Paper Plan

Paper Plan: From Review Conclusions to Paper Outline

Generate a structured, section-by-section paper outline from: $ARGUMENTS

Constants

• REVIEWER_MODEL = gpt-5.4 — Model used via Codex MCP for outline review. Must be an OpenAI model.
• TARGET_VENUE = ICLR — Default venue. User can override (e.g., /paper-plan "topic" — venue: NeurIPS). Supported: ICLR, NeurIPS, ICML.
• MAX_PAGES — Main body page limit, measured from first page to end of Conclusion section (excluding references, appendix, and acknowledgements). ICLR=9, NeurIPS=9, ICML=8.

Inputs

The skill expects one or more of these in the project directory:

1. NARRATIVE_REPORT.md or STORY.md — research narrative with claims and evidence
2. GPT54_AUTO_REVIEW.md — auto-review loop conclusions
3. Experiment results — JSON files in figures/, screen logs, tables
4. IDEA_REPORT.md — from idea-discovery pipeline (if applicable)

If none exist, ask the user to describe the paper's contribution in 3-5 sentences.

Workflow

Step 1: Extract Claims and Evidence

Read all available narrative documents and extract:

1. Core claims (3-5 main contributions)
2. Evidence for each claim (which experiments, which metrics, which figures)
3. Known weaknesses (from reviewer feedback)
4. Suggested framing (from review conclusions)

Build a Claims-Evidence Matrix:

| Claim | Evidence | Status | Section |
|-------|----------|--------|---------|
| [claim 1] | [exp A, metric B] | Supported | §3.2 |
| [claim 2] | [exp C] | Partially supported | §4.1 |

Step 2: Determine Paper Type and Structure

Based on TARGET_VENUE and paper content, classify and select structure.

IMPORTANT: The section count is FLEXIBLE (5-8 sections). Choose what fits the content best. The templates below are starting points, not rigid constraints.

Empirical/Diagnostic paper:

1. Introduction (1.5 pages)
2. Related Work (1 page)
3. Method / Setup (1.5 pages)
4. Experiments (3 pages)
5. Analysis / Discussion (1 page)
6. Conclusion (0.5 pages)

Theory + Experiments paper:

1. Introduction (1.5 pages)
2. Related Work (1 page)
3. Preliminaries & Modeling (1.5 pages)
4. Experiments (1.5 pages)
5. Theory Part A (1.5 pages)
6. Theory Part B (1.5 pages)
7. Conclusion (0.5 pages)
— Total: 9 pages

Theory papers often need 7 sections (splitting theory into estimation + optimization, or setup + analysis). The total page budget MUST sum to MAX_PAGES.

Theory papers should:

• Include proof sketch locations (not just theorem statements)
• Plan a comparison table of prior theoretical bounds vs. this paper's bounds
• Identify which proofs go in appendix vs. main body

Method paper:

1. Introduction (1.5 pages)
2. Related Work (1 page)
3. Method (2 pages)
4. Experiments (2.5 pages)
5. Ablation / Analysis (1 page)
6. Conclusion (0.5 pages)

Step 3: Section-by-Section Planning

For each section, specify:

### §0 Abstract
- **One-sentence problem**: [what gap this paper addresses]
- **Approach**: [what we do, in one sentence]
- **Key result**: [most compelling quantitative finding]
- **Implication**: [why it matters]
- **Estimated length**: 150-250 words
- **Self-contained check**: can a reader understand this without the paper?

### §1 Introduction
- **Opening hook**: [1-2 sentences that motivate the problem]
- **Gap**: [what's missing in prior work]
- **Key questions**: [the research questions this paper answers]
- **Contributions**: [numbered list, matching Claims-Evidence Matrix]
- **Hero figure**: [describe what Figure 1 should show — MUST include clear comparison if applicable]
- **Estimated length**: 1.5 pages
- **Key citations**: [3-5 papers to cite here]

### §2 Related Work
- **Subtopics**: [2-4 categories of related work]
- **Positioning**: [how this paper differs from each category]
- **Minimum length**: 1 full page (at least 3-4 paragraphs with substantive synthesis)
- **Must NOT be just a list** — synthesize, compare, and position

### §3 Method / Setup / Preliminaries
- **Notation**: [key symbols and their meanings]
- **Problem formulation**: [formal setup]
- **Method description**: [algorithm, model, or experimental design]
- **Formal statements**: [theorems, propositions if applicable]
- **Proof sketch locations**: [which key steps appear here vs. appendix]
- **Estimated length**: 1.5-2 pages

