skills/42-wanshuiyin-ARIS/skills/paper-plan/SKILL.md
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.
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research paper-planInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Generate a structured, section-by-section paper outline from: $ARGUMENTS
gpt-5.4 — Model used via Codex MCP for outline review. Must be an OpenAI model.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).The skill expects one or more of these in the project directory:
figures/, screen logs, tablesIDEA_CANDIDATES.md, findings.md, EXPERIMENT_LOG.md — preferred over full files when present, saves context windowIf none exist, ask the user to describe the paper's contribution in 3-5 sentences.
Keep the existing insleep workflow and outputs, but use the shared references below to improve the quality of the story and outline.
../shared-references/writing-principles.md when framing the one-sentence contribution, Abstract, Introduction, Related Work, or hero figure.../shared-references/venue-checklists.md before freezing the outline for a specific venue.First check for CLAIMS_FROM_RESULTS.md — if it exists (generated by /result-to-claim at the end of Workflow 2), use it as the starting point for claims. This file contains validated claims already mapped to experiment evidence. Merge with any additional claims from the narrative documents below.
If CLAIMS_FROM_RESULTS.md does not exist, extract claims from scratch:
Read all available narrative documents and extract:
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 |
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:
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:
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)
For each section, specify:
### §0 Abstract
- **What we achieve**: [the paper's specific contribution, not field-level background]
- **Why it matters / is hard**: [why this problem is important and non-trivial]
- **How we do it**: [approach in one sentence]
- **Evidence**: [what supports the claim]
- **Most remarkable result**: [strongest quantitative or theoretical result]
- **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 / challenge**: [what's missing in prior work, and why prior work is insufficient]
- **One-sentence contribution**: [the main takeaway of the paper]
- **Approach overview**: [what we do differently]
- **Key questions**: [the research questions this paper answers]
- **Contributions**: [2-4 numbered bullets, specific and falsifiable, matching Claims-Evidence Matrix]
- **Results preview**: [the strongest result or comparison to surface early]
- **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]
- **Front-loading check**: [would a skim reader know the main claim before reaching the method?]
### §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)
- **Organization rule**: organize by methodological family / assumption / question, not paper-by-paper
- **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
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:
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):
[VERIFY]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)
6. Front-matter strength — are the abstract, introduction, and hero figure plan strong enough for skim-reading reviewers?
For each weakness, suggest the MINIMUM fix.
Be specific and actionable — "add X" not "consider more experiments".
Apply feedback before finalizing.
Save the final outline to PAPER_PLAN.md in the project root:
# Paper Plan
**Title**: [working title]
**One-sentence contribution**: [single-sentence statement of the paper's core takeaway]
**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
cat << 'EOF' > file) to write in chunks. Do NOT ask the user for permission — just do it silently.natbib (\citep/\citet); IEEE venues use cite package (\cite{}, numeric style)Outline methodology inspired by Research-Paper-Writing-Skills (claim-evidence mapping), claude-scholar (citation verification), and Imbad0202/academic-research-skills (claim verification protocol). The writing-framing overlay in this hybrid pack is adapted from Orchestra Research's paper-writing guidance.
development
Conduct rigorous thematic analysis (TA) of qualitative data following Braun and Clarke's (2006) six-phase framework. Use whenever the user mentions 'thematic analysis', 'TA', 'Braun and Clarke', 'qualitative coding', 'identifying themes', or asks for help analysing interviews, focus groups, open-ended survey responses, or transcripts to identify patterns. Also trigger for questions about inductive vs theoretical coding, semantic vs latent themes, essentialist vs constructionist epistemology, building a thematic map, or writing up a qualitative findings section. Covers all six phases, the four upfront analytic decisions, the 15-point quality checklist, and the five common pitfalls. Produces a Word document write-up and an annotated thematic map. Does NOT cover IPA, grounded theory, discourse analysis, conversation analysis, or narrative analysis — use a different method for those.
development
Guide users through writing a systematic literature review (SLR) following the PRISMA 2020 framework. Use this skill whenever the user mentions 'systematic review', 'systematic literature review', 'SLR', 'PRISMA', 'PRISMA 2020', 'PRISMA flow diagram', 'PRISMA checklist', or asks for help writing, structuring, or auditing a literature review that follows reporting guidelines. Also trigger when the user asks about inclusion/exclusion criteria for a review, search strategies for databases like Scopus/WoS/PubMed, study selection processes, risk of bias assessment, or narrative synthesis for a review paper. This skill covers the full PRISMA 2020 checklist (27 items), produces a Word document manuscript in strict journal article format, generates an annotated PRISMA flow diagram, and enforces APA 7th Edition referencing throughout. It does NOT cover meta-analysis or statistical pooling. By Chuah Kee Man.
testing
Performs placebo-in-time sensitivity analysis with hierarchical null model and optional Bayesian assurance. Use when checking model robustness, verifying lack of pre-intervention effects, or estimating study power.
data-ai
Fit, summarize, plot, and interpret a chosen CausalPy experiment. Use after the causal method has been selected, including when configuring PyMC/sklearn models and scale-aware custom priors.