Awesome-Agent-Skills-for-Empirical-Research paper-plan

Generate a structured paper outline from review conclusions and experiment results. Use when user says \\\"\u5199\u5927\u7eb2\\\", \\\"paper outline\\\", \\\"plan the paper\\\", \\\"\u8bba\u6587\u89c4\u5212\\\", or wants to create a paper plan before writing.

install
source · Clone the upstream repo
git clone https://github.com/brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/42-wanshuiyin-ARIS/skills/skills-codex/paper-plan" ~/.claude/skills/brycewang-stanford-awesome-agent-skills-for-empirical-research-paper-plan-f200d4 && rm -rf "$T"
manifest: skills/42-wanshuiyin-ARIS/skills/skills-codex/paper-plan/SKILL.md
source content

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 a secondary Codex agent 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
    ,
    CVPR
    ,
    ACL
    ,
    AAAI
    ,
    ACM
    ,
    IEEE_JOURNAL
    (IEEE Transactions / Letters),
    IEEE_CONF
    (IEEE conferences).
  • MAX_PAGES — Page limit. For ML conferences: main body to Conclusion end (excluding references, appendix). ICLR=9, NeurIPS=9, ICML=8. For IEEE venues: references ARE included in page count. IEEE journal Transactions ≈ 12-14 pages total, Letters ≈ 4-5 pages total; IEEE conference ≈ 5-8 pages total (including references).

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)
  5. CLAIMS_FROM_RESULTS.md — structured claim judgment from
    /result-to-claim
    (preferred if available)

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

Orchestra-Guided Writing Overlay

Keep the existing workflow and outputs, but use the shared references below to improve the quality of the story and outline:

  • Read
    ../shared-references/writing-principles.md
    when framing the Abstract, Introduction, Related Work, or hero figure
  • Read
    ../shared-references/venue-checklists.md
    before freezing the outline for a specific venue
  • Load these references only when they help; they are support material, not a new workflow phase

Workflow

Step 1: Extract Claims and Evidence

First check for

CLAIMS_FROM_RESULTS.md
— if it exists, use it as the starting point for claims and merge it with any additional evidence from the narrative documents below.

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.

Before committing to a structure, apply the narrative principle from

../shared-references/writing-principles.md
:

  • The paper should tell one coherent technical story
  • By the end of the Introduction, the outline should make the What, Why, and So What explicit
  • Front-load the most important material: title, abstract, introduction, and hero figure

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:

spawn_agent:
  model: gpt-5.4
  reasoning_effort: xhigh
  message: |
    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

  • Large file handling: If the Write tool fails due to file size, immediately retry using Bash (

    cat << 'EOF' > file
    ) to write in chunks. Do NOT ask the user for permission — just do it silently.

  • 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 counting differs by venue — ML conferences: main body to Conclusion end, references/appendix NOT counted. IEEE venues: references ARE counted toward the page limit.

  • Venue-specific norms — ML conferences (ICLR/NeurIPS/ICML) use

    natbib
    (
    \citep
    /
    \citet
    ); IEEE venues use
    cite
    package (
    \cite{}
    , numeric style)

  • 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).