  1. Overall Plan — Strategic overview: methodology, key experiments, evaluation metrics
  2. Architecture Design — File structure, system design, Mermaid class/sequence diagrams
  3. Logic Design — Task breakdown with dependencies, required packages, shared knowledge
  4. Configuration — Extract or specify hyperparameters, training details, config.yaml
使用4阶段规划方法(改编自Paper2Code):
  1. 整体规划 — 战略概览:方法、核心实验、评估指标
  2. 架构设计 — 文件结构、系统设计、Mermaid类图/时序图
  3. 逻辑设计 — 带依赖关系的任务拆解、所需依赖包、共享知识
  4. 配置项 — 提取或指定超参数、训练细节、config.yaml

Step 3: Structure the Paper

步骤3:搭建论文结构

Design the paper structure with section-by-section plan:
  • Abstract, Introduction, Background, Related Work, Methods, Experiments, Results, Discussion/Conclusion
  • For each section: key points to cover, required figures/tables, target word count
设计论文结构并给出逐节规划:
  • 摘要、引言、背景、相关工作、研究方法、实验、结果、讨论/结论
  • 针对每个章节:需覆盖的核心要点、所需图表、目标字数

Step 4: Create Task Dependency Graph

步骤4:生成任务依赖图

  • Order tasks by dependency (data → model → training → evaluation → writing)
  • Identify parallelizable tasks
  • Flag risks and potential failure modes
  • 按依赖关系排序任务(数据 → 模型 → 训练 → 评估 → 撰写)
  • 识别可并行执行的任务
  • 标注风险和潜在失败模式

Output Format

输出格式

json
{
  "research_question": "...",
  "methodology": "...",
  "paper_structure": {
    "sections": ["Abstract", "Introduction", ...],
    "section_plans": { "Introduction": "..." }
  },
  "task_list": [
    {"task": "...", "depends_on": [], "priority": 1}
  ],
  "baselines": ["..."],
  "datasets": ["..."],
  "evaluation_metrics": ["..."],
  "risks": ["..."]
}
json
{
  "research_question": "...",
  "methodology": "...",
  "paper_structure": {
    "sections": ["Abstract", "Introduction", ...],
    "section_plans": { "Introduction": "..." }
  },
  "task_list": [
    {"task": "...", "depends_on": [], "priority": 1}
  ],
  "baselines": ["..."],
  "datasets": ["..."],
  "evaluation_metrics": ["..."],
  "risks": ["..."]
}

Rules

规则

  • Each plan component must be detailed and actionable
  • Include specific implementation references when available
  • Ensure all components work together coherently
  • Always include a testing/evaluation plan
  • Flag ambiguities explicitly rather than making assumptions
  • 每个计划模块都必须详细且可执行
  • 如有可用的具体实现参考资料需包含在内
  • 确保所有模块逻辑连贯一致
  • 必须包含测试/评估计划
  • 明确标注歧义内容,而非自行假设

Related Skills

相关技能

  • Upstream: idea-generation, literature-review
  • Downstream: experiment-design, paper-assembly
  • See also: atomic-decomposition
  • 上游:idea-generationliterature-review
  • 下游:experiment-designpaper-assembly
  • 另见:atomic-decomposition