lingzhi227/claude-research-skills · Archived

research-planning

Design research plans and paper architectures. Given a research topic or idea, generate structured plans with methodology outlines, paper structure, dependency-ordered task lists, UML diagrams, and experiment designs. Use when starting a new research project or paper.

First seen Apr 21, 2026

Installation

$ npx skills add lingzhi227/claude-research-skills --skill research-planning

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Declared
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Repository health

Stars 29
Default branch main
Open issues 3
Status Archived

Skill metadata

Parsed from SKILL.md frontmatter.

Declared agents claude-code

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 2,901 B
  • docs SUMMARY.md 293 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 1 installs

SKILL.md

Research Planning

Create comprehensive research plans and paper architectures from a research topic or idea.

Input

  • $0 — Research topic, idea description, or paper to reproduce

References

  • 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

Workflow

Step 1: Understand the Research Context

  • Read any provided papers, code, or references
  • Identify the core research question and its significance
  • Assess available resources (datasets, compute, existing code)

Step 2: Generate Research Plan

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

Step 3: Structure the Paper

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

Step 4: Create Task Dependency Graph

  • Order tasks by dependency (data → model → training → evaluation → writing)
  • Identify parallelizable tasks
  • Flag risks and potential failure modes

Output Format

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

Rules

  • 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

Related Skills

  • Upstream: [idea-generation](../idea-generation/), [literature-review](../literature-review/)
  • Downstream: [experiment-design](../experiment-design/), [paper-assembly](../paper-assembly/)
  • See also: [atomic-decomposition](../atomic-decomposition/)