Install
$ agentstack add skill-aravindan20-claude-research-paper-os-research-planning ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo 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.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →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):
- Overall Plan — Strategic overview: methodology, key experiments, evaluation metrics
- Architecture Design — File structure, system design, Mermaid class/sequence diagrams
- Logic Design — Task breakdown with dependencies, required packages, shared knowledge
- 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.
- Author: ARAVINDAN20
- Source: ARAVINDAN20/Claude-Research-Paper-OS
- License: Apache-2.0
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.