Paper plan
Skill wanshuiyin/Auto-claude-code-research-in-sleep/skills/skills-codex-claude-review/paper-plan
ARIS ⚔️ (Auto-Research-In-Sleep) — Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in — works with Claude Code, Codex, OpenClaw, or any LLM agent.
npx -y skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill paper-planAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
What its author says it does
Copied from the file, not written here
Generate a structured paper outline from review conclusions and experiment results. Use when user says \"写大纲\", \"paper outline\", \"plan the paper\", \"论文规划\", or wants to create a paper plan before writing.
SKILL.md
12.9 KB, as published. Nobody here has run it
Override for Codex users who want Claude Code, not a second Codex agent, to act as the reviewer. Install this package after
skills/skills-codex/*.This reviewer is a different model family from the Codex executor. Every overlay trace/audit records:
review_independence: cross-family acceptance_status: accepted
Paper Plan: From Review Conclusions to Paper Outline
Generate a structured, section-by-section paper outline from: $ARGUMENTS
Constants
- REVIEWER_MODEL =
claude-review— Claude reviewer invoked through the localclaude-reviewMCP bridge. SetCLAUDE_REVIEW_MODELif you need a specific Claude model override. - 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, AAAI=7 technical-content pages plus references unless the current AAAI CFP says otherwise. 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:
- NARRATIVE_REPORT.md or STORY.md — research narrative with claims and evidence
- review-stage/AUTO_REVIEW.md — auto-review loop conclusions (fall back to
./AUTO_REVIEW.mdif not found) - Experiment results — JSON files in
figures/, screen logs, tables - idea-stage/IDEA_REPORT.md — from idea-discovery pipeline (if applicable) (fall back to
./IDEA_REPORT.mdif not found) - 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.mdwhen framing the Abstract, Introduction, Related Work, or hero figure - Read
../shared-references/venue-checklists.mdbefore 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 its first line is verdict: REVIEW_UNAVAILABLE, treat the file as ABSENT for claim extraction (fall through to the narrative documents below) and then: under — assurance: submission (shared-references/assurance-contract.md; implied by — effort: max|beast) STOP — the claims were never adjudicated, rerun /result-to-claim first; under assurance: draft continue but tag every claim [unadjudicated]. Otherwise, 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:
- Core claims (3-5 main contributions)
- Evidence for each claim (which experiments, which metrics, which figures)
- Known weaknesses (from reviewer feedback)
- 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):
- NEVER generate BibTeX from memory — always verify via search or existing .bib files
- Every citation must be verified: correct authors, year, venue
- Flag any citation you're unsure about with
[VERIFY] - Prefer published versions over arXiv preprints when available
Step 6: Cross-Review with REVIEWER_MODEL
Send the complete outline to Claude review for feedback:
mcp__claude-review__review_start:
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".
After this start call, immediately save the returned jobId and poll mcp__claude-review__review_status with a bounded waitSeconds until done=true. Treat the completed status payload's response as the reviewer output, and save the completed threadId for any follow-up round.
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; AAAI main track is typically 7 technical-content pages plus references. IEEE venues: references ARE counted toward the page limit.
-
Venue-specific norms — ML conferences (ICLR/NeurIPS/ICML) use
natbib(\citep/\citet); IEEE venues usecitepackage (\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).
Output Protocols
Follow these shared protocols for all output files:
- Output Versioning Protocol — write timestamped file first, then copy to fixed name
- Output Manifest Protocol — log every output to MANIFEST.md
- Output Language Protocol — respect the project's language setting