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SKILL verified Apache-2.0 Self-run

Research Planning

skill-aravindan20-claude-research-paper-os-research-planning · by ARAVINDAN20

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.

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Install

$ agentstack add skill-aravindan20-claude-research-paper-os-research-planning

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • ✓ Prompt-injection patterns
  • ✓ Secret / credential exfiltration
  • ✓ Dangerous shell & filesystem operations
  • ✓ Untrusted network calls
  • ✓ Known-malicious package signatures

What it can access

  • ✓ Network access No
  • ✓ Filesystem access No
  • ✓ Shell / process execution No
  • ✓ Environment & secrets No
  • ✓ Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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Reliability & compatibility

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About

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/)

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.