/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.
$ npx -y skills add lingzhi227/agent-research-skills --skill research-planning --agent claude-codeHow it fires
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/research-planning
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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.
SKILL.md
research-planning.SKILL.mdname: research-planning
description: 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.
argument-hint: [topic-or-idea]
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/)
Read more
name: research-planning description: 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. argument-hint: [topic-or-idea]
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/)
31 skills for Claude Code covering the full academic research paper lifecycle — from literature search to slide generation — plus GitHub repository analysis for research topics. Extracted from 17 GitHub repos studying LLM-agent-driven research automation.
Other skills on agent-research-skills.
- /algorithm-design
Design algorithms with LaTeX pseudocode and UML diagrams. Generate algorithmic environments, Mermaid class/sequence diagrams, and ensure consistency between pseudocode and implementation. Use when formalizing methods for a paper.
Open skill - /atomic-decomposition
Decompose research ideas into atomic, self-contained concepts with bidirectional math-code mapping. For each concept, extract the math formula from papers and find code implementations. Use for complex system papers requiring formal grounding.
Open skill - /backward-traceability
Make every number in the final PDF traceable to the exact code line that produced it. Uses \hypertarget/\hyperlink LaTeX commands and \num{formula} evaluated at compile time. Use for reproducibility and data integrity verification.
Open skill - /citation-management
Manage BibTeX citations for LaTeX papers. Harvest missing citations from a draft using Semantic Scholar, validate cite keys against .bib files, deduplicate entries, and format bibliography. Use when working with references, BibTeX, or citations.
Open skill - /code-debugging
Debug experiment code with structured error analysis. Categorize errors, apply targeted fixes with retry logic, and use reflection to prevent recurring issues. Use when experiment code fails or produces incorrect results.
Open skill - /data-analysis
Generate statistical analysis code with 4-round review. Select appropriate statistical tests, interpret results, and produce analysis reports with p-values, effect sizes, and confidence intervals. Use when analyzing experimental data for a paper.
Open skill

