paper-plan

Generate venue-aligned paper outlines with claims-evidence mapping and gap reports.

2|Updated Aug 12, 2025
One-click install
npx skills add https://github.com/goupup-ai/miccai25 --skill paper-plan-goupup-ai
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: paper-plan
Source: https://github.com/goupup-ai/miccai25/tree/main/ARIS/skills/paper-plan
Command: npx skills add https://github.com/goupup-ai/miccai25 --skill paper-plan-goupup-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Researchers and academic writers often struggle to organize fragmented experimental results, reviewer feedback, and research narratives into a coherent, venue-compliant paper structure, wasting valuable time on layout and formatting instead of refining their core contributions.

Core Features & Use Cases

  • Claims-Evidence Alignment: Automatically extracts core claims from narrative documents, review feedback, and experiment results to build a validated claims-evidence matrix that ensures every paper claim is backed by data.
  • Venue-Specific Outline Generation: Creates structured, section-by-section paper outlines tailored to target venues (ICLR, NeurIPS, CVPR, MICCAI, IEEE, etc.) with strict page budget enforcement and formatting norm alignment.
  • Gap Reporting & Style Alignment: Supports optional style reference matching to align with target paper structures, and auto-generates gap reports to identify missing evidence slots that need additional experiments before writing.
  • Use Case: For a MICCAI 2025 vertebrae segmentation paper, use this skill to turn your auto-review conclusions and experiment results into a compliant, reviewer-friendly outline in minutes, with clear figure and citation plans.

Quick Start

Use the paper-plan skill to generate a structured, venue-compliant paper outline from your research narrative, experiment results, and review feedback.

Frequently Asked Questions about paper-plan

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate a venue-compliant paper outline from fragmented research results?

To generate a venue-compliant paper outline, input your fragmented research narratives, experimental results, and reviewer feedback to produce a structured, section-by-section outline tailored to specific conferences like ICLR, NeurIPS, or CVPR. This process enforces page budgets and aligns formatting norms automatically.

What is claims-evidence mapping in academic writing and how does it prevent unsupported claims?

Claims-evidence mapping in academic writing extracts core claims from research narratives and matches them with experimental data to build a validated matrix. This prevents unsupported claims by ensuring every paper assertion is backed by corresponding experimental results.

How do I plan figures and citations for a MICCAI or IEEE paper before writing the draft?

To plan figures and citations for a MICCAI or IEEE paper, use automated outline generation to map evidence gaps and structure section requirements. This produces clear figure and citation plans integrated directly into the venue-aligned paper outline.

Can I use automated outline generation for medical imaging and machine learning research papers?

Yes, you can use automated outline generation for medical imaging and machine learning research papers. The workflow supports researchers targeting top-tier venues like MICCAI, NeurIPS, and CVPR, turning experimental results into structured, reviewer-friendly outlines.

How do I identify missing experimental evidence before writing a conference submission?

To identify missing experimental evidence before writing a conference submission, generate an automated gap report. This report analyzes your claims-evidence matrix to highlight unsupported claims and identify missing evidence slots requiring additional experiments.

Does automated paper outlining work with reviewer feedback from previous submissions?

Yes, automated paper outlining works with reviewer feedback from previous submissions. The system ingests review feedback alongside research narratives and experimental results to produce a revised, submission-ready paper outline that addresses reviewer concerns.