aris-paper-plan

Generate a structured section-by-section paper outline from review conclusions and experiment results.

1.1k|116|Updated Feb 26, 2026
One-click install
npx skills add https://github.com/OpenLAIR/dr-claw --skill aris-paper-plan
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: aris-paper-plan
Source: https://github.com/OpenLAIR/dr-claw/tree/main/skills/aris-paper-plan
Command: npx skills add https://github.com/OpenLAIR/dr-claw --skill aris-paper-plan

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Turning scattered research artifacts—narrative reports, auto-review conclusions, and experiment results—into a coherent, venue-compliant paper outline is time-consuming and error-prone. This Skill automates the planning phase by extracting claims, mapping them to evidence, and producing a page-budgeted outline ready for drafting.

Core Features & Use Cases

  • Claims-Evidence Matrix: Extracts core claims from NARRATIVE_REPORT.md, GPT54_AUTO_REVIEW.md, and experiment JSON files, then maps every claim to supporting evidence.
  • Venue-Aware Structure: Selects paper type (empirical, theory, method) and enforces page budgets for ICLR, NeurIPS, ICML, CVPR, ACL, AAAI, ACM, and IEEE venues, including IEEE's rule that references count toward the limit.
  • Figure and Citation Planning: Produces a detailed figure plan (including a hero figure specification) and a verified citation plan that flags unverified references.
  • Automated Review Loop: Sends the outline to GPT-5.4 via Codex MCP for scored feedback on logic, claim-evidence alignment, and page feasibility before finalizing PAPER_PLAN.md.
  • Use Case: After finishing experiments for an ICLR submission, run the Skill to convert your review conclusions and result JSONs into a 9-page section-by-section outline with figure and citation plans.

Quick Start

Ask the assistant to generate a paper outline for an ICLR submission from the narrative report and experiment results in the current project directory.

Frequently Asked Questions about aris-paper-plan

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

FAQPage Schema
How do I generate a paper outline from experiment results?

Place your narrative report, auto-review conclusions, and experiment JSON files in the project directory, then invoke the Skill with your topic. It extracts claims, builds a claims-evidence matrix, and outputs a section-by-section outline saved as PAPER_PLAN.md.

What input files does the paper planning skill need?

It looks for NARRATIVE_REPORT.md or STORY.md, GPT54_AUTO_REVIEW.md, experiment result JSONs, and optionally IDEA_REPORT.md or CLAIMS_FROM_RESULTS.md. If none exist, it asks you to describe the paper's contribution in three to five sentences.

Which venues and page limits does the outline support?

Supported venues include ICLR, NeurIPS, ICML, CVPR, ACL, AAAI, ACM, and IEEE journals or conferences. ML conferences count main body pages only (ICLR/NeurIPS 9, ICML 8), while IEEE venues include references in the page count.

Does the outline get reviewed before finalizing?

Yes. The complete outline is sent to GPT-5.4 via Codex MCP with high reasoning effort, which scores logical flow, claim-evidence alignment, missing experiments, positioning, and page feasibility. Feedback is applied before writing PAPER_PLAN.md.

How are citations handled in the paper plan?

The Skill builds a per-section citation plan but never generates BibTeX from memory. Every citation must be verified through search or existing .bib files, and uncertain references are flagged with a [VERIFY] marker.

What are the limitations of automated paper outline generation?

The outline quality depends on the input artifacts; without experiment results or narrative documents, claims cannot be evidence-mapped. It also does not write the paper itself—drafting, figure generation, and LaTeX compilation are separate downstream steps.