### §4 Experiments / Main Results
- **Figures planned**:
  - Fig 1: [description, type: bar/line/table/architecture, WHAT COMPARISON it shows]
  - Fig 2: [description]
  - Table 1: [what it shows, which methods/baselines compared]
- **Data source**: [which JSON files / experiment results]

### §5 Conclusion
- **Restatement**: [contributions rephrased, not copy-pasted from intro]
- **Limitations**: [honest assessment — reviewers value this]
- **Future work**: [1-2 concrete directions]
- **Estimated length**: 0.5 pages

Step 4: Figure Plan

List every figure and table:

## Figure Plan

| ID | Type | Description | Data Source | Priority |
|----|------|-------------|-------------|----------|
| Fig 1 | Hero/Architecture | System overview + comparison | manual | HIGH |
| Fig 2 | Line plot | Training curves comparison | figures/exp_A.json | HIGH |
| Fig 3 | Bar chart | Ablation results | figures/ablation.json | MEDIUM |
| Table 1 | Comparison table | Main results vs. baselines | figures/main_results.json | HIGH |
| Table 2 | Theory comparison | Prior bounds vs. ours | manual | HIGH (theory papers) |

CRITICAL for Figure 1 / Hero Figure: Describe in detail what the figure should contain, including:

• Which methods are being compared
• What the visual difference should demonstrate
• Caption draft that clearly states the comparison

Step 5: Citation Scaffolding

For each section, list required citations:

## Citation Plan
- §1 Intro: [paper1], [paper2], [paper3] (problem motivation)
- §2 Related: [paper4]-[paper10] (categorized by subtopic)
- §3 Method: [paper11] (baseline), [paper12] (technique we build on)

Citation rules (from claude-scholar + Imbad0202/academic-research-skills):

1. NEVER generate BibTeX from memory — always verify via search or existing .bib files
2. Every citation must be verified: correct authors, year, venue
3. Flag any citation you're unsure about with [VERIFY]
4. Prefer published versions over arXiv preprints when available

Step 6: Cross-Review with REVIEWER_MODEL

Send the complete outline to GPT-5.4 xhigh for feedback:

mcp__codex__codex:
  model: gpt-5.4
  config: {"model_reasoning_effort": "xhigh"}
  prompt: |
    Review this paper outline for a [VENUE] submission.
    [full outline including Claims-Evidence Matrix]

    Score 1-10 on:
    1. Logical flow — does the story build naturally?
    2. Claim-evidence alignment — every claim backed?
    3. Missing experiments or analysis
    4. Positioning relative to prior work
    5. Page budget feasibility (MAX_PAGES = main body to Conclusion end, excluding refs/appendix)

    For each weakness, suggest the MINIMUM fix.
    Be specific and actionable — "add X" not "consider more experiments".

Apply feedback before finalizing.

Step 7: Output

Save the final outline to PAPER_PLAN.md in the project root:

# Paper Plan

**Title**: [working title]
**Venue**: [target venue]
**Type**: [empirical/theory/method]
**Date**: [today]
**Page budget**: [MAX_PAGES] pages (main body to Conclusion end, excluding references & appendix)
**Section count**: [N] (must match the number of section files that will be created)

## Claims-Evidence Matrix
[from Step 1]

## Structure
[from Step 2-3, section by section]

## Figure Plan
[from Step 4, with detailed hero figure description]

## Citation Plan
[from Step 5]

## Reviewer Feedback
[from Step 6, summarized]

## Next Steps
- [ ] /paper-figure to generate all figures
- [ ] /paper-write to draft LaTeX
- [ ] /paper-compile to build PDF

Key Rules

• Do NOT generate author information — leave author block as placeholder or anonymous
• Be honest about evidence gaps — mark claims as "needs experiment" rather than overclaiming
• Page budget is hard — if content exceeds MAX_PAGES, suggest what to move to appendix
• MAX_PAGES counts main body only — from first page to end of Conclusion. References and appendix are NOT counted.
• Venue-specific norms — all three venues (ICLR/NeurIPS/ICML) use natbib (\citep/\citet)
• Claims-Evidence Matrix is the backbone — every claim must map to evidence, every experiment must support a claim
• Figures need detailed descriptions — especially the hero figure, which must clearly specify comparisons and visual expectations
• Section count is flexible — 5-8 sections depending on paper type. Don't force content into a rigid 5-section template.

Acknowledgements

Outline methodology inspired by Research-Paper-Writing-Skills (claim-evidence mapping), claude-scholar (citation verification), and Imbad0202/academic-research-skills (claim verification protocol).